WorldWideScience

Sample records for drug discovery research

  1. Open source drug discovery--a new paradigm of collaborative research in tuberculosis drug development.

    Science.gov (United States)

    Bhardwaj, Anshu; Scaria, Vinod; Raghava, Gajendra Pal Singh; Lynn, Andrew Michael; Chandra, Nagasuma; Banerjee, Sulagna; Raghunandanan, Muthukurussi V; Pandey, Vikas; Taneja, Bhupesh; Yadav, Jyoti; Dash, Debasis; Bhattacharya, Jaijit; Misra, Amit; Kumar, Anil; Ramachandran, Srinivasan; Thomas, Zakir; Brahmachari, Samir K

    2011-09-01

    It is being realized that the traditional closed-door and market driven approaches for drug discovery may not be the best suited model for the diseases of the developing world such as tuberculosis and malaria, because most patients suffering from these diseases have poor paying capacity. To ensure that new drugs are created for patients suffering from these diseases, it is necessary to formulate an alternate paradigm of drug discovery process. The current model constrained by limitations for collaboration and for sharing of resources with confidentiality hampers the opportunities for bringing expertise from diverse fields. These limitations hinder the possibilities of lowering the cost of drug discovery. The Open Source Drug Discovery project initiated by Council of Scientific and Industrial Research, India has adopted an open source model to power wide participation across geographical borders. Open Source Drug Discovery emphasizes integrative science through collaboration, open-sharing, taking up multi-faceted approaches and accruing benefits from advances on different fronts of new drug discovery. Because the open source model is based on community participation, it has the potential to self-sustain continuous development by generating a storehouse of alternatives towards continued pursuit for new drug discovery. Since the inventions are community generated, the new chemical entities developed by Open Source Drug Discovery will be taken up for clinical trial in a non-exclusive manner by participation of multiple companies with majority funding from Open Source Drug Discovery. This will ensure availability of drugs through a lower cost community driven drug discovery process for diseases afflicting people with poor paying capacity. Hopefully what LINUX the World Wide Web have done for the information technology, Open Source Drug Discovery will do for drug discovery. Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. Plant natural products research in tuberculosis drug discovery and ...

    African Journals Online (AJOL)

    Plant natural products research in tuberculosis drug discovery and development: A situation report ... African Journal of Biotechnology ... tuberculosis (XDR-TB), call for the development of new anti-tuberculosis drugs to combat this disease.

  3. Computational methods in drug discovery

    Directory of Open Access Journals (Sweden)

    Sumudu P. Leelananda

    2016-12-01

    Full Text Available The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

  4. Arthritis Genetics Analysis Aids Drug Discovery

    Science.gov (United States)

    ... NIH Research Matters January 13, 2014 Arthritis Genetics Analysis Aids Drug Discovery An international research team identified 42 new ... Edition Distracted Driving Raises Crash Risk Arthritis Genetics Analysis Aids Drug Discovery Oxytocin Affects Facial Recognition Connect with Us ...

  5. Computational methods in drug discovery

    OpenAIRE

    Sumudu P. Leelananda; Steffen Lindert

    2016-01-01

    The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery project...

  6. Antibody informatics for drug discovery

    DEFF Research Database (Denmark)

    Shirai, Hiroki; Prades, Catherine; Vita, Randi

    2014-01-01

    to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic...... infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies...... for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii...

  7. Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field.

    Science.gov (United States)

    Wójcikowski, Maciej; Zielenkiewicz, Piotr; Siedlecki, Pawel

    2015-01-01

    There has been huge progress in the open cheminformatics field in both methods and software development. Unfortunately, there has been little effort to unite those methods and software into one package. We here describe the Open Drug Discovery Toolkit (ODDT), which aims to fulfill the need for comprehensive and open source drug discovery software. The Open Drug Discovery Toolkit was developed as a free and open source tool for both computer aided drug discovery (CADD) developers and researchers. ODDT reimplements many state-of-the-art methods, such as machine learning scoring functions (RF-Score and NNScore) and wraps other external software to ease the process of developing CADD pipelines. ODDT is an out-of-the-box solution designed to be easily customizable and extensible. Therefore, users are strongly encouraged to extend it and develop new methods. We here present three use cases for ODDT in common tasks in computer-aided drug discovery. Open Drug Discovery Toolkit is released on a permissive 3-clause BSD license for both academic and industrial use. ODDT's source code, additional examples and documentation are available on GitHub (https://github.com/oddt/oddt).

  8. Deep Learning in Drug Discovery.

    Science.gov (United States)

    Gawehn, Erik; Hiss, Jan A; Schneider, Gisbert

    2016-01-01

    Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of "deep learning". Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Maximum Entropy in Drug Discovery

    Directory of Open Access Journals (Sweden)

    Chih-Yuan Tseng

    2014-07-01

    Full Text Available Drug discovery applies multidisciplinary approaches either experimentally, computationally or both ways to identify lead compounds to treat various diseases. While conventional approaches have yielded many US Food and Drug Administration (FDA-approved drugs, researchers continue investigating and designing better approaches to increase the success rate in the discovery process. In this article, we provide an overview of the current strategies and point out where and how the method of maximum entropy has been introduced in this area. The maximum entropy principle has its root in thermodynamics, yet since Jaynes’ pioneering work in the 1950s, the maximum entropy principle has not only been used as a physics law, but also as a reasoning tool that allows us to process information in hand with the least bias. Its applicability in various disciplines has been abundantly demonstrated. We give several examples of applications of maximum entropy in different stages of drug discovery. Finally, we discuss a promising new direction in drug discovery that is likely to hinge on the ways of utilizing maximum entropy.

  10. Virtual drug discovery: beyond computational chemistry?

    Science.gov (United States)

    Gilardoni, Francois; Arvanites, Anthony C

    2010-02-01

    This editorial looks at how a fully integrated structure that performs all aspects in the drug discovery process, under one company, is slowly disappearing. The steps in the drug discovery paradigm have been slowly increasing toward virtuality or outsourcing at various phases of product development in a company's candidate pipeline. Each step in the process, such as target identification and validation and medicinal chemistry, can be managed by scientific teams within a 'virtual' company. Pharmaceutical companies to biotechnology start-ups have been quick in adopting this new research and development business strategy in order to gain flexibility, access the best technologies and technical expertise, and decrease product developmental costs. In today's financial climate, the term virtual drug discovery has an organizational meaning. It represents the next evolutionary step in outsourcing drug development.

  11. Computational neuropharmacology: dynamical approaches in drug discovery.

    Science.gov (United States)

    Aradi, Ildiko; Erdi, Péter

    2006-05-01

    Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.

  12. Orphan diseases: state of the drug discovery art.

    Science.gov (United States)

    Volmar, Claude-Henry; Wahlestedt, Claes; Brothers, Shaun P

    2017-06-01

    Since 1983 more than 300 drugs have been developed and approved for orphan diseases. However, considering the development of novel diagnosis tools, the number of rare diseases vastly outpaces therapeutic discovery. Academic centers and nonprofit institutes are now at the forefront of rare disease R&D, partnering with pharmaceutical companies when academic researchers discover novel drugs or targets for specific diseases, thus reducing the failure risk and cost for pharmaceutical companies. Considerable progress has occurred in the art of orphan drug discovery, and a symbiotic relationship now exists between pharmaceutical industry, academia, and philanthropists that provides a useful framework for orphan disease therapeutic discovery. Here, the current state-of-the-art of drug discovery for orphan diseases is reviewed. Current technological approaches and challenges for drug discovery are considered, some of which can present somewhat unique challenges and opportunities in orphan diseases, including the potential for personalized medicine, gene therapy, and phenotypic screening.

  13. Translational medicine and drug discovery

    National Research Council Canada - National Science Library

    Littman, Bruce H; Krishna, Rajesh

    2011-01-01

    ..., and examples of their application to real-life drug discovery and development. The latest thinking is presented by researchers from many of the world's leading pharmaceutical companies, including Pfizer, Merck, Eli Lilly, Abbott, and Novartis, as well as from academic institutions and public- private partnerships that support translational research...

  14. Revisiting lab-on-a-chip technology for drug discovery.

    Science.gov (United States)

    Neuži, Pavel; Giselbrecht, Stefan; Länge, Kerstin; Huang, Tony Jun; Manz, Andreas

    2012-08-01

    The field of microfluidics or lab-on-a-chip technology aims to improve and extend the possibilities of bioassays, cell biology and biomedical research based on the idea of miniaturization. Microfluidic systems allow more accurate modelling of physiological situations for both fundamental research and drug development, and enable systematic high-volume testing for various aspects of drug discovery. Microfluidic systems are in development that not only model biological environments but also physically mimic biological tissues and organs; such 'organs on a chip' could have an important role in expediting early stages of drug discovery and help reduce reliance on animal testing. This Review highlights the latest lab-on-a-chip technologies for drug discovery and discusses the potential for future developments in this field.

  15. Scientific workflows as productivity tools for drug discovery.

    Science.gov (United States)

    Shon, John; Ohkawa, Hitomi; Hammer, Juergen

    2008-05-01

    Large pharmaceutical companies annually invest tens to hundreds of millions of US dollars in research informatics to support their early drug discovery processes. Traditionally, most of these investments are designed to increase the efficiency of drug discovery. The introduction of do-it-yourself scientific workflow platforms has enabled research informatics organizations to shift their efforts toward scientific innovation, ultimately resulting in a possible increase in return on their investments. Unlike the handling of most scientific data and application integration approaches, researchers apply scientific workflows to in silico experimentation and exploration, leading to scientific discoveries that lie beyond automation and integration. This review highlights some key requirements for scientific workflow environments in the pharmaceutical industry that are necessary for increasing research productivity. Examples of the application of scientific workflows in research and a summary of recent platform advances are also provided.

  16. Skin too thin? The developing utility of zebrafish skin (neuro)pharmacology for CNS drug discovery research.

    Science.gov (United States)

    Nguyen, Michael; Poudel, Manoj K; Stewart, Adam Michael; Kalueff, Allan V

    2013-09-01

    Skin coloration can be affected by many genetic, environmental and pharmacological factors. Zebrafish (Danio rerio) are a useful and versatile model organism in biomedical research due to their genetic tractability, physiological homology to mammals, low cost, reproducibility and high throughput. Zebrafish coloration is mediated by chromatophores - the skin color pigment cells largely controlled by endocrine and neural mechanisms. The characteristic darkening of zebrafish skin is caused by the dispersion (and paling - by aggregation) of melanosomes (pigment-containing organelles), which show high homology to mammalian structures. Various pharmacological agents potently affect zebrafish coloration - the phenotype that often accompanies behavioral effects of the drugs, and may be used for drug discovery. Although zebrafish behavior and skin responses are usually not directly related, they share common regulatory (neural, endocrine) mechanisms, and therefore may be assessed in parallel during psychotropic drug screening. For example, some psychoactive drugs can potently affect zebrafish skin coloration. Can we use this knowledge to refine phenotype-driven psychotropic drug discovery? Here, we present current models using zebrafish skin coloration assays, and discuss how these models may be applied to enhance in vivo CNS drug discovery. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

    Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic...

  18. Applied metabolomics in drug discovery.

    Science.gov (United States)

    Cuperlovic-Culf, M; Culf, A S

    2016-08-01

    The metabolic profile is a direct signature of phenotype and biochemical activity following any perturbation. Metabolites are small molecules present in a biological system including natural products as well as drugs and their metabolism by-products depending on the biological system studied. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs. This review focuses primarily on the application of metabolomics in the discovery of active drugs from natural products and the analysis of chemical libraries and the computational analysis of metabolic networks. Metabolomics methodology, both experimental and analytical is fast developing. At the same time, databases of compounds are ever growing with the inclusion of more molecular and spectral information. An increasing number of systems are being represented by very detailed metabolic network models. Combining these experimental and computational tools with high throughput drug testing and drug discovery techniques can provide new promising compounds and leads.

  19. Semiconductor technology in protein kinase research and drug discovery: sensing a revolution.

    Science.gov (United States)

    Bhalla, Nikhil; Di Lorenzo, Mirella; Estrela, Pedro; Pula, Giordano

    2017-02-01

    Since the discovery of protein kinase activity in 1954, close to 600 kinases have been discovered that have crucial roles in cell physiology. In several pathological conditions, aberrant protein kinase activity leads to abnormal cell and tissue physiology. Therefore, protein kinase inhibitors are investigated as potential treatments for several diseases, including dementia, diabetes, cancer and autoimmune and cardiovascular disease. Modern semiconductor technology has recently been applied to accelerate the discovery of novel protein kinase inhibitors that could become the standard-of-care drugs of tomorrow. Here, we describe current techniques and novel applications of semiconductor technologies in protein kinase inhibitor drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

    Directory of Open Access Journals (Sweden)

    Nicholas Ekow Thomford

    2018-05-01

    Full Text Available The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of “active compound” has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of ‘organ-on chip’ and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug

  1. Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery.

    Science.gov (United States)

    Thomford, Nicholas Ekow; Senthebane, Dimakatso Alice; Rowe, Arielle; Munro, Daniella; Seele, Palesa; Maroyi, Alfred; Dzobo, Kevin

    2018-05-25

    The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review

  2. Toxins and drug discovery.

    Science.gov (United States)

    Harvey, Alan L

    2014-12-15

    Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

  3. Bioinformatics in translational drug discovery.

    Science.gov (United States)

    Wooller, Sarah K; Benstead-Hume, Graeme; Chen, Xiangrong; Ali, Yusuf; Pearl, Frances M G

    2017-08-31

    Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications. © 2017 The Author(s).

  4. Synthetic biology for pharmaceutical drug discovery

    Directory of Open Access Journals (Sweden)

    Trosset JY

    2015-12-01

    Full Text Available Jean-Yves Trosset,1 Pablo Carbonell2,3 1Bioinformation Research Laboratory, Sup’Biotech, Villejuif, France; 2Faculty of Life Sciences, SYNBIOCHEM Centre, Manchester Institute of Biotechnology, University of Manchester, Manchester, UK; 3Department of Experimental and Health Sciences (DCEXS, Research Programme on Biomedical Informatics (GRIB, Hospital del Mar Medical Research Institute (IMIM, Universitat Pompeu Fabra (UPF, Barcelona, Spain Abstract: Synthetic biology (SB is an emerging discipline, which is slowly reorienting the field of drug discovery. For thousands of years, living organisms such as plants were the major source of human medicines. The difficulty in resynthesizing natural products, however, often turned pharmaceutical industries away from this rich source for human medicine. More recently, progress on transformation through genetic manipulation of biosynthetic units in microorganisms has opened the possibility of in-depth exploration of the large chemical space of natural products derivatives. Success of SB in drug synthesis culminated with the bioproduction of artemisinin by microorganisms, a tour de force in protein and metabolic engineering. Today, synthetic cells are not only used as biofactories but also used as cell-based screening platforms for both target-based and phenotypic-based approaches. Engineered genetic circuits in synthetic cells are also used to decipher disease mechanisms or drug mechanism of actions and to study cell–cell communication within bacteria consortia. This review presents latest developments of SB in the field of drug discovery, including some challenging issues such as drug resistance and drug toxicity. Keywords: metabolic engineering, plant synthetic biology, natural products, synthetic quorum sensing, drug resistance

  5. Integration of distributed computing into the drug discovery process.

    Science.gov (United States)

    von Korff, Modest; Rufener, Christian; Stritt, Manuel; Freyss, Joel; Bär, Roman; Sander, Thomas

    2011-02-01

    Grid computing offers an opportunity to gain massive computing power at low costs. We give a short introduction into the drug discovery process and exemplify the use of grid computing for image processing, docking and 3D pharmacophore descriptor calculations. The principle of a grid and its architecture are briefly explained. More emphasis is laid on the issues related to a company-wide grid installation and embedding the grid into the research process. The future of grid computing in drug discovery is discussed in the expert opinion section. Most needed, besides reliable algorithms to predict compound properties, is embedding the grid seamlessly into the discovery process. User friendly access to powerful algorithms without any restrictions, that is, by a limited number of licenses, has to be the goal of grid computing in drug discovery.

  6. Zebrafish models in neuropsychopharmacology and CNS drug discovery.

    Science.gov (United States)

    Khan, Kanza M; Collier, Adam D; Meshalkina, Darya A; Kysil, Elana V; Khatsko, Sergey L; Kolesnikova, Tatyana; Morzherin, Yury Yu; Warnick, Jason E; Kalueff, Allan V; Echevarria, David J

    2017-07-01

    Despite the high prevalence of neuropsychiatric disorders, their aetiology and molecular mechanisms remain poorly understood. The zebrafish (Danio rerio) is increasingly utilized as a powerful animal model in neuropharmacology research and in vivo drug screening. Collectively, this makes zebrafish a useful tool for drug discovery and the identification of disordered molecular pathways. Here, we discuss zebrafish models of selected human neuropsychiatric disorders and drug-induced phenotypes. As well as covering a broad range of brain disorders (from anxiety and psychoses to neurodegeneration), we also summarize recent developments in zebrafish genetics and small molecule screening, which markedly enhance the disease modelling and the discovery of novel drug targets. © 2017 The British Pharmacological Society.

  7. Novel opportunities for computational biology and sociology in drug discovery

    Science.gov (United States)

    Yao, Lixia

    2009-01-01

    Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801

  8. Conference Abstracts: Translational Science and Drug Discovery ...

    African Journals Online (AJOL)

    ... and Drug Discovery: Impact on Health, Wellness, Environment and Economics" conference, July 27-29th, 2015, at the Hennessy Park Hotel, Ebène Cybercity, Mauritius. The conference was hosted by the Society for Free radical Research Africa and the International Association of Medical and Biomedical Researchers.

  9. The discovery of drug-induced illness.

    Science.gov (United States)

    Jick, H

    1977-03-03

    The increased use of drugs (and the concurrent increased risks of drug-induced illness) require definition of relevant research areas and strategy. For established marketed drugs, research needs depend on the magnitudes of risk of an illness from a drug and the base-line risk. With the drug risk high and the base-line risk low, the problem surfaces in premarketing studies or through the epidemic that develops after marketing. If the drug adds slightly to a high base-line risk, the effect is undetectable. When both risks are low, adverse effects can be discovered by chance, but systematic case-referent studies can speed discovery. If both risks are high, clinical trials and nonexperimental studies may be used. With both risks intermediate, systematic evaluations, especially case-referent studies are needed. Newly marketed drugs should be routinely evaluated through compulsory registration and follow-up study of the earliest users.

  10. Drug discovery and developments in developing countries ...

    African Journals Online (AJOL)

    the major burden being in developing countries. Many of ... The driving force for drug discovery and development by pharmaceutical firms ... world and particularly in the third world countries ..... GFHR (2000) Global Forum for Health Research:.

  11. Recent advances in inkjet dispensing technologies: applications in drug discovery.

    Science.gov (United States)

    Zhu, Xiangcheng; Zheng, Qiang; Yang, Hu; Cai, Jin; Huang, Lei; Duan, Yanwen; Xu, Zhinan; Cen, Peilin

    2012-09-01

    Inkjet dispensing technology is a promising fabrication methodology widely applied in drug discovery. The automated programmable characteristics and high-throughput efficiency makes this approach potentially very useful in miniaturizing the design patterns for assays and drug screening. Various custom-made inkjet dispensing systems as well as specialized bio-ink and substrates have been developed and applied to fulfill the increasing demands of basic drug discovery studies. The incorporation of other modern technologies has further exploited the potential of inkjet dispensing technology in drug discovery and development. This paper reviews and discusses the recent developments and practical applications of inkjet dispensing technology in several areas of drug discovery and development including fundamental assays of cells and proteins, microarrays, biosensors, tissue engineering, basic biological and pharmaceutical studies. Progression in a number of areas of research including biomaterials, inkjet mechanical systems and modern analytical techniques as well as the exploration and accumulation of profound biological knowledge has enabled different inkjet dispensing technologies to be developed and adapted for high-throughput pattern fabrication and miniaturization. This in turn presents a great opportunity to propel inkjet dispensing technology into drug discovery.

  12. Toward Omics-Based, Systems Biomedicine, and Path and Drug Discovery Methodologies for Depression-Inflammation Research.

    Science.gov (United States)

    Maes, Michael; Nowak, Gabriel; Caso, Javier R; Leza, Juan Carlos; Song, Cai; Kubera, Marta; Klein, Hans; Galecki, Piotr; Noto, Cristiano; Glaab, Enrico; Balling, Rudi; Berk, Michael

    2016-07-01

    Meta-analyses confirm that depression is accompanied by signs of inflammation including increased levels of acute phase proteins, e.g., C-reactive protein, and pro-inflammatory cytokines, e.g., interleukin-6. Supporting the translational significance of this, a meta-analysis showed that anti-inflammatory drugs may have antidepressant effects. Here, we argue that inflammation and depression research needs to get onto a new track. Firstly, the choice of inflammatory biomarkers in depression research was often too selective and did not consider the broader pathways. Secondly, although mild inflammatory responses are present in depression, other immune-related pathways cannot be disregarded as new drug targets, e.g., activation of cell-mediated immunity, oxidative and nitrosative stress (O&NS) pathways, autoimmune responses, bacterial translocation, and activation of the toll-like receptor and neuroprogressive pathways. Thirdly, anti-inflammatory treatments are sometimes used without full understanding of their effects on the broader pathways underpinning depression. Since many of the activated immune-inflammatory pathways in depression actually confer protection against an overzealous inflammatory response, targeting these pathways may result in unpredictable and unwanted results. Furthermore, this paper discusses the required improvements in research strategy, i.e., path and drug discovery processes, omics-based techniques, and systems biomedicine methodologies. Firstly, novel methods should be employed to examine the intracellular networks that control and modulate the immune, O&NS and neuroprogressive pathways using omics-based assays, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, immunoproteomics and metagenomics. Secondly, systems biomedicine analyses are essential to unravel the complex interactions between these cellular networks, pathways, and the multifactorial trigger factors and to delineate new drug targets in the cellular

  13. Perspectives on bioanalytical mass spectrometry and automation in drug discovery.

    Science.gov (United States)

    Janiszewski, John S; Liston, Theodore E; Cole, Mark J

    2008-11-01

    The use of high speed synthesis technologies has resulted in a steady increase in the number of new chemical entities active in the drug discovery research stream. Large organizations can have thousands of chemical entities in various stages of testing and evaluation across numerous projects on a weekly basis. Qualitative and quantitative measurements made using LC/MS are integrated throughout this process from early stage lead generation through candidate nomination. Nearly all analytical processes and procedures in modern research organizations are automated to some degree. This includes both hardware and software automation. In this review we discuss bioanalytical mass spectrometry and automation as components of the analytical chemistry infrastructure in pharma. Analytical chemists are presented as members of distinct groups with similar skillsets that build automated systems, manage test compounds, assays and reagents, and deliver data to project teams. The ADME-screening process in drug discovery is used as a model to highlight the relationships between analytical tasks in drug discovery. Emerging software and process automation tools are described that can potentially address gaps and link analytical chemistry related tasks. The role of analytical chemists and groups in modern 'industrialized' drug discovery is also discussed.

  14. Solution NMR Spectroscopy in Target-Based Drug Discovery.

    Science.gov (United States)

    Li, Yan; Kang, Congbao

    2017-08-23

    Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

  15. Integration of Antibody Array Technology into Drug Discovery and Development.

    Science.gov (United States)

    Huang, Wei; Whittaker, Kelly; Zhang, Huihua; Wu, Jian; Zhu, Si-Wei; Huang, Ruo-Pan

    Antibody arrays represent a high-throughput technique that enables the parallel detection of multiple proteins with minimal sample volume requirements. In recent years, antibody arrays have been widely used to identify new biomarkers for disease diagnosis or prognosis. Moreover, many academic research laboratories and commercial biotechnology companies are starting to apply antibody arrays in the field of drug discovery. In this review, some technical aspects of antibody array development and the various platforms currently available will be addressed; however, the main focus will be on the discussion of antibody array technologies and their applications in drug discovery. Aspects of the drug discovery process, including target identification, mechanisms of drug resistance, molecular mechanisms of drug action, drug side effects, and the application in clinical trials and in managing patient care, which have been investigated using antibody arrays in recent literature will be examined and the relevance of this technology in progressing this process will be discussed. Protein profiling with antibody array technology, in addition to other applications, has emerged as a successful, novel approach for drug discovery because of the well-known importance of proteins in cell events and disease development.

  16. Targeting cysteine proteases in trypanosomatid disease drug discovery.

    Science.gov (United States)

    Ferreira, Leonardo G; Andricopulo, Adriano D

    2017-12-01

    Chagas disease and human African trypanosomiasis are endemic conditions in Latin America and Africa, respectively, for which no effective and safe therapy is available. Efforts in drug discovery have focused on several enzymes from these protozoans, among which cysteine proteases have been validated as molecular targets for pharmacological intervention. These enzymes are expressed during the entire life cycle of trypanosomatid parasites and are essential to many biological processes, including infectivity to the human host. As a result of advances in the knowledge of the structural aspects of cysteine proteases and their role in disease physiopathology, inhibition of these enzymes by small molecules has been demonstrated to be a worthwhile approach to trypanosomatid drug research. This review provides an update on drug discovery strategies targeting the cysteine peptidases cruzain from Trypanosoma cruzi and rhodesain and cathepsin B from Trypanosoma brucei. Given that current chemotherapy for Chagas disease and human African trypanosomiasis has several drawbacks, cysteine proteases will continue to be actively pursued as valuable molecular targets in trypanosomatid disease drug discovery efforts. Copyright © 2017. Published by Elsevier Inc.

  17. Medicinal chemistry inspired fragment-based drug discovery.

    Science.gov (United States)

    Lanter, James; Zhang, Xuqing; Sui, Zhihua

    2011-01-01

    Lead generation can be a very challenging phase of the drug discovery process. The two principal methods for this stage of research are blind screening and rational design. Among the rational or semirational design approaches, fragment-based drug discovery (FBDD) has emerged as a useful tool for the generation of lead structures. It is particularly powerful as a complement to high-throughput screening approaches when the latter failed to yield viable hits for further development. Engagement of medicinal chemists early in the process can accelerate the progression of FBDD efforts by incorporating drug-friendly properties in the earliest stages of the design process. Medium-chain acyl-CoA synthetase 2b and ketohexokinase are chosen as examples to illustrate the importance of close collaboration of medicinal chemists, crystallography, and modeling. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Comment on "drug discovery: turning the titanic".

    Science.gov (United States)

    Lesterhuis, W Joost; Bosco, Anthony; Lake, Richard A

    2014-03-26

    The pathobiology-based approach to research and development has been the dominant paradigm for successful drug discovery over the last decades. We propose that the molecular and cellular events that govern a resolving, rather than an evolving, disease may reveal new druggable pathways.

  19. Neuroproteases in peptide neurotransmission and neurodegenerative diseases: applications to drug discovery research.

    Science.gov (United States)

    Hook, Vivian Y H

    2006-01-01

    The nervous system represents a key area for development of novel therapeutic agents for the treatment of neurological and neurodegenerative diseases. Recent research has demonstrated the critical importance of neuroproteases for the production of specific peptide neurotransmitters and for the production of toxic peptides in major neurodegenerative diseases that include Alzheimer, Huntington, and Parkinson diseases. This review illustrates the successful criteria that have allowed identification of proteases responsible for converting protein precursors into active peptide neurotransmitters, consisting of dual cysteine protease and subtilisin-like protease pathways in neuroendocrine cells. These peptide neurotransmitters are critical regulators of neurologic conditions, including analgesia and cognition, and numerous behaviors. Importantly, protease pathways also represent prominent mechanisms in neurodegenerative diseases, especially Alzheimer, Huntington, and Parkinson diseases. Recent studies have identified secretory vesicle cathepsin B as a novel beta-secretase for production of the neurotoxic beta-amyloid (Abeta) peptide of Alzheimer disease. Moreover, inhibition of cathepsin B reduces Abeta peptide levels in brain. These neuroproteases potentially represent new drug targets that should be explored in future pharmaceutical research endeavors for drug discovery.

  20. The in silico drug discovery toolbox: applications in lead discovery and optimization.

    Science.gov (United States)

    Bruno, Agostino; Costantino, Gabriele; Sartori, Luca; Radi, Marco

    2017-11-06

    Discovery and development of a new drug is a long lasting and expensive journey that takes around 15 years from starting idea to approval and marketing of new medication. Despite the R&D expenditures have been constantly increasing in the last few years, number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. From this point of view, it is clear that if we want to increase drug-discovery success rate and reduce costs associated with development of a new drug, a comprehensive evaluation/prediction of potential safety issues should be conducted as soon as possible during early drug discovery phase. In the present review, we will analyse the early steps of drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  1. [Application of Imaging Mass Spectrometry for Drug Discovery].

    Science.gov (United States)

    Hayasaka, Takahiro

    2016-01-01

    Imaging mass spectrometry (IMS) can reveal the distribution of biomolecules on tissue sections. In this process, the biomolecules are directly ionized within tissue sections using matrix-assisted laser desorption/ionization, and then their distribution is visualized by pseudo-color based on the relative signal intensity. The biomolecules, such as fatty acids, phospholipids, glycolipids, peptides, proteins, and neurotransmitters, have been analyzed at a spatial resolution of 5 μm. A special instrument for IMS analysis was developed by Shimadzu. The IMS analysis does not require the labeling of biomolecules and is capable of analyzing all the ionized biomolecules. Interest in this method has expanded to many research fields, including biology, agriculture, medicine, and pharmacology. The technique is especially relevant to the drug discovery process. As practiced currently, drug discovery is expensive and time consuming, requiring the preparation of probes for each drug and its metabolites, followed by systematic probe tracking in animal models. The IMS technique is expected to overcome these drawbacks by revealing the distribution of drugs and their metabolites using only a single analysis. In this symposium, I introduced the methodology and applications of IMS and discussed the feasibility of its application to drug discovery in the near future.

  2. Introduction to fragment-based drug discovery.

    Science.gov (United States)

    Erlanson, Daniel A

    2012-01-01

    Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

  3. From crystal to compound: structure-based antimalarial drug discovery.

    Science.gov (United States)

    Drinkwater, Nyssa; McGowan, Sheena

    2014-08-01

    Despite a century of control and eradication campaigns, malaria remains one of the world's most devastating diseases. Our once-powerful therapeutic weapons are losing the war against the Plasmodium parasite, whose ability to rapidly develop and spread drug resistance hamper past and present malaria-control efforts. Finding new and effective treatments for malaria is now a top global health priority, fuelling an increase in funding and promoting open-source collaborations between researchers and pharmaceutical consortia around the world. The result of this is rapid advances in drug discovery approaches and technologies, with three major methods for antimalarial drug development emerging: (i) chemistry-based, (ii) target-based, and (iii) cell-based. Common to all three of these approaches is the unique ability of structural biology to inform and accelerate drug development. Where possible, SBDD (structure-based drug discovery) is a foundation for antimalarial drug development programmes, and has been invaluable to the development of a number of current pre-clinical and clinical candidates. However, as we expand our understanding of the malarial life cycle and mechanisms of resistance development, SBDD as a field must continue to evolve in order to develop compounds that adhere to the ideal characteristics for novel antimalarial therapeutics and to avoid high attrition rates pre- and post-clinic. In the present review, we aim to examine the contribution that SBDD has made to current antimalarial drug development efforts, covering hit discovery to lead optimization and prevention of parasite resistance. Finally, the potential for structural biology, particularly high-throughput structural genomics programmes, to identify future targets for drug discovery are discussed.

  4. Discovery and development of new antibacterial drugs: learning from experience?

    Science.gov (United States)

    Jackson, Nicole; Czaplewski, Lloyd; Piddock, Laura J V

    2018-06-01

    Antibiotic (antibacterial) resistance is a serious global problem and the need for new treatments is urgent. The current antibiotic discovery model is not delivering new agents at a rate that is sufficient to combat present levels of antibiotic resistance. This has led to fears of the arrival of a 'post-antibiotic era'. Scientific difficulties, an unfavourable regulatory climate, multiple company mergers and the low financial returns associated with antibiotic drug development have led to the withdrawal of many pharmaceutical companies from the field. The regulatory climate has now begun to improve, but major scientific hurdles still impede the discovery and development of novel antibacterial agents. To facilitate discovery activities there must be increased understanding of the scientific problems experienced by pharmaceutical companies. This must be coupled with addressing the current antibiotic resistance crisis so that compounds and ultimately drugs are delivered to treat the most urgent clinical challenges. By understanding the causes of the failures and successes of the pharmaceutical industry's research history, duplication of discovery programmes will be reduced, increasing the productivity of the antibiotic drug discovery pipeline by academia and small companies. The most important scientific issues to address are getting molecules into the Gram-negative bacterial cell and avoiding their efflux. Hence screening programmes should focus their efforts on whole bacterial cells rather than cell-free systems. Despite falling out of favour with pharmaceutical companies, natural product research still holds promise for providing new molecules as a basis for discovery.

  5. Organic synthesis provides opportunities to transform drug discovery

    Science.gov (United States)

    Blakemore, David C.; Castro, Luis; Churcher, Ian; Rees, David C.; Thomas, Andrew W.; Wilson, David M.; Wood, Anthony

    2018-03-01

    Despite decades of ground-breaking research in academia, organic synthesis is still a rate-limiting factor in drug-discovery projects. Here we present some current challenges in synthetic organic chemistry from the perspective of the pharmaceutical industry and highlight problematic steps that, if overcome, would find extensive application in the discovery of transformational medicines. Significant synthesis challenges arise from the fact that drug molecules typically contain amines and N-heterocycles, as well as unprotected polar groups. There is also a need for new reactions that enable non-traditional disconnections, more C-H bond activation and late-stage functionalization, as well as stereoselectively substituted aliphatic heterocyclic ring synthesis, C-X or C-C bond formation. We also emphasize that syntheses compatible with biomacromolecules will find increasing use, while new technologies such as machine-assisted approaches and artificial intelligence for synthesis planning have the potential to dramatically accelerate the drug-discovery process. We believe that increasing collaboration between academic and industrial chemists is crucial to address the challenges outlined here.

  6. Cloud computing approaches to accelerate drug discovery value chain.

    Science.gov (United States)

    Garg, Vibhav; Arora, Suchir; Gupta, Chitra

    2011-12-01

    Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

  7. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  8. An Ontology for Description of Drug Discovery Investigations

    Directory of Open Access Journals (Sweden)

    Qi Da

    2010-12-01

    Full Text Available The paper presents an ontology for the description of Drug Discovery Investigation (DDI. This has been developed through the use of a Robot Scientist “Eve”, and in consultation with industry. DDI aims to define the principle entities and the relations in the research and development phase of the drug discovery pipeline. DDI is highly transferable and extendable due to its adherence to accepted standards, and compliance with existing ontology resources. This enables DDI to be integrated with such related ontologies as the Vaccine Ontology, the Advancing Clinico-Genomic Trials on Cancer Master Ontology, etc. DDI is available at http://purl.org/ddi/wikipedia or http://purl.org/ddi/home

  9. Accessing external innovation in drug discovery and development.

    Science.gov (United States)

    Tufféry, Pierre

    2015-06-01

    A decline in the productivity of the pharmaceutical industry research and development (R&D) pipeline has highlighted the need to reconsider the classical strategies of drug discovery and development, which are based on internal resources, and to identify new means to improve the drug discovery process. Accepting that the combination of internal and external ideas can improve innovation, ways to access external innovation, that is, opening projects to external contributions, have recently been sought. In this review, the authors look at a number of external innovation opportunities. These include increased interactions with academia via academic centers of excellence/innovation centers, better communication on projects using crowdsourcing or social media and new models centered on external providers such as built-to-buy startups or virtual pharmaceutical companies. The buzz for accessing external innovation relies on the pharmaceutical industry's major challenge to improve R&D productivity, a conjuncture favorable to increase interactions with academia and new business models supporting access to external innovation. So far, access to external innovation has mostly been considered during early stages of drug development, and there is room for enhancement. First outcomes suggest that external innovation should become part of drug development in the long term. However, the balance between internal and external developments in drug discovery can vary largely depending on the company strategies.

  10. Applying genetics in inflammatory disease drug discovery

    DEFF Research Database (Denmark)

    Folkersen, Lasse; Biswas, Shameek; Frederiksen, Klaus Stensgaard

    2015-01-01

    , with several notable exceptions, the journey from a small-effect genetic variant to a functional drug has proven arduous, and few examples of actual contributions to drug discovery exist. Here, we discuss novel approaches of overcoming this hurdle by using instead public genetics resources as a pragmatic guide...... alongside existing drug discovery methods. Our aim is to evaluate human genetic confidence as a rationale for drug target selection....

  11. RAS - Screens & Assays - Drug Discovery

    Science.gov (United States)

    The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.

  12. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  13. Fragment-based drug discovery and molecular docking in drug design.

    Science.gov (United States)

    Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong

    2015-01-01

    Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.

  14. Common characteristics of open source software development and applicability for drug discovery: a systematic review.

    Science.gov (United States)

    Ardal, Christine; Alstadsæter, Annette; Røttingen, John-Arne

    2011-09-28

    Innovation through an open source model has proven to be successful for software development. This success has led many to speculate if open source can be applied to other industries with similar success. We attempt to provide an understanding of open source software development characteristics for researchers, business leaders and government officials who may be interested in utilizing open source innovation in other contexts and with an emphasis on drug discovery. A systematic review was performed by searching relevant, multidisciplinary databases to extract empirical research regarding the common characteristics and barriers of initiating and maintaining an open source software development project. Common characteristics to open source software development pertinent to open source drug discovery were extracted. The characteristics were then grouped into the areas of participant attraction, management of volunteers, control mechanisms, legal framework and physical constraints. Lastly, their applicability to drug discovery was examined. We believe that the open source model is viable for drug discovery, although it is unlikely that it will exactly follow the form used in software development. Hybrids will likely develop that suit the unique characteristics of drug discovery. We suggest potential motivations for organizations to join an open source drug discovery project. We also examine specific differences between software and medicines, specifically how the need for laboratories and physical goods will impact the model as well as the effect of patents.

  15. ASM Inaugural Lecture 2010: Single crystal X-ray structural determination: A powerful technique for natural products research and drug discovery

    International Nuclear Information System (INIS)

    Fun Hoong Kun; Chantrapromma, S.; Boonnak, N.; Lee, V.S.

    2010-01-01

    Drug discovery from natural products resources have been extensively studied worldwide because natural products with their great structural diversity have traditionally provided most of the drugs in use. They offer major opportunities for finding novel low molecular weight leading-structures that are active against a wide range of assay targets. The most important step in the discovery process is the identification of compounds with interesting biological activity. Single crystal X-ray structure determination is a powerful technique for natural products research and drug discovery. The detailed three-dimensional structures that emerge can be co-related to the activities to these structures. In this article the following is presented: (i) co-crystal and disorder structures; (ii) determination of absolute configuration and (iii) the ability to distinguish between whether a natural product compound is a natural product or a natural product artifact. All these three properties are unique to the technique of single crystal X-ray structure determination. Case (iii) was demonstrated with a compound containing a chromene ring, namely macluraxanthone (which was isolated from Cratoxylum formosum subsp. pruniflorum, a Thai medicinal plant). (author)

  16. Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

    Science.gov (United States)

    San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

    2014-12-01

    Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

  17. [Frontiers in Live Bone Imaging Researches. Novel drug discovery by means of intravital bone imaging technology].

    Science.gov (United States)

    Ishii, Masaru

    2015-06-01

    Recent advances in intravital bone imaging technology has enabled us to grasp the real cellular behaviors and functions in vivo , revolutionizing the field of drug discovery for novel therapeutics against intractable bone diseases. In this chapter, I introduce various updated information on pharmacological actions of several antibone resorptive agents, which could only be derived from advanced imaging techniques, and also discuss the future perspectives of this new trend in drug discovery.

  18. Mathematical modeling for novel cancer drug discovery and development.

    Science.gov (United States)

    Zhang, Ping; Brusic, Vladimir

    2014-10-01

    Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.

  19. Systems Pharmacology in Small Molecular Drug Discovery

    Directory of Open Access Journals (Sweden)

    Wei Zhou

    2016-02-01

    Full Text Available Drug discovery is a risky, costly and time-consuming process depending on multidisciplinary methods to create safe and effective medicines. Although considerable progress has been made by high-throughput screening methods in drug design, the cost of developing contemporary approved drugs did not match that in the past decade. The major reason is the late-stage clinical failures in Phases II and III because of the complicated interactions between drug-specific, human body and environmental aspects affecting the safety and efficacy of a drug. There is a growing hope that systems-level consideration may provide a new perspective to overcome such current difficulties of drug discovery and development. The systems pharmacology method emerged as a holistic approach and has attracted more and more attention recently. The applications of systems pharmacology not only provide the pharmacodynamic evaluation and target identification of drug molecules, but also give a systems-level of understanding the interaction mechanism between drugs and complex disease. Therefore, the present review is an attempt to introduce how holistic systems pharmacology that integrated in silico ADME/T (i.e., absorption, distribution, metabolism, excretion and toxicity, target fishing and network pharmacology facilitates the discovery of small molecular drugs at the system level.

  20. Perspectives of biomolecular NMR in drug discovery: the blessing and curse of versatility

    International Nuclear Information System (INIS)

    Jahnke, Wolfgang

    2007-01-01

    The versatility of NMR and its broad applicability to several stages in the drug discovery process is well known and generally considered one of the major strengths of NMR (Pellecchia et al., Nature Rev Drug Discov 1:211-219, 2002; Stockman and Dalvit, Prog Nucl Magn Reson Spectrosc 41:187-231, 2002; Lepre et al., Comb Chem High throughput screen 5:583-590, 2002; Wyss et al., Curr Opin Drug Discov Devel 5:630-647, 2002; Jahnke and Widmer, Cell Mol Life Sci 61:580-599, 2004; Huth et al., Methods Enzymol 394:549-571, 2005b; Klages et al., Mol Biosyst 2:318-332, 2006; Takeuchi and Wagner, Curr Opin Struct Biol 16:109-117, 2006; Zartler and Shapiro, Curr Pharm Des 12:3963-3972, 2006). Indeed, NMR is the only biophysical technique which can detect and quantify molecular interactions, and at the same time provide detailed structural information with atomic level resolution. NMR should therefore be ideally suited and widely requested as a tool for drug discovery research, and numerous examples of drug discovery projects which have substantially benefited from NMR contributions or were even driven by NMR have been described in the literature. However, not all pharmaceutical companies have rigorously implemented NMR as integral tool of their research processes. Some companies invest with limited resources, and others do not use biomolecular NMR at all. This discrepancy in assessing the value of a technology is striking, and calls for clarification-under which circumstances can NMR provide added value to the drug discovery process? What kind of contributions can NMR make, and how is it implemented and integrated for maximum impact? This perspectives article suggests key areas of impact for NMR, and a model of integrating NMR with other technologies to realize synergies and maximize their value for drug discovery

  1. International Drug Discovery Science and Technology--BIT's Seventh Annual Congress.

    Science.gov (United States)

    Bodovitz, Steven

    2010-01-01

    BIT's Seventh Annual International Drug Discovery Science and Technology Congress, held in Shanghai, included topics covering new therapeutic and technological developments in the field of drug discovery. This conference report highlights selected presentations on open-access approaches to R&D, novel and multifactorial targets, and technologies that assist drug discovery. Investigational drugs discussed include the anticancer agents astuprotimut-r (GlaxoSmithKline plc) and AS-1411 (Antisoma plc).

  2. Four disruptive strategies for removing drug discovery bottlenecks.

    Science.gov (United States)

    Ekins, Sean; Waller, Chris L; Bradley, Mary P; Clark, Alex M; Williams, Antony J

    2013-03-01

    Drug discovery is shifting focus from industry to outside partners and, in the process, creating new bottlenecks. Technologies like high throughput screening (HTS) have moved to a larger number of academic and institutional laboratories in the USA, with little coordination or consideration of the outputs and creating a translational gap. Although there have been collaborative public-private partnerships in Europe to share pharmaceutical data, the USA has seemingly lagged behind and this may hold it back. Sharing precompetitive data and models may accelerate discovery across the board, while finding the best collaborators, mining social media and mobile approaches to open drug discovery should be evaluated in our efforts to remove drug discovery bottlenecks. We describe four strategies to rectify the current unsustainable situation. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Multi-target drugs: the trend of drug research and development.

    Science.gov (United States)

    Lu, Jin-Jian; Pan, Wei; Hu, Yuan-Jia; Wang, Yi-Tao

    2012-01-01

    Summarizing the status of drugs in the market and examining the trend of drug research and development is important in drug discovery. In this study, we compared the drug targets and the market sales of the new molecular entities approved by the U.S. Food and Drug Administration from January 2000 to December 2009. Two networks, namely, the target-target and drug-drug networks, have been set up using the network analysis tools. The multi-target drugs have much more potential, as shown by the network visualization and the market trends. We discussed the possible reasons and proposed the rational strategies for drug research and development in the future.

  4. "Drug" Discovery with the Help of Organic Chemistry.

    Science.gov (United States)

    Itoh, Yukihiro; Suzuki, Takayoshi

    2017-01-01

    The first step in "drug" discovery is to find compounds binding to a potential drug target. In modern medicinal chemistry, the screening of a chemical library, structure-based drug design, and ligand-based drug design, or a combination of these methods, are generally used for identifying the desired compounds. However, they do not necessarily lead to success and there is no infallible method for drug discovery. Therefore, it is important to explore medicinal chemistry based on not only the conventional methods but also new ideas. So far, we have found various compounds as drug candidates. In these studies, some strategies based on organic chemistry have allowed us to find drug candidates, through 1) construction of a focused library using organic reactions and 2) rational design of enzyme inhibitors based on chemical reactions catalyzed by the target enzyme. Medicinal chemistry based on organic chemical reactions could be expected to supplement the conventional methods. In this review, we present drug discovery with the help of organic chemistry showing examples of our explorative studies on histone deacetylase inhibitors and lysine-specific demethylase 1 inhibitors.

  5. Current approaches for the discovery of drugs that deter substance and drug abuse.

    Science.gov (United States)

    Yasgar, Adam; Simeonov, Anton

    2014-11-01

    Much has been presented and debated on the topic of drug abuse and its multidimensional nature, including the role of society and its customs and laws, economical factors, and the magnitude and nature of the burden. Given the complex nature of the receptors and pathways implicated in regulation of the cognitive and behavioral processes associated with addiction, a large number of molecular targets have been interrogated during recent years to discover starting points for development of small-molecule interventions. This review describes recent developments in the field of early drug discovery for drug abuse interventions with an emphasis on the advances published during the 2012 - 2014 period. Technologically, the processes/platforms utilized in drug abuse drug discovery are nearly identical to those used in the other disease areas. A key complicating factor in drug abuse research is the enormous biological complexity surrounding the brain processes involved and the associated difficulty in finding 'good' targets and achieving exquisite selectivity of treatment agents. While tremendous progress has been made during recent years to use the power of high-throughput technologies to discover proof-of-principle molecules for many new targets, next-generation models will be especially important in this field. Examples include: seeking advantageous drug-drug combinations, the use of automated whole-animal behavioral screening systems, advancing our understanding of the role of epigenetics in drug addiction and the employment of organoid-level 3D test platforms (also referred to as tissue-chip or organs-on-chip).

  6. Computer-aided drug discovery [v1; ref status: indexed, http://f1000r.es/5ij

    Directory of Open Access Journals (Sweden)

    Jürgen Bajorath

    2015-08-01

    Full Text Available Computational approaches are an integral part of interdisciplinary drug discovery research. Understanding the science behind computational tools, their opportunities, and limitations is essential to make a true impact on drug discovery at different levels. If applied in a scientifically meaningful way, computational methods improve the ability to identify and evaluate potential drug molecules, but there remain weaknesses in the methods that preclude naïve applications. Herein, current trends in computer-aided drug discovery are reviewed, and selected computational areas are discussed. Approaches are highlighted that aid in the identification and optimization of new drug candidates. Emphasis is put on the presentation and discussion of computational concepts and methods, rather than case studies or application examples. As such, this contribution aims to provide an overview of the current methodological spectrum of computational drug discovery for a broad audience.

  7. Mass spectrometry-driven drug discovery for development of herbal medicine.

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Wang, Xijun

    2018-05-01

    Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes. © 2016 Wiley Periodicals, Inc.

  8. Science of the science, drug discovery and artificial neural networks.

    Science.gov (United States)

    Patel, Jigneshkumar

    2013-03-01

    Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

  9. Drug design and discovery: translational biomedical science varies among countries.

    Science.gov (United States)

    Weaver, Ian N; Weaver, Donald F

    2013-10-01

    Drug design and discovery is an innovation process that translates the outcomes of fundamental biomedical research into therapeutics that are ultimately made available to people with medical disorders in many countries throughout the world. To identify which nations succeed, exceed, or fail at the drug design/discovery endeavor--more specifically, which countries, within the context of their national size and wealth, are "pulling their weight" when it comes to developing medications targeting the myriad of diseases that afflict humankind--we compiled and analyzed a comprehensive survey of all new drugs (small molecular entities and biologics) approved annually throughout the world over the 20-year period from 1991 to 2010. Based upon this analysis, we have devised prediction algorithms to ascertain which countries are successful (or not) in contributing to the worldwide need for effective new therapeutics. © 2013 Wiley Periodicals, Inc.

  10. Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?

    Science.gov (United States)

    Dobchev, Dimitar; Karelson, Mati

    2016-07-01

    Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably, in the past two decades, ANNs have been used widely in the process of drug discovery. In this review, the authors discuss advantages and disadvantages of ANNs in drug discovery as incorporated into the quantitative structure-activity relationships (QSAR) framework. Furthermore, the authors examine the recent studies, which span over a broad area with various diseases in drug discovery. In addition, the authors attempt to answer the question about the expectations of the ANNs in drug discovery and discuss the trends in this field. The old pitfalls of overtraining and interpretability are still present with ANNs. However, despite these pitfalls, the authors believe that ANNs have likely met many of the expectations of researchers and are still considered as excellent tools for nonlinear data modeling in QSAR. It is likely that ANNs will continue to be used in drug development in the future.

  11. Alkaloids as Cyclooxygenase Inhibitors in Anticancer Drug Discovery.

    Science.gov (United States)

    Hashmi, Muhammad Ali; Khan, Afsar; Farooq, Umar; Khan, Sehroon

    2018-01-01

    Cancer is the leading cause of death worldwide and anticancer drug discovery is a very hot area of research at present. There are various factors which control and affect cancer, out of which enzymes like cyclooxygenase-2 (COX-2) play a vital role in the growth of tumor cells. Inhibition of this enzyme is a very useful target for the prevention of various types of cancers. Alkaloids are a diverse group of naturally occurring compounds which have shown great COX-2 inhibitory activity both in vitro and in vivo. In this mini-review, we have discussed different alkaloids with COX-2 inhibitory activities and anticancer potential which may act as leads in modern anticancer drug discovery. Different classes of alkaloids including isoquinoline alkaloids, indole alkaloids, piperidine alkaloids, quinazoline alkaloids, and various miscellaneous alkaloids obtained from natural sources have been discussed in detail in this review. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Open Access Could Transform Drug Discovery: A Case Study of JQ1.

    Science.gov (United States)

    Arshad, Zeeshaan; Smith, James; Roberts, Mackenna; Lee, Wen Hwa; Davies, Ben; Bure, Kim; Hollander, Georg A; Dopson, Sue; Bountra, Chas; Brindley, David

    2016-01-01

    The cost to develop a new drug from target discovery to market is a staggering $1.8 billion, largely due to the very high attrition rate of drug candidates and the lengthy transition times during development. Open access is an emerging model of open innovation that places no restriction on the use of information and has the potential to accelerate the development of new drugs. To date, no quantitative assessment has yet taken place to determine the effects and viability of open access on the process of drug translation. This need is addressed within this study. The literature and intellectual property landscapes of the drug candidate JQ1, which was made available on an open access basis when discovered, and conventionally developed equivalents that were not are compared using the Web of Science and Thomson Innovation software, respectively. Results demonstrate that openly sharing the JQ1 molecule led to a greater uptake by a wider and more multi-disciplinary research community. A comparative analysis of the patent landscapes for each candidate also found that the broader scientific diaspora of the publically released JQ1 data enhanced innovation, evidenced by a greater number of downstream patents filed in relation to JQ1. The authors' findings counter the notion that open access drug discovery would leak commercial intellectual property. On the contrary, JQ1 serves as a test case to evidence that open access drug discovery can be an economic model that potentially improves efficiency and cost of drug discovery and its subsequent commercialization.

  13. A role for physicians in ethnopharmacology and drug discovery.

    Science.gov (United States)

    Raza, Mohsin

    2006-04-06

    Ethnopharmacology investigations classically involved traditional healers, botanists, anthropologists, chemists and pharmacologists. The role of some groups of researchers but not of physician has been highlighted and well defined in ethnopharmacological investigations. Historical data shows that discovery of several important modern drugs of herbal origin owe to the medical knowledge and clinical expertise of physicians. Current trends indicate negligible role of physicians in ethnopharmacological studies. Rising cost of modern drug development is attributed to the lack of classical ethnopharmacological approach. Physicians can play multiple roles in the ethnopharmacological studies to facilitate drug discovery as well as to rescue authentic traditional knowledge of use of medicinal plants. These include: (1) Ethnopharmacological field work which involves interviewing healers, interpreting traditional terminologies into their modern counterparts, examining patients consuming herbal remedies and identifying the disease for which an herbal remedy is used. (2) Interpretation of signs and symptoms mentioned in ancient texts and suggesting proper use of old traditional remedies in the light of modern medicine. (3) Clinical studies on herbs and their interaction with modern medicines. (4) Advising pharmacologists to carryout laboratory studies on herbs observed during field studies. (5) Work in collaboration with local healers to strengthen traditional system of medicine in a community. In conclusion, physician's involvement in ethnopharmacological studies will lead to more reliable information on traditional use of medicinal plants both from field and ancient texts, more focused and cheaper natural product based drug discovery, as well as bridge the gap between traditional and modern medicine.

  14. Twenty years on: the impact of fragments on drug discovery.

    Science.gov (United States)

    Erlanson, Daniel A; Fesik, Stephen W; Hubbard, Roderick E; Jahnke, Wolfgang; Jhoti, Harren

    2016-09-01

    After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.

  15. Fragment-based drug discovery and its application to challenging drug targets.

    Science.gov (United States)

    Price, Amanda J; Howard, Steven; Cons, Benjamin D

    2017-11-08

    Fragment-based drug discovery (FBDD) is a technique for identifying low molecular weight chemical starting points for drug discovery. Since its inception 20 years ago, FBDD has grown in popularity to the point where it is now an established technique in industry and academia. The approach involves the biophysical screening of proteins against collections of low molecular weight compounds (fragments). Although fragments bind to proteins with relatively low affinity, they form efficient, high quality binding interactions with the protein architecture as they have to overcome a significant entropy barrier to bind. Of the biophysical methods available for fragment screening, X-ray protein crystallography is one of the most sensitive and least prone to false positives. It also provides detailed structural information of the protein-fragment complex at the atomic level. Fragment-based screening using X-ray crystallography is therefore an efficient method for identifying binding hotspots on proteins, which can then be exploited by chemists and biologists for the discovery of new drugs. The use of FBDD is illustrated here with a recently published case study of a drug discovery programme targeting the challenging protein-protein interaction Kelch-like ECH-associated protein 1:nuclear factor erythroid 2-related factor 2. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  16. Advancing Drug Discovery through Enhanced Free Energy Calculations.

    Science.gov (United States)

    Abel, Robert; Wang, Lingle; Harder, Edward D; Berne, B J; Friesner, Richard A

    2017-07-18

    A principal goal of drug discovery project is to design molecules that can tightly and selectively bind to the target protein receptor. Accurate prediction of protein-ligand binding free energies is therefore of central importance in computational chemistry and computer aided drug design. Multiple recent improvements in computing power, classical force field accuracy, enhanced sampling methods, and simulation setup have enabled accurate and reliable calculations of protein-ligands binding free energies, and position free energy calculations to play a guiding role in small molecule drug discovery. In this Account, we outline the relevant methodological advances, including the REST2 (Replica Exchange with Solute Temperting) enhanced sampling, the incorporation of REST2 sampling with convential FEP (Free Energy Perturbation) through FEP/REST, the OPLS3 force field, and the advanced simulation setup that constitute our FEP+ approach, followed by the presentation of extensive comparisons with experiment, demonstrating sufficient accuracy in potency prediction (better than 1 kcal/mol) to substantially impact lead optimization campaigns. The limitations of the current FEP+ implementation and best practices in drug discovery applications are also discussed followed by the future methodology development plans to address those limitations. We then report results from a recent drug discovery project, in which several thousand FEP+ calculations were successfully deployed to simultaneously optimize potency, selectivity, and solubility, illustrating the power of the approach to solve challenging drug design problems. The capabilities of free energy calculations to accurately predict potency and selectivity have led to the advance of ongoing drug discovery projects, in challenging situations where alternative approaches would have great difficulties. The ability to effectively carry out projects evaluating tens of thousands, or hundreds of thousands, of proposed drug candidates

  17. Protein Complex Production from the Drug Discovery Standpoint.

    Science.gov (United States)

    Moarefi, Ismail

    2016-01-01

    Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.

  18. Cell and small animal models for phenotypic drug discovery

    Directory of Open Access Journals (Sweden)

    Szabo M

    2017-06-01

    Full Text Available Mihaly Szabo,1 Sara Svensson Akusjärvi,1 Ankur Saxena,1 Jianping Liu,2 Gayathri Chandrasekar,1 Satish S Kitambi1 1Department of Microbiology Tumor, and Cell Biology, 2Department of Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden Abstract: The phenotype-based drug discovery (PDD approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery. Keywords: phenotype, screening, PDD, discovery, zebrafish, drug

  19. Advances in fragment-based drug discovery platforms.

    Science.gov (United States)

    Orita, Masaya; Warizaya, Masaichi; Amano, Yasushi; Ohno, Kazuki; Niimi, Tatsuya

    2009-11-01

    Fragment-based drug discovery (FBDD) has been established as a powerful alternative and complement to traditional high-throughput screening techniques for identifying drug leads. At present, this technique is widely used among academic groups as well as small biotech and large pharmaceutical companies. In recent years, > 10 new compounds developed with FBDD have entered clinical development, and more and more attention in the drug discovery field is being focused on this technique. Under the FBDD approach, a fragment library of relatively small compounds (molecular mass = 100 - 300 Da) is screened by various methods and the identified fragment hits which normally weakly bind to the target are used as starting points to generate more potent drug leads. Because FBDD is still a relatively new drug discovery technology, further developments and optimizations in screening platforms and fragment exploitation can be expected. This review summarizes recent advances in FBDD platforms and discusses the factors important for the successful application of this technique. Under the FBDD approach, both identifying the starting fragment hit to be developed and generating the drug lead from that starting fragment hit are important. Integration of various techniques, such as computational technology, X-ray crystallography, NMR, surface plasmon resonance, isothermal titration calorimetry, mass spectrometry and high-concentration screening, must be applied in a situation-appropriate manner.

  20. Japan-China Joint Medical Workshop on Drug Discoveries and Therapeutics 2008: The need of Asian pharmaceutical researchers' cooperation.

    Science.gov (United States)

    Nakata, M; Tang, W

    2008-10-01

    The Japan-China Joint Medical Workshop on Drug Discoveries and Therapeutics 2008 (JCMWDDT 2008) was held from September 29 to October 1, 2008 at The University of Tokyo, Tokyo, Japan. JCMWDDT is an international workshop that is mainly organized by Asian editorial members of Drug Discoveries & Therapeutics (http://www.ddtjournal.com/home) for the purpose of promoting research exchanges in the field of drug discovery and therapeutic. This year's JCMWDDT is the second workshop and focused particularly on novel development and technological innovation of anti-influenza agents. The workshop began with an announcement by the Japanese Co-chairperson, Dr. Sekimizu (Department of Microbiology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Japan; Editorin- Chief of Drug Discoveries & Therapeutics, DDT) followed by a speech by the Chinese Co-chairperson, Dr. Wenfang Xu (School of Pharmaceutical Sciences, Shandong University, Shandong, China; Editor in China Office of DDT), with additional speeches by Dr. Norio Matsuki (The University of Tokyo, Japan; Editor of DDT) and Dr. Guanhua Du (Chinese Academy of Medical Science, China; Editor of DDT). Fifty-nine titles were presented in 6 specialized sessions (Research Advances in Drug Discoveries and Therapeutics, Drug Synthesis/Clinical Therapeutics, Medicinal Chemistry/Natural Products, Anti-influenza Drugs, Anti-infection/antiviral Drugs, Biochemistry/Molecular Biology /Pharmacology) and a poster session (Drug Discov Ther 2008; 2, Suppl; available at http://www.ddtjournal.com/Announce/index.htm). An annual outbreak of avian influenza in Asian countries including China and Japan has sparked fears that the virus will mutate and then cause an epidemic in humans. Therefore, Asian researchers need to work together to control this infection. This year's JCMWDDT helped provide an opportunity to reiterate the crucial role of medicinal chemistry in conquering influenza and created an environment for cooperative

  1. Pathways to new drug discovery in neuropsychiatry

    Directory of Open Access Journals (Sweden)

    Berk Michael

    2012-11-01

    Full Text Available Abstract There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success. See related article http://www.biomedcentral.com/1741-7015/10/150

  2. ACFIS: a web server for fragment-based drug discovery.

    Science.gov (United States)

    Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

    2016-07-08

    In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown 'chemical space' to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for 'chemical space', which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Use of combinatorial chemistry to speed drug discovery.

    Science.gov (United States)

    Rádl, S

    1998-10-01

    IBC's International Conference on Integrating Combinatorial Chemistry into the Discovery Pipeline was held September 14-15, 1998. The program started with a pre-conference workshop on High-Throughput Compound Characterization and Purification. The agenda of the main conference was divided into sessions of Synthesis, Automation and Unique Chemistries; Integrating Combinatorial Chemistry, Medicinal Chemistry and Screening; Combinatorial Chemistry Applications for Drug Discovery; and Information and Data Management. This meeting was an excellent opportunity to see how big pharma, biotech and service companies are addressing the current bottlenecks in combinatorial chemistry to speed drug discovery. (c) 1998 Prous Science. All rights reserved.

  4. Natural Products as Leads in Schistosome Drug Discovery

    Directory of Open Access Journals (Sweden)

    Bruno J. Neves

    2015-01-01

    Full Text Available Schistosomiasis is a neglected parasitic tropical disease that claims around 200,000 human lives every year. Praziquantel (PZQ, the only drug recommended by the World Health Organization for the treatment and control of human schistosomiasis, is now facing the threat of drug resistance, indicating the urgent need for new effective compounds to treat this disease. Therefore, globally, there is renewed interest in natural products (NPs as a starting point for drug discovery and development for schistosomiasis. Recent advances in genomics, proteomics, bioinformatics, and cheminformatics have brought about unprecedented opportunities for the rapid and more cost-effective discovery of new bioactive compounds against neglected tropical diseases. This review highlights the main contributions that NP drug discovery and development have made in the treatment of schistosomiasis and it discusses how integration with virtual screening (VS strategies may contribute to accelerating the development of new schistosomidal leads, especially through the identification of unexplored, biologically active chemical scaffolds and structural optimization of NPs with previously established activity.

  5. Open Access Target Validation Is a More Efficient Way to Accelerate Drug Discovery

    Science.gov (United States)

    Lee, Wen Hwa

    2015-01-01

    There is a scarcity of novel treatments to address many unmet medical needs. Industry and academia are finally coming to terms with the fact that the prevalent models and incentives for innovation in early stage drug discovery are failing to promote progress quickly enough. Here we will examine how an open model of precompetitive public–private research partnership is enabling efficient derisking and acceleration in the early stages of drug discovery, whilst also widening the range of communities participating in the process, such as patient and disease foundations. PMID:26042736

  6. ChEMBL web services: streamlining access to drug discovery data and utilities.

    Science.gov (United States)

    Davies, Mark; Nowotka, Michał; Papadatos, George; Dedman, Nathan; Gaulton, Anna; Atkinson, Francis; Bellis, Louisa; Overington, John P

    2015-07-01

    ChEMBL is now a well-established resource in the fields of drug discovery and medicinal chemistry research. The ChEMBL database curates and stores standardized bioactivity, molecule, target and drug data extracted from multiple sources, including the primary medicinal chemistry literature. Programmatic access to ChEMBL data has been improved by a recent update to the ChEMBL web services (version 2.0.x, https://www.ebi.ac.uk/chembl/api/data/docs), which exposes significantly more data from the underlying database and introduces new functionality. To complement the data-focused services, a utility service (version 1.0.x, https://www.ebi.ac.uk/chembl/api/utils/docs), which provides RESTful access to commonly used cheminformatics methods, has also been concurrently developed. The ChEMBL web services can be used together or independently to build applications and data processing workflows relevant to drug discovery and chemical biology. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Drug-Target Kinetics in Drug Discovery.

    Science.gov (United States)

    Tonge, Peter J

    2018-01-17

    The development of therapies for the treatment of neurological cancer faces a number of major challenges including the synthesis of small molecule agents that can penetrate the blood-brain barrier (BBB). Given the likelihood that in many cases drug exposure will be lower in the CNS than in systemic circulation, it follows that strategies should be employed that can sustain target engagement at low drug concentration. Time dependent target occupancy is a function of both the drug and target concentration as well as the thermodynamic and kinetic parameters that describe the binding reaction coordinate, and sustained target occupancy can be achieved through structural modifications that increase target (re)binding and/or that decrease the rate of drug dissociation. The discovery and deployment of compounds with optimized kinetic effects requires information on the structure-kinetic relationships that modulate the kinetics of binding, and the molecular factors that control the translation of drug-target kinetics to time-dependent drug activity in the disease state. This Review first introduces the potential benefits of drug-target kinetics, such as the ability to delineate both thermodynamic and kinetic selectivity, and then describes factors, such as target vulnerability, that impact the utility of kinetic selectivity. The Review concludes with a description of a mechanistic PK/PD model that integrates drug-target kinetics into predictions of drug activity.

  8. Microfluidic cell culture systems for drug research.

    Science.gov (United States)

    Wu, Min-Hsien; Huang, Song-Bin; Lee, Gwo-Bin

    2010-04-21

    In pharmaceutical research, an adequate cell-based assay scheme to efficiently screen and to validate potential drug candidates in the initial stage of drug discovery is crucial. In order to better predict the clinical response to drug compounds, a cell culture model that is faithful to in vivo behavior is required. With the recent advances in microfluidic technology, the utilization of a microfluidic-based cell culture has several advantages, making it a promising alternative to the conventional cell culture methods. This review starts with a comprehensive discussion on the general process for drug discovery and development, the role of cell culture in drug research, and the characteristics of the cell culture formats commonly used in current microfluidic-based, cell-culture practices. Due to the significant differences in several physical phenomena between microscale and macroscale devices, microfluidic technology provides unique functionality, which is not previously possible by using traditional techniques. In a subsequent section, the niches for using microfluidic-based cell culture systems for drug research are discussed. Moreover, some critical issues such as cell immobilization, medium pumping or gradient generation in microfluidic-based, cell-culture systems are also reviewed. Finally, some practical applications of microfluidic-based, cell-culture systems in drug research particularly those pertaining to drug toxicity testing and those with a high-throughput capability are highlighted.

  9. SemaTyP: a knowledge graph based literature mining method for drug discovery.

    Science.gov (United States)

    Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

    2018-05-30

    Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

  10. Financing drug discovery for orphan diseases

    OpenAIRE

    Fagnan, David Erik; Gromatzky, Austin A.; Stein, Roger Mark; Fernandez, Jose-Maria; Lo, Andrew W.

    2014-01-01

    Recently proposed ‘megafund’ financing methods for funding translational medicine and drug development require billions of dollars in capital per megafund to de-risk the drug discovery process enough to issue long-term bonds. Here, we demonstrate that the same financing methods can be applied to orphan drug development but, because of the unique nature of orphan diseases and therapeutics (lower development costs, faster FDA approval times, lower failure rates and lower correlation of failures...

  11. AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

    International Nuclear Information System (INIS)

    Tsai, Yingssu; McPhillips, Scott E.; González, Ana; McPhillips, Timothy M.; Zinn, Daniel; Cohen, Aina E.; Feese, Michael D.; Bushnell, David; Tiefenbrunn, Theresa; Stout, C. David; Ludaescher, Bertram; Hedman, Britt; Hodgson, Keith O.; Soltis, S. Michael

    2013-01-01

    New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully

  12. Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases.

    Science.gov (United States)

    Mello, Juliana da Fonseca Rezende E; Gomes, Renan Augusto; Vital-Fujii, Drielli Gomes; Ferreira, Glaucio Monteiro; Trossini, Gustavo Henrique Goulart

    2017-12-01

    Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs. © 2017 John Wiley & Sons A/S.

  13. Use of allosteric targets in the discovery of safer drugs.

    Science.gov (United States)

    Grover, Ashok Kumar

    2013-01-01

    The need for drugs with fewer side effects cannot be overemphasized. Today, most drugs modify the actions of enzymes, receptors, transporters and other molecules by directly binding to their active (orthosteric) sites. However, orthosteric site configuration is similar in several proteins performing related functions and this leads to a lower specificity of a drug for the desired protein. Consequently, such drugs may have adverse side effects. A new basis of drug discovery is emerging based on the binding of the drug molecules to sites away (allosteric) from the orthosteric sites. It is possible to find allosteric sites which are unique and hence more specific as targets for drug discovery. Of many available examples, two are highlighted here. The first is caloxins - a new class of highly specific inhibitors of plasma membrane Ca²⁺ pumps. The second concerns the modulation of receptors for the neurotransmitter acetylcholine, which binds to 12 types of receptors. Exploitation of allosteric sites has led to the discovery of drugs which can selectively modulate the activation of only 1 (M1 muscarinic) out of the 12 different types of acetylcholine receptors. These drugs are being tested for schizophrenia treatment. It is anticipated that the drug discovery exploiting allosteric sites will lead to more effective therapeutic agents with fewer side effects. Copyright © 2013 S. Karger AG, Basel.

  14. In silico pharmacology for a multidisciplinary drug discovery process.

    Science.gov (United States)

    Ortega, Santiago Schiaffino; Cara, Luisa Carlota López; Salvador, María Kimatrai

    2012-01-01

    The process of bringing new and innovative drugs, from conception and synthesis through to approval on the market can take the pharmaceutical industry 8-15 years and cost approximately $1.8 billion. Two key technologies are improving the hit-to-drug timeline: high-throughput screening (HTS) and rational drug design. In the latter case, starting from some known ligand-based or target-based information, a lead structure will be rationally designed to be tested in vitro or in vivo. Computational methods are part of many drug discovery programs, including the assessment of ADME (absorption-distribution-metabolism-excretion) and toxicity (ADMET) properties of compounds at the early stages of discovery/development with impressive results. The aim of this paper is to review, in a simple way, some of the most popular strategies used by modelers and some successful applications on computational chemistry to raise awareness of its importance and potential for an actual multidisciplinary drug discovery process.

  15. Preclinical experimental models of drug metabolism and disposition in drug discovery and development

    Directory of Open Access Journals (Sweden)

    Donglu Zhang

    2012-12-01

    Full Text Available Drug discovery and development involve the utilization of in vitro and in vivo experimental models. Different models, ranging from test tube experiments to cell cultures, animals, healthy human subjects, and even small numbers of patients that are involved in clinical trials, are used at different stages of drug discovery and development for determination of efficacy and safety. The proper selection and applications of correct models, as well as appropriate data interpretation, are critically important in decision making and successful advancement of drug candidates. In this review, we discuss strategies in the applications of both in vitro and in vivo experimental models of drug metabolism and disposition.

  16. Structural Genomics and Drug Discovery for Infectious Diseases

    International Nuclear Information System (INIS)

    Anderson, W.F.

    2009-01-01

    The application of structural genomics methods and approaches to proteins from organisms causing infectious diseases is making available the three dimensional structures of many proteins that are potential drug targets and laying the groundwork for structure aided drug discovery efforts. There are a number of structural genomics projects with a focus on pathogens that have been initiated worldwide. The Center for Structural Genomics of Infectious Diseases (CSGID) was recently established to apply state-of-the-art high throughput structural biology technologies to the characterization of proteins from the National Institute for Allergy and Infectious Diseases (NIAID) category A-C pathogens and organisms causing emerging, or re-emerging infectious diseases. The target selection process emphasizes potential biomedical benefits. Selected proteins include known drug targets and their homologs, essential enzymes, virulence factors and vaccine candidates. The Center also provides a structure determination service for the infectious disease scientific community. The ultimate goal is to generate a library of structures that are available to the scientific community and can serve as a starting point for further research and structure aided drug discovery for infectious diseases. To achieve this goal, the CSGID will determine protein crystal structures of 400 proteins and protein-ligand complexes using proven, rapid, highly integrated, and cost-effective methods for such determination, primarily by X-ray crystallography. High throughput crystallographic structure determination is greatly aided by frequent, convenient access to high-performance beamlines at third-generation synchrotron X-ray sources.

  17. Web-based services for drug design and discovery.

    Science.gov (United States)

    Frey, Jeremy G; Bird, Colin L

    2011-09-01

    Reviews of the development of drug discovery through the 20(th) century recognised the importance of chemistry and increasingly bioinformatics, but had relatively little to say about the importance of computing and networked computing in particular. However, the design and discovery of new drugs is arguably the most significant single application of bioinformatics and cheminformatics to have benefitted from the increases in the range and power of the computational techniques since the emergence of the World Wide Web, commonly now referred to as simply 'the Web'. Web services have enabled researchers to access shared resources and to deploy standardized calculations in their search for new drugs. This article first considers the fundamental principles of Web services and workflows, and then explores the facilities and resources that have evolved to meet the specific needs of chem- and bio-informatics. This strategy leads to a more detailed examination of the basic components that characterise molecules and the essential predictive techniques, followed by a discussion of the emerging networked services that transcend the basic provisions, and the growing trend towards embracing modern techniques, in particular the Semantic Web. In the opinion of the authors, the issues that require community action are: increasing the amount of chemical data available for open access; validating the data as provided; and developing more efficient links between the worlds of cheminformatics and bioinformatics. The goal is to create ever better drug design services.

  18. The impact of genetics on future drug discovery in schizophrenia.

    Science.gov (United States)

    Matsumoto, Mitsuyuki; Walton, Noah M; Yamada, Hiroshi; Kondo, Yuji; Marek, Gerard J; Tajinda, Katsunori

    2017-07-01

    Failures of investigational new drugs (INDs) for schizophrenia have left huge unmet medical needs for patients. Given the recent lackluster results, it is imperative that new drug discovery approaches (and resultant drug candidates) target pathophysiological alterations that are shared in specific, stratified patient populations that are selected based on pre-identified biological signatures. One path to implementing this paradigm is achievable by leveraging recent advances in genetic information and technologies. Genome-wide exome sequencing and meta-analysis of single nucleotide polymorphism (SNP)-based association studies have already revealed rare deleterious variants and SNPs in patient populations. Areas covered: Herein, the authors review the impact that genetics have on the future of schizophrenia drug discovery. The high polygenicity of schizophrenia strongly indicates that this disease is biologically heterogeneous so the identification of unique subgroups (by patient stratification) is becoming increasingly necessary for future investigational new drugs. Expert opinion: The authors propose a pathophysiology-based stratification of genetically-defined subgroups that share deficits in particular biological pathways. Existing tools, including lower-cost genomic sequencing and advanced gene-editing technology render this strategy ever more feasible. Genetically complex psychiatric disorders such as schizophrenia may also benefit from synergistic research with simpler monogenic disorders that share perturbations in similar biological pathways.

  19. Public and private sector contributions to the discovery and development of "impact" drugs.

    Science.gov (United States)

    Reichert, Janice M; Milne, Christopher-Paul

    2002-01-01

    Recently, well-publicized reports by Public Citizen and the Joint Economic Committee (JEC) of the US Congress questioned the role of the drug industry in the discovery and development of therapeutically important drugs. To gain a better understanding of the relative roles of the public and private sectors in pharmaceutic innovation, the Tufts Center for the Study of Drug Development evaluated the underlying National Institutes of Health (NIH) and academic research cited in the Public Citizen and JEC reports and performed its own assessment of the relationship between the private and public sectors in drug discovery and development of 21 "impact" drugs. We found that, ultimately, any attempt to measure the relative contribution of the public and private sectors to the research and development (R&D) of therapeutically important drugs by output alone, such as counting publications or even product approvals, is flawed. Several key factors (eg, degree of uncertainty, expected market value, potential social benefit) affect investment decisions and determine whether public or private sector funds, or both, are most appropriate. Because of the competitiveness and complexity of today's R&D environment, both sectors are increasingly challenged to show returns on their investment and the traditional boundaries separating the roles of the private and public research spheres have become increasingly blurred. What remains clear, however, is that the process still starts with good science and ends with good medicine.

  20. Hierarchical virtual screening approaches in small molecule drug discovery.

    Science.gov (United States)

    Kumar, Ashutosh; Zhang, Kam Y J

    2015-01-01

    Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Application of PBPK modelling in drug discovery and development at Pfizer.

    Science.gov (United States)

    Jones, Hannah M; Dickins, Maurice; Youdim, Kuresh; Gosset, James R; Attkins, Neil J; Hay, Tanya L; Gurrell, Ian K; Logan, Y Raj; Bungay, Peter J; Jones, Barry C; Gardner, Iain B

    2012-01-01

    Early prediction of human pharmacokinetics (PK) and drug-drug interactions (DDI) in drug discovery and development allows for more informed decision making. Physiologically based pharmacokinetic (PBPK) modelling can be used to answer a number of questions throughout the process of drug discovery and development and is thus becoming a very popular tool. PBPK models provide the opportunity to integrate key input parameters from different sources to not only estimate PK parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. Using examples from the literature and our own company, we have shown how PBPK techniques can be utilized through the stages of drug discovery and development to increase efficiency, reduce the need for animal studies, replace clinical trials and to increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however, some limitations need to be addressed to realize its application and utility more broadly.

  2. [Chapter 2. Transitions in drug-discovery technology and drug-development in Japan (1980-2010)].

    Science.gov (United States)

    Sakakibara, Noriko; Yoshioka, Ryuzo; Matsumoto, Kazuo

    2014-01-01

    In 1970s, the material patent system was introduced in Japan. Since then, many Japanese pharmaceutical companies have endeavored to create original in-house products. From 1980s, many of the innovative products were small molecular drugs and were developed using powerful medicinal-chemical technologies. Among them were antibiotics and effective remedies for the digestive organs and circulatory organs. During this period, Japanese companies were able to launch some blockbuster drugs. At the same time, the pharmaceutical market, which had grown rapidly for two decades, was beginning to level off. From the late 1990s, drug development was slowing down due to the lack of expertise in biotechnology such as genetic engineering. In response to the circumstances, the research and development on biotechnology-based drugs such as antibody drugs have become more dynamic and popular at companies than small molecule drugs. In this paper, the writers reviewed in detail the transitions in drug discovery and development between 1980 and 2010.

  3. Drug discovery for Chagas disease should consider Trypanosoma cruzi strain diversity

    Directory of Open Access Journals (Sweden)

    Bianca Zingales

    2014-09-01

    Full Text Available This opinion piece presents an approach to standardisation of an important aspect of Chagas disease drug discovery and development: selecting Trypanosoma cruzi strains for in vitro screening. We discuss the rationale for strain selection representing T. cruzi diversity and provide recommendations on the preferred parasite stage for drug discovery, T. cruzi discrete typing units to include in the panel of strains and the number of strains/clones for primary screens and lead compounds. We also consider experimental approaches for in vitro drug assays. The Figure illustrates the current Chagas disease drug-discovery and development landscape.

  4. Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders.

    Science.gov (United States)

    Han, Chanshuai; Chaineau, Mathilde; Chen, Carol X-Q; Beitel, Lenore K; Durcan, Thomas M

    2018-01-01

    Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs) from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop "first-of-their-kind" disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI) and its partners are piloting an "Open Science" model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders.

  5. Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Chanshuai Han

    2018-02-01

    Full Text Available Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop “first-of-their-kind” disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI and its partners are piloting an “Open Science” model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders.

  6. Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations.

    Science.gov (United States)

    Cournia, Zoe; Allen, Bryce; Sherman, Woody

    2017-12-26

    Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives

  7. Net present value approaches for drug discovery.

    Science.gov (United States)

    Svennebring, Andreas M; Wikberg, Jarl Es

    2013-12-01

    Three dedicated approaches to the calculation of the risk-adjusted net present value (rNPV) in drug discovery projects under different assumptions are suggested. The probability of finding a candidate drug suitable for clinical development and the time to the initiation of the clinical development is assumed to be flexible in contrast to the previously used models. The rNPV of the post-discovery cash flows is calculated as the probability weighted average of the rNPV at each potential time of initiation of clinical development. Practical considerations how to set probability rates, in particular during the initiation and termination of a project is discussed.

  8. Bead-based screening in chemical biology and drug discovery

    DEFF Research Database (Denmark)

    Komnatnyy, Vitaly V.; Nielsen, Thomas Eiland; Qvortrup, Katrine

    2018-01-01

    libraries for early drug discovery. Among the various library forms, the one-bead-one-compound (OBOC) library, where each bead carries many copies of a single compound, holds the greatest potential for the rapid identification of novel hits against emerging drug targets. However, this potential has not yet...... been fully realized due to a number of technical obstacles. In this feature article, we review the progress that has been made towards bead-based library screening and applications to the discovery of bioactive compounds. We identify the key challenges of this approach and highlight key steps needed......High-throughput screening is an important component of the drug discovery process. The screening of libraries containing hundreds of thousands of compounds requires assays amanable to miniaturisation and automization. Combinatorial chemistry holds a unique promise to deliver structural diverse...

  9. Computer-Aided Drug Discovery in Plant Pathology.

    Science.gov (United States)

    Shanmugam, Gnanendra; Jeon, Junhyun

    2017-12-01

    Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides .

  10. Cardiovascular drug discovery in the academic setting: building infrastructure, harnessing strengths, and seeking synergies.

    Science.gov (United States)

    Gardell, Stephen J; Roth, Gregory P; Kelly, Daniel P

    2010-10-01

    The flow of innovative, effective, and safe new drugs from pharmaceutical laboratories for the treatment and prevention of cardiovascular disease has slowed to a trickle. While the need for breakthrough cardiovascular disease drugs is still paramount, the incentive to develop these agents has been blunted by burgeoning clinical development costs coupled with a heightened risk of failure due to the unprecedented nature of the emerging drug targets and increasingly challenging regulatory environment. A fuller understanding of the drug targets and employing novel biomarker strategies in clinical trials should serve to mitigate the risk. In any event, these current challenges have evoked changing trends in the pharmaceutical industry, which have created an opportunity for non-profit biomedical research institutions to play a pivotal partnering role in early stage drug discovery. The obvious strengths of academic research institutions is the breadth of their scientific programs and the ability and motivation to "go deep" to identify and characterize new target pathways that unlock the specific mysteries of cardiovascular diseases--leading to a bounty of novel therapeutic targets and prescient biomarkers. However, success in the drug discovery arena within the academic environment is contingent upon assembling the requisite infrastructure, annexing the talent to interrogate and validate the drug targets, and building translational bridges with pharmaceutical organizations and patient-oriented researchers.

  11. Biomimicry as a basis for drug discovery.

    Science.gov (United States)

    Kolb, V M

    1998-01-01

    Selected works are discussed which clearly demonstrate that mimicking various aspects of the process by which natural products evolved is becoming a powerful tool in contemporary drug discovery. Natural products are an established and rich source of drugs. The term "natural product" is often used synonymously with "secondary metabolite." Knowledge of genetics and molecular evolution helps us understand how biosynthesis of many classes of secondary metabolites evolved. One proposed hypothesis is termed "inventive evolution." It invokes duplication of genes, and mutation of the gene copies, among other genetic events. The modified duplicate genes, per se or in conjunction with other genetic events, may give rise to new enzymes, which, in turn, may generate new products, some of which may be selected for. Steps of the inventive evolution can be mimicked in several ways for purpose of drug discovery. For example, libraries of chemical compounds of any imaginable structure may be produced by combinatorial synthesis. Out of these libraries new active compounds can be selected. In another example, genetic system can be manipulated to produce modified natural products ("unnatural natural products"), from which new drugs can be selected. In some instances, similar natural products turn up in species that are not direct descendants of each other. This is presumably due to a horizontal gene transfer. The mechanism of this inter-species gene transfer can be mimicked in therapeutic gene delivery. Mimicking specifics or principles of chemical evolution including experimental and test-tube evolution also provides leads for new drug discovery.

  12. Drugs from the Oceans: Marine Natural Products as Leads for Drug Discovery.

    Science.gov (United States)

    Altmann, Karl-Heinz

    2017-10-25

    The marine environment harbors a vast number of species that are the source of a wide array of structurally diverse bioactive secondary metabolites. At this point in time, roughly 27'000 marine natural products are known, of which eight are (were) at the origin of seven marketed drugs, mostly for the treatment of cancer. The majority of these drugs and also of drug candidates currently undergoing clinical evaluation (excluding antibody-drug conjugates) are unmodified natural products, but synthetic chemistry has played a central role in the discovery and/or development of all but one of the approved marine-derived drugs. More than 1000 new marine natural products have been isolated per year over the last decade, but the pool of new and unique structures is far from exhausted. To fully leverage the potential offered by the structural diversity of marine-produced secondary metabolites for drug discovery will require their broad assessment for different bioactivities and the productive interplay between new fermentation technologies, synthetic organic chemistry, and medicinal chemistry, in order to secure compound supply and enable lead optimization.

  13. Key drivers of biomedical innovation in cancer drug discovery

    OpenAIRE

    Huber, Margit A; Kraut, Norbert

    2014-01-01

    Discovery and translational research has led to the identification of a series of ?cancer drivers??genes that, when mutated or otherwise misregulated, can drive malignancy. An increasing number of drugs that directly target such drivers have demonstrated activity in clinical trials and are shaping a new landscape for molecularly targeted cancer therapies. Such therapies rely on molecular and genetic diagnostic tests to detect the presence of a biomarker that predicts response. Here, we highli...

  14. Bigger Data, Collaborative Tools and the Future of Predictive Drug Discovery

    Science.gov (United States)

    Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

    2014-01-01

    Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas. PMID:24943138

  15. Drug target ontology to classify and integrate drug discovery data.

    Science.gov (United States)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C

    2017-11-09

    One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. DTO was built based on the need for a formal semantic

  16. Oncology drug discovery: planning a turnaround.

    Science.gov (United States)

    Toniatti, Carlo; Jones, Philip; Graham, Hilary; Pagliara, Bruno; Draetta, Giulio

    2014-04-01

    We have made remarkable progress in our understanding of the pathophysiology of cancer. This improved understanding has resulted in increasingly effective targeted therapies that are better tolerated than conventional cytotoxic agents and even curative in some patients. Unfortunately, the success rate of drug approval has been limited, and therapeutic improvements have been marginal, with too few exceptions. In this article, we review the current approach to oncology drug discovery and development, identify areas in need of improvement, and propose strategies to improve patient outcomes. We also suggest future directions that may improve the quality of preclinical and early clinical drug evaluation, which could lead to higher approval rates of anticancer drugs.

  17. Traditional Chinese Medicine-Based Network Pharmacology Could Lead to New Multicompound Drug Discovery

    Directory of Open Access Journals (Sweden)

    Jian Li

    2012-01-01

    Full Text Available Current strategies for drug discovery have reached a bottleneck where the paradigm is generally “one gene, one drug, one disease.” However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

  18. Structured evaluation of rodent behavioral tests used in drug discovery research

    Directory of Open Access Journals (Sweden)

    Anders eHånell

    2014-07-01

    Full Text Available A large variety of rodent behavioral tests are currently being used to evaluate traits such as sensory-motor function, social interactions, anxiety-like and depressive-like behavior, substance dependence and various forms of cognitive function. Most behavioral tests have an inherent complexity, and their use requires consideration of several aspects such as the source of motivation in the test, the interaction between experimenter and animal, sources of variability, the sensory modality required by the animal to solve the task as well as costs and required work effort. Of particular importance is a test’s validity because of its influence on the chance of successful translation of preclinical results to clinical settings. High validity may, however, have to be balanced against practical constraints and there are no behavioral tests with optimal characteristics. The design and development of new behavioral tests is therefore an ongoing effort and there are now well over one hundred tests described in the contemporary literature. Some of them are well established following extensive use, while others are novel and still unproven. The task of choosing a behavioral test for a particular project may therefore be daunting and the aim of the present review is to provide a structured way to evaluate rodent behavioral tests aimed at drug discovery research.

  19. The rise of fragment-based drug discovery.

    Science.gov (United States)

    Murray, Christopher W; Rees, David C

    2009-06-01

    The search for new drugs is plagued by high attrition rates at all stages in research and development. Chemists have an opportunity to tackle this problem because attrition can be traced back, in part, to the quality of the chemical leads. Fragment-based drug discovery (FBDD) is a new approach, increasingly used in the pharmaceutical industry, for reducing attrition and providing leads for previously intractable biological targets. FBDD identifies low-molecular-weight ligands (∼150 Da) that bind to biologically important macromolecules. The three-dimensional experimental binding mode of these fragments is determined using X-ray crystallography or NMR spectroscopy, and is used to facilitate their optimization into potent molecules with drug-like properties. Compared with high-throughput-screening, the fragment approach requires fewer compounds to be screened, and, despite the lower initial potency of the screening hits, offers more efficient and fruitful optimization campaigns. Here, we review the rise of FBDD, including its application to discovering clinical candidates against targets for which other chemistry approaches have struggled.

  20. Application of lean manufacturing concepts to drug discovery: rapid analogue library synthesis.

    Science.gov (United States)

    Weller, Harold N; Nirschl, David S; Petrillo, Edward W; Poss, Michael A; Andres, Charles J; Cavallaro, Cullen L; Echols, Martin M; Grant-Young, Katherine A; Houston, John G; Miller, Arthur V; Swann, R Thomas

    2006-01-01

    The application of parallel synthesis to lead optimization programs in drug discovery has been an ongoing challenge since the first reports of library synthesis. A number of approaches to the application of parallel array synthesis to lead optimization have been attempted over the years, ranging from widespread deployment by (and support of) individual medicinal chemists to centralization as a service by an expert core team. This manuscript describes our experience with the latter approach, which was undertaken as part of a larger initiative to optimize drug discovery. In particular, we highlight how concepts taken from the manufacturing sector can be applied to drug discovery and parallel synthesis to improve the timeliness and thus the impact of arrays on drug discovery.

  1. The Critical Role of Organic Chemistry in Drug Discovery.

    Science.gov (United States)

    Rotella, David P

    2016-10-19

    Small molecules remain the backbone for modern drug discovery. They are conceived and synthesized by medicinal chemists, many of whom were originally trained as organic chemists. Support from government and industry to provide training and personnel for continued development of this critical skill set has been declining for many years. This Viewpoint highlights the value of organic chemistry and organic medicinal chemists in the complex journey of drug discovery as a reminder that basic science support must be restored.

  2. Recent advances in combinatorial biosynthesis for drug discovery

    Directory of Open Access Journals (Sweden)

    Sun H

    2015-02-01

    Full Text Available Huihua Sun,1,* Zihe Liu,1,* Huimin Zhao,1,2 Ee Lui Ang1 1Metabolic Engineering Research Laboratory, Institute of Chemical and Engineering Sciences, Agency for Science, Technology and Research, Singapore; 2Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA *These authors contributed equally to this work Abstract: Because of extraordinary structural diversity and broad biological activities, natural products have played a significant role in drug discovery. These therapeutically important secondary metabolites are assembled and modified by dedicated biosynthetic pathways in their host living organisms. Traditionally, chemists have attempted to synthesize natural product analogs that are important sources of new drugs. However, the extraordinary structural complexity of natural products sometimes makes it challenging for traditional chemical synthesis, which usually involves multiple steps, harsh conditions, toxic organic solvents, and byproduct wastes. In contrast, combinatorial biosynthesis exploits substrate promiscuity and employs engineered enzymes and pathways to produce novel “unnatural” natural products, substantially expanding the structural diversity of natural products with potential pharmaceutical value. Thus, combinatorial biosynthesis provides an environmentally friendly way to produce natural product analogs. Efficient expression of the combinatorial biosynthetic pathway in genetically tractable heterologous hosts can increase the titer of the compound, eventually resulting in less expensive drugs. In this review, we will discuss three major strategies for combinatorial biosynthesis: 1 precursor-directed biosynthesis; 2 enzyme-level modification, which includes swapping of the entire domains, modules and subunits, site-specific mutagenesis, and directed evolution; 3 pathway-level recombination. Recent examples of combinatorial biosynthesis employing these

  3. Drug discovery for alopecia: gone today, hair tomorrow.

    Science.gov (United States)

    Santos, Zenildo; Avci, Pinar; Hamblin, Michael R

    2015-03-01

    Hair loss or alopecia affects the majority of the population at some time in their life, and increasingly, sufferers are demanding treatment. Three main types of alopecia (androgenic [AGA], areata [AA] and chemotherapy-induced [CIA]) are very different, and have their own laboratory models and separate drug-discovery efforts. In this article, the authors review the biology of hair, hair follicle (HF) cycling, stem cells and signaling pathways. AGA, due to dihydrotesterone, is treated by 5-α reductase inhibitors, androgen receptor blockers and ATP-sensitive potassium channel-openers. AA, which involves attack by CD8(+)NK group 2D-positive (NKG2D(+)) T cells, is treated with immunosuppressives, biologics and JAK inhibitors. Meanwhile, CIA is treated by apoptosis inhibitors, cytokines and topical immunotherapy. The desire to treat alopecia with an easy topical preparation is expected to grow with time, particularly with an increasing aging population. The discovery of epidermal stem cells in the HF has given new life to the search for a cure for baldness. Drug discovery efforts are being increasingly centered on these stem cells, boosting the hair cycle and reversing miniaturization of HF. Better understanding of the molecular mechanisms underlying the immune attack in AA will yield new drugs. New discoveries in HF neogenesis and low-level light therapy will undoubtedly have a role to play.

  4. Open source drug discovery in practice: a case study.

    Science.gov (United States)

    Årdal, Christine; Røttingen, John-Arne

    2012-01-01

    Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access) and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD) and The Synaptic Leap's Schistosomiasis project (TSLS). Data were gathered from four sources: interviews of participating members (n = 14), a survey of potential members (n = 61), an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline) before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high quality research at low cost. The critical success factors appear to be clearly

  5. An invertebrate model for CNS drug discovery

    DEFF Research Database (Denmark)

    Al-Qadi, Sonia; Schiøtt, Morten; Hansen, Steen Honoré

    2015-01-01

    BACKGROUND: ABC efflux transporters at the blood brain barrier (BBB), namely the P-glycoprotein (P-gp), restrain the development of central nervous system (CNS) drugs. Consequently, early screening of CNS drug candidates is pivotal to identify those affected by efflux activity. Therefore, simple,...... barriers. CONCLUSION: Findings suggest a conserved mechanism of brain efflux activity between insects and vertebrates, confirming that this model holds promise for inexpensive and high-throughput screening relative to in vivo models, for CNS drug discovery....

  6. [Fragment-based drug discovery: concept and aim].

    Science.gov (United States)

    Tanaka, Daisuke

    2010-03-01

    Fragment-Based Drug Discovery (FBDD) has been recognized as a newly emerging lead discovery methodology that involves biophysical fragment screening and chemistry-driven fragment-to-lead stages. Although fragments, defined as structurally simple and small compounds (typically FBDD primarily turns our attention to weakly but specifically binding fragments (hit fragments) as the starting point of medicinal chemistry. Hit fragments are then promoted to more potent lead compounds through linking or merging with another hit fragment and/or attaching functional groups. Another positive aspect of FBDD is ligand efficiency. Ligand efficiency is a useful guide in screening hit selection and hit-to-lead phases to achieve lead-likeness. Owing to these features, a number of successful applications of FBDD to "undruggable targets" (where HTS and other lead identification methods failed to identify useful lead compounds) have been reported. As a result, FBDD is now expected to complement more conventional methodologies. This review, as an introduction of the following articles, will summarize the fundamental concepts of FBDD and will discuss its advantages over other conventional drug discovery approaches.

  7. High throughput electrophysiology: new perspectives for ion channel drug discovery

    DEFF Research Database (Denmark)

    Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter

    2003-01-01

    . A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct....... The introduction of new powerful HTS electrophysiological techniques is predicted to cause a revolution in ion channel drug discovery....

  8. Systems biology-embedded target validation: improving efficacy in drug discovery.

    Science.gov (United States)

    Vandamme, Drieke; Minke, Benedikt A; Fitzmaurice, William; Kholodenko, Boris N; Kolch, Walter

    2014-01-01

    The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment. © 2013 Wiley Periodicals, Inc.

  9. The principle of safety evaluation in medicinal drug - how can toxicology contribute to drug discovery and development as a multidisciplinary science?

    Science.gov (United States)

    Horii, Ikuo

    2016-01-01

    Pharmaceutical (drug) safety assessment covers a diverse science-field in the drug discovery and development including the post-approval and post-marketing phases in order to evaluate safety and risk management. The principle in toxicological science is to be placed on both of pure and applied sciences that are derived from past/present scientific knowledge and coming new science and technology. In general, adverse drug reactions are presented as "biological responses to foreign substances." This is the basic concept of thinking about the manifestation of adverse drug reactions. Whether or not toxic expressions are extensions of the pharmacological effect, adverse drug reactions as seen from molecular targets are captured in the category of "on-target" or "off-target", and are normally expressed as a biological defense reaction. Accordingly, reactions induced by pharmaceuticals can be broadly said to be defensive reactions. Recent molecular biological conception is in line with the new, remarkable scientific and technological developments in the medical and pharmaceutical areas, and the viewpoints in the field of toxicology have shown that they are approaching toward the same direction as well. This paper refers to the basic concept of pharmaceutical toxicology, the differences for safety assessment in each stage of drug discovery and development, regulatory submission, and the concept of scientific considerations for risk assessment and management from the viewpoint of "how can multidisciplinary toxicology contribute to innovative drug discovery and development?" And also realistic translational research from preclinical to clinical application is required to have a significant risk management in post market by utilizing whole scientific data derived from basic and applied scientific research works. In addition, the significance for employing the systems toxicology based on AOP (Adverse Outcome Pathway) analysis is introduced, and coming challenges on precision

  10. Drug Discovery in an Academic Setting: Playing to the Strengths

    OpenAIRE

    Huryn, Donna M.

    2013-01-01

    Drug discovery and medicinal chemistry initiatives in academia provide an opportunity to create a unique environment that is distinct from the traditional industrial model. Two characteristics of a university setting that are not usually associated with pharma are the ability to pursue high-risk projects and a depth of expertise, infrastructure, and capabilities in focused areas. Encouraging, supporting, and fostering drug discovery efforts that take advantage of these an...

  11. Scientific Prediction and Prophetic Patenting in Drug Discovery.

    Science.gov (United States)

    Curry, Stephen H; Schneiderman, Anne M

    2015-01-01

    Pharmaceutical patenting involves writing claims based on both discoveries already made, and on prophesy of future developments in an ongoing project. This is necessitated by the very different timelines involved in the drug discovery and product development process on the one hand, and successful patenting on the other. If patents are sought too early there is a risk that patent examiners will disallow claims because of lack of enablement. If patenting is delayed, claims are at risk of being denied on the basis of existence of prior art, because the body of relevant known science will have developed significantly while the project was being pursued. This review examines the role of prophetic patenting in relation to the essential predictability of many aspects of drug discovery science, promoting the concepts of discipline-related and project-related prediction. This is especially directed towards patenting activities supporting commercialization of academia-based discoveries, where long project timelines occur, and where experience, and resources to pay for patenting, are limited. The need for improved collaborative understanding among project scientists, technology transfer professionals in, for example, universities, patent attorneys, and patent examiners is emphasized.

  12. 3D in vitro technology for drug discovery.

    Science.gov (United States)

    Hosseinkhani, Hossein

    2012-02-01

    Three-dimensional (3D) in vitro systems that can mimic organ and tissue structure and function in vivo, will be of great benefit for a variety of biological applications from basic biology to toxicity testing and drug discovery. There have been several attempts to generate 3D tissue models but most of these models require costly equipment, and the most serious disadvantage in them is that they are too far from the mature human organs in vivo. Because of these problems, research and development in drug discovery, toxicity testing and biotech industries are highly expensive, and involve sacrifice of countless animals and it takes several years to bring a single drug/product to the market or to find the toxicity or otherwise of chemical entities. Our group has been actively working on several alternative models by merging biomaterials science, nanotechnology and biological principles to generate 3D in vitro living organs, to be called "Human Organs-on-Chip", to mimic natural organ/tissues, in order to reduce animal testing and clinical trials. We have fabricated a novel type of mechanically and biologically bio-mimicking collagen-based hydrogel that would provide for interconnected mini-wells in which 3D cell/organ culture of human samples in a manner similar to human organs with extracellular matrix (ECM) molecules would be possible. These products mimic the physical, chemical, and biological properties of natural organs and tissues at different scales. This paper will review the outcome of our several experiments so far in this direction and the future perspectives.

  13. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

    Directory of Open Access Journals (Sweden)

    Tom L. Blundell

    2017-07-01

    Full Text Available The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein–protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called `linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  14. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry.

    Science.gov (United States)

    Blundell, Tom L

    2017-07-01

    The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein-protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called 'linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  15. Screening the Medicines for Malaria Venture Pathogen Box across Multiple Pathogens Reclassifies Starting Points for Open-Source Drug Discovery.

    Science.gov (United States)

    Duffy, Sandra; Sykes, Melissa L; Jones, Amy J; Shelper, Todd B; Simpson, Moana; Lang, Rebecca; Poulsen, Sally-Ann; Sleebs, Brad E; Avery, Vicky M

    2017-09-01

    Open-access drug discovery provides a substantial resource for diseases primarily affecting the poor and disadvantaged. The open-access Pathogen Box collection is comprised of compounds with demonstrated biological activity against specific pathogenic organisms. The supply of this resource by the Medicines for Malaria Venture has the potential to provide new chemical starting points for a number of tropical and neglected diseases, through repurposing of these compounds for use in drug discovery campaigns for these additional pathogens. We tested the Pathogen Box against kinetoplastid parasites and malaria life cycle stages in vitro Consequently, chemical starting points for malaria, human African trypanosomiasis, Chagas disease, and leishmaniasis drug discovery efforts have been identified. Inclusive of this in vitro biological evaluation, outcomes from extensive literature reviews and database searches are provided. This information encompasses commercial availability, literature reference citations, other aliases and ChEMBL number with associated biological activity, where available. The release of this new data for the Pathogen Box collection into the public domain will aid the open-source model of drug discovery. Importantly, this will provide novel chemical starting points for drug discovery and target identification in tropical disease research. Copyright © 2017 Duffy et al.

  16. Overcoming the challenges of drug discovery for neglected tropical diseases: the A·WOL experience.

    Science.gov (United States)

    Johnston, Kelly L; Ford, Louise; Taylor, Mark J

    2014-03-01

    Neglected tropical diseases (NTDs) are a group of 17 diseases that typically affect poor people in tropical countries. Each has been neglected for decades in terms of funding, research, and policy, but the recent grouping of them into one unit, which can be targeted using integrated control measures, together with increased advocacy has helped to place them on the global health agenda. The World Health Organization has set ambitious goals to control or eliminate 10 NTDs by 2020 and launched a roadmap in January 2012 to guide this global plan. The result of the launch meeting, which brought together representatives from the pharmaceutical industry, donors, and politicians, was the London Declaration: a series of commitments to provide more drugs, research, and funds to achieve the 2020 goals. Drug discovery and development for these diseases are extremely challenging, and this article highlights these challenges in the context of the London Declaration, before focusing on an example of a drug discovery and development program for the NTDs onchocerciasis and lymphatic filariasis (the anti-Wolbachia consortium, A·WOL).

  17. Can biochemistry drive drug discovery beyond simple potency measurements?

    Science.gov (United States)

    Chène, Patrick

    2012-04-01

    Among the fields of expertise required to develop drugs successfully, biochemistry holds a key position in drug discovery at the interface between chemistry, structural biology and cell biology. However, taking the example of protein kinases, it appears that biochemical assays are mostly used in the pharmaceutical industry to measure compound potency and/or selectivity. This limited use of biochemistry is surprising, given that detailed biochemical analyses are commonly used in academia to unravel molecular recognition processes. In this article, I show that biochemistry can provide invaluable information on the dynamics and energetics of compound-target interactions that cannot be obtained on the basis of potency measurements and structural data. Therefore, an extensive use of biochemistry in drug discovery could facilitate the identification and/or development of new drugs. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Simulation with quantum mechanics/molecular mechanics for drug discovery.

    Science.gov (United States)

    Barbault, Florent; Maurel, François

    2015-10-01

    Biological macromolecules, such as proteins or nucleic acids, are (still) molecules and thus they follow the same chemical rules that any simple molecule follows, even if their size generally renders accurate studies unhelpful. However, in the context of drug discovery, a detailed analysis of ligand association is required for understanding or predicting their interactions and hybrid quantum mechanics/molecular mechanics (QM/MM) computations are relevant tools to help elucidate this process. In this review, the authors explore the use of QM/MM for drug discovery. After a brief description of the molecular mechanics (MM) technique, the authors describe the subtractive and additive techniques for QM/MM computations. The authors then present several application cases in topics involved in drug discovery. QM/MM have been widely employed during the last decades to study chemical processes such as enzyme-inhibitor interactions. However, despite the enthusiasm around this area, plain MM simulations may be more meaningful than QM/MM. To obtain reliable results, the authors suggest fixing several keystone parameters according to the underlying chemistry of each studied system.

  19. From Protein Structure to Small-Molecules: Recent Advances and Applications to Fragment-Based Drug Discovery.

    Science.gov (United States)

    Ferreira, Leonardo G; Andricopulo, Adriano D

    2017-01-01

    Fragment-based drug discovery (FBDD) is a broadly used strategy in structure-guided ligand design, whereby low-molecular weight hits move from lead-like to drug-like compounds. Over the past 15 years, an increasingly important role of the integration of these strategies into industrial and academic research platforms has been successfully established, allowing outstanding contributions to drug discovery. One important factor for the current prominence of FBDD is the better coverage of the chemical space provided by fragment-like libraries. The development of the field relies on two features: (i) the growing number of structurally characterized drug targets and (ii) the enormous chemical diversity available for experimental and virtual screenings. Indeed, fragment-based campaigns have contributed to address major challenges in lead optimization, such as the appropriate physicochemical profile of clinical candidates. This perspective paper outlines the usefulness and applications of FBDD approaches in medicinal chemistry and drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. Fragment-based drug discovery and protein–protein interactions

    Directory of Open Access Journals (Sweden)

    Turnbull AP

    2014-09-01

    Full Text Available Andrew P Turnbull,1 Susan M Boyd,2 Björn Walse31CRT Discovery Laboratories, Department of Biological Sciences, Birkbeck, University of London, London, UK; 2IOTA Pharmaceuticals Ltd, Cambridge, UK; 3SARomics Biostructures AB, Lund, SwedenAbstract: Protein–protein interactions (PPIs are involved in many biological processes, with an estimated 400,000 PPIs within the human proteome. There is significant interest in exploiting the relatively unexplored potential of these interactions in drug discovery, driven by the need to find new therapeutic targets. Compared with classical drug discovery against targets with well-defined binding sites, developing small-molecule inhibitors against PPIs where the contact surfaces are frequently more extensive and comparatively flat, with most of the binding energy localized in “hot spots”, has proven far more challenging. However, despite the difficulties associated with targeting PPIs, important progress has been made in recent years with fragment-based drug discovery playing a pivotal role in improving their tractability. Computational and empirical approaches can be used to identify hot-spot regions and assess the druggability and ligandability of new targets, whilst fragment screening campaigns can detect low-affinity fragments that either directly or indirectly perturb the PPI. Once fragment hits have been identified and confirmed using biochemical and biophysical approaches, three-dimensional structural data derived from nuclear magnetic resonance or X-ray crystallography can be used to drive medicinal chemistry efforts towards the development of more potent inhibitors. A small-scale comparison presented in this review of “standard” fragments with those targeting PPIs has revealed that the latter tend to be larger, be more lipophilic, and contain more polar (acid/base functionality, whereas three-dimensional descriptor data indicate that there is little difference in their three

  1. Structure and organization of drug-target networks: insights from genomic approaches for drug discovery.

    Science.gov (United States)

    Janga, Sarath Chandra; Tzakos, Andreas

    2009-12-01

    Recent years have seen an explosion in the amount of "omics" data and the integration of several disciplines, which has influenced all areas of life sciences including that of drug discovery. Several lines of evidence now suggest that the traditional notion of "one drug-one protein" for one disease does not hold any more and that treatment for most complex diseases can best be attempted using polypharmacological approaches. In this review, we formalize the definition of a drug-target network by decomposing it into drug, target and disease spaces and provide an overview of our understanding in recent years about its structure and organizational principles. We discuss advances made in developing promiscuous drugs following the paradigm of polypharmacology and reveal their advantages over traditional drugs for targeting diseases such as cancer. We suggest that drug-target networks can be decomposed to be studied at a variety of levels and argue that such network-based approaches have important implications in understanding disease phenotypes and in accelerating drug discovery. We also discuss the potential and scope network pharmacology promises in harnessing the vast amount of data from high-throughput approaches for therapeutic advantage.

  2. Collaboration for rare disease drug discovery research [v1; ref status: indexed, http://f1000r.es/4l6

    Directory of Open Access Journals (Sweden)

    Nadia K. Litterman

    2014-10-01

    Full Text Available Rare disease research has reached a tipping point, with the confluence of scientific and technologic developments that if appropriately harnessed, could lead to key breakthroughs and treatments for this set of devastating disorders. Industry-wide trends have revealed that the traditional drug discovery research and development (R&D model is no longer viable, and drug companies are evolving their approach. Rather than only pursue blockbuster therapeutics for heterogeneous, common diseases, drug companies have increasingly begun to shift their focus to rare diseases. In academia, advances in genetics analyses and disease mechanisms have allowed scientific understanding to mature, but the lack of funding and translational capability severely limits the rare disease research that leads to clinical trials. Simultaneously, there is a movement towards increased research collaboration, more data sharing, and heightened engagement and active involvement by patients, advocates, and foundations. The growth in networks and social networking tools presents an opportunity to help reach other patients but also find researchers and build collaborations. The growth of collaborative software that can enable researchers to share their data could also enable rare disease patients and foundations to manage their portfolio of funded projects for developing new therapeutics and suggest drug repurposing opportunities. Still there are many thousands of diseases without treatments and with only fragmented research efforts. We will describe some recent progress in several rare diseases used as examples and propose how collaborations could be facilitated. We propose that the development of a center of excellence that integrates and shares informatics resources for rare diseases sponsored by all of the stakeholders would help foster these initiatives.

  3. Machine-learning techniques applied to antibacterial drug discovery.

    Science.gov (United States)

    Durrant, Jacob D; Amaro, Rommie E

    2015-01-01

    The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. © 2015 John Wiley & Sons A/S.

  4. Open Source Drug Discovery in Practice: A Case Study

    Science.gov (United States)

    Årdal, Christine; Røttingen, John-Arne

    2012-01-01

    Background Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access) and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. Methodology/Principal Findings A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD) and The Synaptic Leap's Schistosomiasis project (TSLS). Data were gathered from four sources: interviews of participating members (n = 14), a survey of potential members (n = 61), an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline) before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. Conclusions/Significance Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high quality

  5. Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

    Science.gov (United States)

    Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

    2017-02-01

    Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

  6. The development of high-content screening (HCS) technology and its importance to drug discovery.

    Science.gov (United States)

    Fraietta, Ivan; Gasparri, Fabio

    2016-01-01

    High-content screening (HCS) was introduced about twenty years ago as a promising analytical approach to facilitate some critical aspects of drug discovery. Its application has spread progressively within the pharmaceutical industry and academia to the point that it today represents a fundamental tool in supporting drug discovery and development. Here, the authors review some of significant progress in the HCS field in terms of biological models and assay readouts. They highlight the importance of high-content screening in drug discovery, as testified by its numerous applications in a variety of therapeutic areas: oncology, infective diseases, cardiovascular and neurodegenerative diseases. They also dissect the role of HCS technology in different phases of the drug discovery pipeline: target identification, primary compound screening, secondary assays, mechanism of action studies and in vitro toxicology. Recent advances in cellular assay technologies, such as the introduction of three-dimensional (3D) cultures, induced pluripotent stem cells (iPSCs) and genome editing technologies (e.g., CRISPR/Cas9), have tremendously expanded the potential of high-content assays to contribute to the drug discovery process. Increasingly predictive cellular models and readouts, together with the development of more sophisticated and affordable HCS readers, will further consolidate the role of HCS technology in drug discovery.

  7. Comparative psychology and the grand challenge of drug discovery in psychiatry and neurodegeneration.

    Science.gov (United States)

    Brunner, Dani; Balcı, Fuat; Ludvig, Elliot A

    2012-02-01

    Drug discovery for brain disorders is undergoing a period of upheaval. Faced with an empty drug pipeline and numerous failures of potential new drugs in clinical trials, many large pharmaceutical companies have been shrinking or even closing down their research divisions that focus on central nervous system (CNS) disorders. In this paper, we argue that many of the difficulties facing CNS drug discovery stem from a lack of robustness in pre-clinical (i.e., non-human animal) testing. There are two main sources for this lack of robustness. First, there is the lack of replicability of many results from the pre-clinical stage, which we argue is driven by a combination of publication bias and inappropriate selection of statistical and experimental designs. Second, there is the frequent failure to translate results in non-human animals to parallel results in humans in the clinic. This limitation can only be overcome by developing new behavioral tests for non-human animals that have predictive, construct, and etiological validity. Here, we present these translational difficulties as a "grand challenge" to researchers from comparative cognition, who are well positioned to provide new methods for testing behavior and cognition in non-human animals. These new experimental protocols will need to be both statistically robust and target behavioral and cognitive processes that allow for better connection with human CNS disorders. Our hope is that this downturn in industrial research may represent an opportunity to develop new protocols that will re-kindle the search for more effective and safer drugs for CNS disorders. Copyright © 2011 Elsevier B.V. All rights reserved.

  8. Stem cells in drug discovery, tissue engineering, and regenerative medicine: emerging opportunities and challenges.

    Science.gov (United States)

    Nirmalanandhan, Victor Sanjit; Sittampalam, G Sitta

    2009-08-01

    Stem cells, irrespective of their origin, have emerged as valuable reagents or tools in human health in the past 2 decades. Initially, a research tool to study fundamental aspects of developmental biology is now the central focus of generating transgenic animals, drug discovery, and regenerative medicine to address degenerative diseases of multiple organ systems. This is because stem cells are pluripotent or multipotent cells that can recapitulate developmental paths to repair damaged tissues. However, it is becoming clear that stem cell therapy alone may not be adequate to reverse tissue and organ damage in degenerative diseases. Existing small-molecule drugs and biologicals may be needed as "molecular adjuvants" or enhancers of stem cells administered in therapy or adult stem cells in the diseased tissues. Hence, a combination of stem cell-based, high-throughput screening and 3D tissue engineering approaches is necessary to advance the next wave of tools in preclinical drug discovery. In this review, the authors have attempted to provide a basic account of various stem cells types, as well as their biology and signaling, in the context of research in regenerative medicine. An attempt is made to link stem cells as reagents, pharmacology, and tissue engineering as converging fields of research for the next decade.

  9. Fragment-based drug discovery using rational design.

    Science.gov (United States)

    Jhoti, H

    2007-01-01

    Fragment-based drug discovery (FBDD) is established as an alternative approach to high-throughput screening for generating novel small molecule drug candidates. In FBDD, relatively small libraries of low molecular weight compounds (or fragments) are screened using sensitive biophysical techniques to detect their binding to the target protein. A lower absolute affinity of binding is expected from fragments, compared to much higher molecular weight hits detected by high-throughput screening, due to their reduced size and complexity. Through the use of iterative cycles of medicinal chemistry, ideally guided by three-dimensional structural data, it is often then relatively straightforward to optimize these weak binding fragment hits into potent and selective lead compounds. As with most other lead discovery methods there are two key components of FBDD; the detection technology and the compound library. In this review I outline the two main approaches used for detecting the binding of low affinity fragments and also some of the key principles that are used to generate a fragment library. In addition, I describe an example of how FBDD has led to the generation of a drug candidate that is now being tested in clinical trials for the treatment of cancer.

  10. Fragment approaches in structure-based drug discovery

    International Nuclear Information System (INIS)

    Hubbard, Roderick E.

    2008-01-01

    Fragment-based methods are successfully generating novel and selective drug-like inhibitors of protein targets, with a number of groups reporting compounds entering clinical trials. This paper summarizes the key features of the approach as one of the tools in structure-guided drug discovery. There has been considerable interest recently in what is known as 'fragment-based lead discovery'. The novel feature of the approach is to begin with small low-affinity compounds. The main advantage is that a larger potential chemical diversity can be sampled with fewer compounds, which is particularly important for new target classes. The approach relies on careful design of the fragment library, a method that can detect binding of the fragment to the protein target, determination of the structure of the fragment bound to the target, and the conventional use of structural information to guide compound optimization. In this article the methods are reviewed, and experiences in fragment-based discovery of lead series of compounds against kinases such as PDK1 and ATPases such as Hsp90 are discussed. The examples illustrate some of the key benefits and issues of the approach and also provide anecdotal examples of the patterns seen in selectivity and the binding mode of fragments across different protein targets

  11. Fragment-Based Drug Discovery in the Bromodomain and Extra-Terminal Domain Family.

    Science.gov (United States)

    Radwan, Mostafa; Serya, Rabah

    2017-08-01

    Bromodomain and extra-terminal domain (BET) inhibition has emerged recently as a potential therapeutic target for the treatment of many human disorders such as atherosclerosis, inflammatory disorders, chronic obstructive pulmonary disease (COPD), some viral infections, and cancer. Since the discovery of the two potent inhibitors, I-BET762 and JQ1, different research groups have used different techniques to develop novel potent and selective inhibitors. In this review, we will be concerned with the trials that used fragment-based drug discovery (FBDD) approaches to discover or optimize BET inhibitors, also showing fragments that can be further optimized in future projects to reach novel potent BET inhibitors. © 2017 Deutsche Pharmazeutische Gesellschaft.

  12. The future of drug discovery: enabling technologies for enhancing lead characterization and profiling therapeutic potential.

    Science.gov (United States)

    Janero, David R

    2014-08-01

    Technology often serves as a handmaiden and catalyst of invention. The discovery of safe, effective medications depends critically upon experimental approaches capable of providing high-impact information on the biological effects of drug candidates early in the discovery pipeline. This information can enable reliable lead identification, pharmacological compound differentiation and successful translation of research output into clinically useful therapeutics. The shallow preclinical profiling of candidate compounds promulgates a minimalistic understanding of their biological effects and undermines the level of value creation necessary for finding quality leads worth moving forward within the development pipeline with efficiency and prognostic reliability sufficient to help remediate the current pharma-industry productivity drought. Three specific technologies discussed herein, in addition to experimental areas intimately associated with contemporary drug discovery, appear to hold particular promise for strengthening the preclinical valuation of drug candidates by deepening lead characterization. These are: i) hydrogen-deuterium exchange mass spectrometry for characterizing structural and ligand-interaction dynamics of disease-relevant proteins; ii) activity-based chemoproteomics for profiling the functional diversity of mammalian proteomes; and iii) nuclease-mediated precision gene editing for developing more translatable cellular and in vivo models of human diseases. When applied in an informed manner congruent with the clinical understanding of disease processes, technologies such as these that span levels of biological organization can serve as valuable enablers of drug discovery and potentially contribute to reducing the current, unacceptably high rates of compound clinical failure.

  13. Experiences in fragment-based drug discovery.

    Science.gov (United States)

    Murray, Christopher W; Verdonk, Marcel L; Rees, David C

    2012-05-01

    Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. Applications of Dynamic Clamp to Cardiac Arrhythmia Research: Role in Drug Target Discovery and Safety Pharmacology Testing

    Directory of Open Access Journals (Sweden)

    Francis A. Ortega

    2018-01-01

    Full Text Available Dynamic clamp, a hybrid-computational-experimental technique that has been used to elucidate ionic mechanisms underlying cardiac electrophysiology, is emerging as a promising tool in the discovery of potential anti-arrhythmic targets and in pharmacological safety testing. Through the injection of computationally simulated conductances into isolated cardiomyocytes in a real-time continuous loop, dynamic clamp has greatly expanded the capabilities of patch clamp outside traditional static voltage and current protocols. Recent applications include fine manipulation of injected artificial conductances to identify promising drug targets in the prevention of arrhythmia and the direct testing of model-based hypotheses. Furthermore, dynamic clamp has been used to enhance existing experimental models by addressing their intrinsic limitations, which increased predictive power in identifying pro-arrhythmic pharmacological compounds. Here, we review the recent advances of the dynamic clamp technique in cardiac electrophysiology with a focus on its future role in the development of safety testing and discovery of anti-arrhythmic drugs.

  15. New perspectives on innovative drug discovery: an overview.

    Science.gov (United States)

    Pan, Si Yuan; Pan, Shan; Yu, Zhi-Ling; Ma, Dik-Lung; Chen, Si-Bao; Fong, Wang-Fun; Han, Yi-Fan; Ko, Kam-Ming

    2010-01-01

    Despite advances in technology, drug discovery is still a lengthy, expensive, difficult, and inefficient process, with a low rate of success. Today, advances in biomedical science have brought about great strides in therapeutic interventions for a wide spectrum of diseases. The advent of biochemical techniques and cutting-edge bio/chemical technologies has made available a plethora of practical approaches to drug screening and design. In 2010, the total sales of the global pharmaceutical market will reach 600 billion US dollars and expand to over 975 billion dollars by 2013. The aim of this review is to summarize available information on contemporary approaches and strategies in the discovery of novel therapeutic agents, especially from the complementary and alternative medicines, including natural products and traditional remedies such as Chinese herbal medicine.

  16. Stem cell technology for drug discovery and development.

    Science.gov (United States)

    Hook, Lilian A

    2012-04-01

    Stem cells have enormous potential to revolutionise the drug discovery process at all stages, from target identification through to toxicology studies. Their ability to generate physiologically relevant cells in limitless supply makes them an attractive alternative to currently used recombinant cell lines or primary cells. However, realisation of the full potential of stem cells is currently hampered by the difficulty in routinely directing stem cell differentiation to reproducibly and cost effectively generate pure populations of specific cell types. In this article we discuss how stem cells have already been used in the drug discovery process and how novel technologies, particularly in relation to stem cell differentiation, can be applied to attain widespread adoption of stem cell technology by the pharmaceutical industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

    Science.gov (United States)

    Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

    2017-11-01

    Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Open Innovation Drug Discovery (OIDD): a potential path to novel therapeutic chemical space.

    Science.gov (United States)

    Alvim-Gaston, Maria; Grese, Timothy; Mahoui, Abdelaziz; Palkowitz, Alan D; Pineiro-Nunez, Marta; Watson, Ian

    2014-01-01

    The continued development of computational and synthetic methods has enabled the enumeration or preparation of a nearly endless universe of chemical structures. Nevertheless, the ability of this chemical universe to deliver small molecules that can both modulate biological targets and have drug-like physicochemical properties continues to be a topic of interest to the pharmaceutical industry and academic researchers alike. The chemical space described by public, commercial, in-house and virtual compound collections has been interrogated by multiple approaches including biochemical, cellular and virtual screening, diversity analysis, and in-silico profiling. However, current drugs and known chemical probes derived from these efforts are contained within a remarkably small volume of the predicted chemical space. Access to more diverse classes of chemical scaffolds that maintain the properties relevant for drug discovery is certainly needed to meet the increasing demands for pharmaceutical innovation. The Lilly Open Innovation Drug Discovery platform (OIDD) was designed to tackle barriers to innovation through the identification of novel molecules active in relevant disease biology models. In this article we will discuss several computational approaches towards describing novel, biologically active, drug-like chemical space and illustrate how the OIDD program may facilitate access to previously untapped molecules that may aid in the search for innovative pharmaceuticals.

  19. Drug discovery in an academic setting: playing to the strengths.

    Science.gov (United States)

    Huryn, Donna M

    2013-03-14

    Drug discovery and medicinal chemistry initiatives in academia provide an opportunity to create a unique environment that is distinct from the traditional industrial model. Two characteristics of a university setting that are not usually associated with pharma are the ability to pursue high-risk projects and a depth of expertise, infrastructure, and capabilities in focused areas. Encouraging, supporting, and fostering drug discovery efforts that take advantage of these and other distinguishing characteristics of an academic setting can lead to novel and innovative therapies that might not be discovered otherwise.

  20. Designing an intuitive web application for drug discovery scientists.

    Science.gov (United States)

    Karamanis, Nikiforos; Pignatelli, Miguel; Carvalho-Silva, Denise; Rowland, Francis; Cham, Jennifer A; Dunham, Ian

    2018-01-11

    We discuss how we designed the Open Targets Platform (www.targetvalidation.org), an intuitive application for bench scientists working in early drug discovery. To meet the needs of our users, we applied lean user experience (UX) design methods: we started engaging with users very early and carried out research, design and evaluation activities within an iterative development process. We also emphasize the collaborative nature of applying lean UX design, which we believe is a foundation for success in this and many other scientific projects. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Financing drug discovery for orphan diseases.

    Science.gov (United States)

    Fagnan, David E; Gromatzky, Austin A; Stein, Roger M; Fernandez, Jose-Maria; Lo, Andrew W

    2014-05-01

    Recently proposed 'megafund' financing methods for funding translational medicine and drug development require billions of dollars in capital per megafund to de-risk the drug discovery process enough to issue long-term bonds. Here, we demonstrate that the same financing methods can be applied to orphan drug development but, because of the unique nature of orphan diseases and therapeutics (lower development costs, faster FDA approval times, lower failure rates and lower correlation of failures among disease targets) the amount of capital needed to de-risk such portfolios is much lower in this field. Numerical simulations suggest that an orphan disease megafund of only US$575 million can yield double-digit expected rates of return with only 10-20 projects in the portfolio. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era.

    Science.gov (United States)

    Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean

    2018-03-30

    Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.

  3. Chimeric mice with humanized liver: Application in drug metabolism and pharmacokinetics studies for drug discovery.

    Science.gov (United States)

    Naritomi, Yoichi; Sanoh, Seigo; Ohta, Shigeru

    2018-02-01

    Predicting human drug metabolism and pharmacokinetics (PK) is key to drug discovery. In particular, it is important to predict human PK, metabolite profiles and drug-drug interactions (DDIs). Various methods have been used for such predictions, including in vitro metabolic studies using human biological samples, such as hepatic microsomes and hepatocytes, and in vivo studies using experimental animals. However, prediction studies using these methods are often inconclusive due to discrepancies between in vitro and in vivo results, and interspecies differences in drug metabolism. Further, the prediction methods have changed from qualitative to quantitative to solve these issues. Chimeric mice with humanized liver have been developed, in which mouse liver cells are mostly replaced with human hepatocytes. Since human drug metabolizing enzymes are expressed in the liver of these mice, they are regarded as suitable models for mimicking the drug metabolism and PK observed in humans; therefore, these mice are useful for predicting human drug metabolism and PK. In this review, we discuss the current state, issues, and future directions of predicting human drug metabolism and PK using chimeric mice with humanized liver in drug discovery. Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

  4. Open-access public-private partnerships to enable drug discovery--new approaches.

    Science.gov (United States)

    Müller, Susanne; Weigelt, Johan

    2010-03-01

    The productivity of the pharmaceutical industry, as assessed by the number of NMEs produced per US dollar spent in R&D, has been in steady decline during the past 40 years. This decline in productivity not only poses a significant challenge to the pharmaceutical industry, but also to society because of the importance of developing drugs for the treatment of unmet medical needs. The major challenge in progressing a new drug to the market is the successful completion of clinical trials. However, the failure rate of drugs entering trials has not decreased, despite various technological and scientific breakthroughs in recent decades, and despite intense target validation efforts. This lack of success suggests limitations in the fundamental understanding of target biology and human pharmacology. One contributing factor may be the traditional secrecy of the pharmaceutical sector, a characteristic that does not promote scientific discovery in an optimal manner. Access to broader knowledge relating to target biology and human pharmacology is difficult to obtain because interactions between researchers in industry and academia are typically restricted to closed collaborations in which the knowledge gained is confidential.However, open-access collaborative partnerships are gaining momentum in industry, and are also favored by funding agencies. Such open-access collaborations may be a powerful alternative to closed collaborations; the sharing of early-stage research data is expected to enable scientific discovery by engaging a broader section of the scientific community in the exploration of new findings. Potentially, the sharing of data could contribute to an increased understanding of biological processes and a decrease in the attrition of clinical programs.

  5. ACFIS: a web server for fragment-based drug discovery

    Science.gov (United States)

    Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

    2016-01-01

    In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown ‘chemical space’ to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for ‘chemical space’, which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. PMID:27150808

  6. Use of machine learning approaches for novel drug discovery.

    Science.gov (United States)

    Lima, Angélica Nakagawa; Philot, Eric Allison; Trossini, Gustavo Henrique Goulart; Scott, Luis Paulo Barbour; Maltarollo, Vinícius Gonçalves; Honorio, Kathia Maria

    2016-01-01

    The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds. This article presents an overview on some applications of ML techniques in drug design. These techniques can be employed in ligand-based drug design (LBDD) and structure-based drug design (SBDD) studies, such as similarity searches, construction of classification and/or prediction models of biological activity, prediction of secondary structures and binding sites docking and virtual screening. Successful cases have been reported in the literature, demonstrating the efficiency of ML techniques combined with traditional approaches to study medicinal chemistry problems. Some ML techniques used in drug design are: support vector machine, random forest, decision trees and artificial neural networks. Currently, an important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.

  7. Preparative Scale Resolution of Enantiomers Enables Accelerated Drug Discovery and Development

    Directory of Open Access Journals (Sweden)

    Hanna Leek

    2017-01-01

    Full Text Available The provision of pure enantiomers is of increasing importance not only for the pharmaceutical industry but also for agro-chemistry and biotechnology. In drug discovery and development, the enantiomers of a chiral drug depict unique chemical and pharmacological behaviors in a chiral environment, such as the human body, in which the stereochemistry of the chiral drugs determines their pharmacokinetic, pharmacodynamic and toxicological properties. We present a number of challenging case studies of up-to-kilogram separations of racemic or enriched isomer mixtures using preparative liquid chromatography and super critical fluid chromatography to generate individual enantiomers that have enabled the development of new candidate drugs within AstraZeneca. The combination of chromatography and racemization as well as strategies on when to apply preparative chiral chromatography of enantiomers in a multi-step synthesis of a drug compound can further facilitate accelerated drug discovery and the early clinical evaluation of the drug candidates.

  8. Computer-Aided Drug Design Applied to Marine Drug Discovery: Meridianins as Alzheimer's Disease Therapeutic Agents.

    Science.gov (United States)

    Llorach-Pares, Laura; Nonell-Canals, Alfons; Sanchez-Martinez, Melchor; Avila, Conxita

    2017-11-27

    Computer-aided drug discovery/design (CADD) techniques allow the identification of natural products that are capable of modulating protein functions in pathogenesis-related pathways, constituting one of the most promising lines followed in drug discovery. In this paper, we computationally evaluated and reported the inhibitory activity found in meridianins A-G, a group of marine indole alkaloids isolated from the marine tunicate Aplidium , against various protein kinases involved in Alzheimer's disease (AD), a neurodegenerative pathology characterized by the presence of neurofibrillary tangles (NFT). Balance splitting between tau kinase and phosphate activities caused tau hyperphosphorylation and, thereby, its aggregation and NTF formation. Inhibition of specific kinases involved in its phosphorylation pathway could be one of the key strategies to reverse tau hyperphosphorylation and would represent an approach to develop drugs to palliate AD symptoms. Meridianins bind to the adenosine triphosphate (ATP) binding site of certain protein kinases, acting as ATP competitive inhibitors. These compounds show very promising scaffolds to design new drugs against AD, which could act over tau protein kinases Glycogen synthetase kinase-3 Beta (GSK3β) and Casein kinase 1 delta (CK1δ, CK1D or KC1D), and dual specificity kinases as dual specificity tyrosine phosphorylation regulated kinase 1 (DYRK1A) and cdc2-like kinases (CLK1). This work is aimed to highlight the role of CADD techniques in marine drug discovery and to provide precise information regarding the binding mode and strength of meridianins against several protein kinases that could help in the future development of anti-AD drugs.

  9. Insights into Integrated Lead Generation and Target Identification in Malaria and Tuberculosis Drug Discovery.

    Science.gov (United States)

    Okombo, John; Chibale, Kelly

    2017-07-18

    New, safe and effective drugs are urgently needed to treat and control malaria and tuberculosis, which affect millions of people annually. However, financial return on investment in the poor settings where these diseases are mostly prevalent is very minimal to support market-driven drug discovery and development. Moreover, the imminent loss of therapeutic lifespan of existing therapies due to evolution and spread of drug resistance further compounds the urgency to identify novel effective drugs. However, the advent of new public-private partnerships focused on tropical diseases and the recent release of large data sets by pharmaceutical companies on antimalarial and antituberculosis compounds derived from phenotypic whole cell high throughput screening have spurred renewed interest and opened new frontiers in malaria and tuberculosis drug discovery. This Account recaps the existing challenges facing antimalarial and antituberculosis drug discovery, including limitations associated with experimental animal models as well as biological complexities intrinsic to the causative pathogens. We enlist various highlights from a body of work within our research group aimed at identifying and characterizing new chemical leads, and navigating these challenges to contribute toward the global drug discovery and development pipeline in malaria and tuberculosis. We describe a catalogue of in-house efforts toward deriving safe and efficacious preclinical drug development candidates via cell-based medicinal chemistry optimization of phenotypic whole-cell medium and high throughput screening hits sourced from various small molecule chemical libraries. We also provide an appraisal of target-based screening, as invoked in our laboratory for mechanistic evaluation of the hits generated, with particular focus on the enzymes within the de novo pyrimidine biosynthetic and hemoglobin degradation pathways, the latter constituting a heme detoxification process and an associated cysteine

  10. An overview of aldehyde oxidase: an enzyme of emerging importance in novel drug discovery.

    Science.gov (United States)

    Rashidi, Mohammad-Reza; Soltani, Somaieh

    2017-03-01

    Given the rising trend in medicinal chemistry strategy to reduce cytochrome P450-dependent metabolism, aldehyde oxidase (AOX) has recently gained increased attention in drug discovery programs and the number of drug candidates that are metabolized by AOX is steadily growing. Areas covered: Despite the emerging importance of AOX in drug discovery, there are certain major recognized problems associated with AOX-mediated metabolism of drugs. Intra- and inter-species variations in AOX activity, the lack of reliable and predictive animal models using the common experimental animals, and failure in the predictions of in vivo metabolic activity of AOX using traditional in vitro methods are among these issues that are covered in this article. A comprehensive review of computational human AOX (hAOX) related studies are also provided. Expert opinion: Following the recent progress in the stem cell field, the authors recommend the application of organoids technology as an effective tool to solve the fundamental problems associated with the evaluation of AOX in drug discovery. The recent success in resolving the hAOX crystal structure can too be another valuable data source for the study of AOX-catalyzed metabolism of new drug candidates, using computer-aided drug discovery methods.

  11. Providing data science support for systems pharmacology and its implications to drug discovery.

    Science.gov (United States)

    Hart, Thomas; Xie, Lei

    2016-01-01

    The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations.

  12. Outsourcing drug discovery to India and China: from surviving to thriving.

    Science.gov (United States)

    Subramaniam, Swaminathan; Dugar, Sundeep

    2012-10-01

    Global pharmaceutical companies face an increasingly harsh environment for their primary business of selling medicines. They have to contend with a spiraling decline in the productivity of their R&D programs that is guaranteed to severely diminish their growth prospects. Outsourcing of drug discovery activities to low-cost locations is a growing response to this crisis. However, the upsides to outsourcing are capped by the failure of global pharmaceutical companies to take advantage of the full range of possibilities that this model provides. Companies that radically rethink and transform the way they conduct R&D, such as seeking the benefits of low-cost locations in India and China will be the ones that thrive in this environment. In this article we present our views on how the outsourcing model in drug discovery should go beyond increasing the efficiency of existing drug discovery processes to a fundamental rethink and re-engineering of these processes. Copyright © 2012. Published by Elsevier Ltd.

  13. Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery.

    Science.gov (United States)

    Hall, David R; Kozakov, Dima; Whitty, Adrian; Vajda, Sandor

    2015-11-01

    Analysis of binding energy hot spots at protein surfaces can provide crucial insights into the prospects for successful application of fragment-based drug discovery (FBDD), and whether a fragment hit can be advanced into a high-affinity, drug-like ligand. The key factor is the strength of the top ranking hot spot, and how well a given fragment complements it. We show that published data are sufficient to provide a sophisticated and quantitative understanding of how hot spots derive from a protein 3D structure, and how their strength, number, and spatial arrangement govern the potential for a surface site to bind to fragment-sized and larger ligands. This improved understanding provides important guidance for the effective application of FBDD in drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. G-protein-coupled receptors: new approaches to maximise the impact of GPCRS in drug discovery.

    Science.gov (United States)

    Davey, John

    2004-04-01

    IBC's Drug Discovery Technology Series is a group of conferences highlighting technological advances and applications in niche areas of the drug discovery pipeline. This 2-day meeting focused on G-protein-coupled receptors (GPCRs), probably the most important and certainly the most valuable class of targets for drug discovery. The meeting was chaired by J Beesley (Vice President, European Business Development for LifeSpan Biosciences, Seattle, USA) and included 17 presentations on various aspects of GPCR activity, drug screens and therapeutic analyses. Keynote Addresses covered two of the emerging areas in GPCR regulation; receptor dimerisation (G Milligan, Professor of Molecular Pharmacology and Biochemistry, University of Glasgow, UK) and proteins that interact with GPCRs (J Bockaert, Laboratory of Functional Genomics, CNRS Montpellier, France). A third Keynote Address from W Thomsen (Director of GPCR Drug Screening, Arena Pharmaceuticals, USA) discussed Arena's general approach to drug discovery and illustrated this with reference to the development of an agonist with potential efficacy in Type II diabetes.

  15. The use of web ontology languages and other semantic web tools in drug discovery.

    Science.gov (United States)

    Chen, Huajun; Xie, Guotong

    2010-05-01

    To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

  16. Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities.

    Science.gov (United States)

    Huang, Boshi; Kang, Dongwei; Zhan, Peng; Liu, Xinyong

    2015-12-01

    The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery. In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress. Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

  17. The Drug Discovery and Development Industry in India-Two Decades of Proprietary Small-Molecule R&D.

    Science.gov (United States)

    Differding, Edmond

    2017-06-07

    This review provides a comprehensive survey of proprietary drug discovery and development efforts performed by Indian companies between 1994 and mid-2016. It is based on the identification and detailed analysis of pharmaceutical, biotechnology, and contract research companies active in proprietary new chemical entity (NCE) research and development (R&D) in India. Information on preclinical and clinical development compounds was collected by company, therapeutic indication, mode of action, target class, and development status. The analysis focuses on the overall pipeline and its evolution over two decades, contributions by type of company, therapeutic focus, attrition rates, and contribution to Western pharmaceutical pipelines through licensing agreements. This comprehensive analysis is the first of its kind, and, in our view, represents a significant contribution to the understanding of the current state of the drug discovery and development industry in India. © 2017 The Author. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  18. The mass-action law based algorithm for cost-effective approach for cancer drug discovery and development.

    Science.gov (United States)

    Chou, Ting-Chao

    2011-01-01

    The mass-action law based system analysis via mathematical induction and deduction lead to the generalized theory and algorithm that allows computerized simulation of dose-effect dynamics with small size experiments using a small number of data points in vitro, in animals, and in humans. The median-effect equation of the mass-action law deduced from over 300 mechanism specific-equations has been shown to be the unified theory that serves as the common-link for complicated biomedical systems. After using the median-effect principle as the common denominator, its applications are mechanism-independent, drug unit-independent, and dynamic order-independent; and can be used generally for single drug analysis or for multiple drug combinations in constant-ratio or non-constant ratios. Since the "median" is the common link and universal reference point in biological systems, these general enabling lead to computerized quantitative bio-informatics for econo-green bio-research in broad disciplines. Specific applications of the theory, especially relevant to drug discovery, drug combination, and clinical trials, have been cited or illustrated in terms of algorithms, experimental design and computerized simulation for data analysis. Lessons learned from cancer research during the past fifty years provide a valuable opportunity to reflect, and to improve the conventional divergent approach and to introduce a new convergent avenue, based on the mass-action law principle, for the efficient cancer drug discovery and the low-cost drug development.

  19. An integrated dataset for in silico drug discovery

    Directory of Open Access Journals (Sweden)

    Cockell Simon J

    2010-12-01

    Full Text Available Drug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound. Systematic approaches to drug repositioning are needed to increase throughput and find candidates more reliably. Here we address this need with an integrated systems biology dataset, developed using the Ondex data integration platform, for the in silico discovery of new drug repositioning candidates. We demonstrate that the information in this dataset allows known repositioning examples to be discovered. We also propose a means of automating the search for new treatment indications of existing compounds.

  20. BPS Pharmacology 2014 - Drug Discovery Pathways symposium Report

    OpenAIRE

    Marsh, Andrew

    2015-01-01

    Report on BPS Pharmacology 2014, BPS Industry Committe and Learned Societies Drug Discovery Pathways Group symposium: "Realizing the potential of new approaches to target identification and validation" by Dr Andrew Marsh Associate Professor Department of Chemistry University of Warwick go.warwick.ac.uk/marshgroup Twitter @marshgroup

  1. Stem cells: a model for screening, discovery and development of drugs.

    Science.gov (United States)

    Kitambi, Satish Srinivas; Chandrasekar, Gayathri

    2011-01-01

    The identification of normal and cancerous stem cells and the recent advances made in isolation and culture of stem cells have rapidly gained attention in the field of drug discovery and regenerative medicine. The prospect of performing screens aimed at proliferation, directed differentiation, and toxicity and efficacy studies using stem cells offers a reliable platform for the drug discovery process. Advances made in the generation of induced pluripotent stem cells from normal or diseased tissue serves as a platform to perform drug screens aimed at developing cell-based therapies against conditions like Parkinson's disease and diabetes. This review discusses the application of stem cells and cancer stem cells in drug screening and their role in complementing, reducing, and replacing animal testing. In addition to this, target identification and major advances in the field of personalized medicine using induced pluripotent cells are also discussed.

  2. DenguePredict: An Integrated Drug Repositioning Approach towards Drug Discovery for Dengue.

    Science.gov (United States)

    Wang, QuanQiu; Xu, Rong

    2015-01-01

    Dengue is a viral disease of expanding global incidence without cures. Here we present a drug repositioning system (DenguePredict) leveraging upon a unique drug treatment database and vast amounts of disease- and drug-related data. We first constructed a large-scale genetic disease network with enriched dengue genetics data curated from biomedical literature. We applied a network-based ranking algorithm to find dengue-related diseases from the disease network. We then developed a novel algorithm to prioritize FDA-approved drugs from dengue-related diseases to treat dengue. When tested in a de-novo validation setting, DenguePredict found the only two drugs tested in clinical trials for treating dengue and ranked them highly: chloroquine ranked at top 0.96% and ivermectin at top 22.75%. We showed that drugs targeting immune systems and arachidonic acid metabolism-related apoptotic pathways might represent innovative drugs to treat dengue. In summary, DenguePredict, by combining comprehensive disease- and drug-related data and novel algorithms, may greatly facilitate drug discovery for dengue.

  3. Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery.

    Directory of Open Access Journals (Sweden)

    Albert H Gough

    Full Text Available One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

  4. Current status and future prospects for enabling chemistry technology in the drug discovery process.

    Science.gov (United States)

    Djuric, Stevan W; Hutchins, Charles W; Talaty, Nari N

    2016-01-01

    This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of "dangerous" reagents. Also featured are advances in the "computer-assisted drug design" area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.

  5. DrugQuest - a text mining workflow for drug association discovery.

    Science.gov (United States)

    Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Vizirianakis, Ioannis S; Iliopoulos, Ioannis

    2016-06-06

    Text mining and data integration methods are gaining ground in the field of health sciences due to the exponential growth of bio-medical literature and information stored in biological databases. While such methods mostly try to extract bioentity associations from PubMed, very few of them are dedicated in mining other types of repositories such as chemical databases. Herein, we apply a text mining approach on the DrugBank database in order to explore drug associations based on the DrugBank "Description", "Indication", "Pharmacodynamics" and "Mechanism of Action" text fields. We apply Name Entity Recognition (NER) techniques on these fields to identify chemicals, proteins, genes, pathways, diseases, and we utilize the TextQuest algorithm to find additional biologically significant words. Using a plethora of similarity and partitional clustering techniques, we group the DrugBank records based on their common terms and investigate possible scenarios why these records are clustered together. Different views such as clustered chemicals based on their textual information, tag clouds consisting of Significant Terms along with the terms that were used for clustering are delivered to the user through a user-friendly web interface. DrugQuest is a text mining tool for knowledge discovery: it is designed to cluster DrugBank records based on text attributes in order to find new associations between drugs. The service is freely available at http://bioinformatics.med.uoc.gr/drugquest .

  6. A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

    Science.gov (United States)

    Guerrero, Ginés D.; Imbernón, Baldomero; García, José M.

    2014-01-01

    Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor. PMID:25025055

  7. Contributions of computational chemistry and biophysical techniques to fragment-based drug discovery.

    Science.gov (United States)

    Gozalbes, Rafael; Carbajo, Rodrigo J; Pineda-Lucena, Antonio

    2010-01-01

    In the last decade, fragment-based drug discovery (FBDD) has evolved from a novel approach in the search of new hits to a valuable alternative to the high-throughput screening (HTS) campaigns of many pharmaceutical companies. The increasing relevance of FBDD in the drug discovery universe has been concomitant with an implementation of the biophysical techniques used for the detection of weak inhibitors, e.g. NMR, X-ray crystallography or surface plasmon resonance (SPR). At the same time, computational approaches have also been progressively incorporated into the FBDD process and nowadays several computational tools are available. These stretch from the filtering of huge chemical databases in order to build fragment-focused libraries comprising compounds with adequate physicochemical properties, to more evolved models based on different in silico methods such as docking, pharmacophore modelling, QSAR and virtual screening. In this paper we will review the parallel evolution and complementarities of biophysical techniques and computational methods, providing some representative examples of drug discovery success stories by using FBDD.

  8. Financing drug discovery via dynamic leverage.

    Science.gov (United States)

    Montazerhodjat, Vahid; Frishkopf, John J; Lo, Andrew W

    2016-03-01

    We extend the megafund concept for funding drug discovery to enable dynamic leverage in which the portfolio of candidate therapeutic assets is predominantly financed initially by equity, and debt is introduced gradually as assets mature and begin generating cash flows. Leverage is adjusted so as to maintain an approximately constant level of default risk throughout the life of the fund. Numerical simulations show that applying dynamic leverage to a small portfolio of orphan drug candidates can boost the return on equity almost twofold compared with securitization with a static capital structure. Dynamic leverage can also add significant value to comparable all-equity-financed portfolios, enhancing the return on equity without jeopardizing debt performance or increasing risk to equity investors. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.

    Science.gov (United States)

    Benson, Neil

    2015-08-01

    Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Current status and future prospects for enabling chemistry technology in the drug discovery process

    Science.gov (United States)

    Djuric, Stevan W.; Hutchins, Charles W.; Talaty, Nari N.

    2016-01-01

    This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of “dangerous” reagents. Also featured are advances in the “computer-assisted drug design” area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities. PMID:27781094

  11. Phenotypic and genomic comparison of Mycobacterium aurum and surrogate model species to Mycobacterium tuberculosis: implications for drug discovery.

    Science.gov (United States)

    Namouchi, Amine; Cimino, Mena; Favre-Rochex, Sandrine; Charles, Patricia; Gicquel, Brigitte

    2017-07-13

    Tuberculosis (TB) is caused by Mycobacterium tuberculosis and represents one of the major challenges facing drug discovery initiatives worldwide. The considerable rise in bacterial drug resistance in recent years has led to the need of new drugs and drug regimens. Model systems are regularly used to speed-up the drug discovery process and circumvent biosafety issues associated with manipulating M. tuberculosis. These include the use of strains such as Mycobacterium smegmatis and Mycobacterium marinum that can be handled in biosafety level 2 facilities, making high-throughput screening feasible. However, each of these model species have their own limitations. We report and describe the first complete genome sequence of Mycobacterium aurum ATCC23366, an environmental mycobacterium that can also grow in the gut of humans and animals as part of the microbiota. This species shows a comparable resistance profile to that of M. tuberculosis for several anti-TB drugs. The aims of this study were to (i) determine the drug resistance profile of a recently proposed model species, Mycobacterium aurum, strain ATCC23366, for anti-TB drug discovery as well as Mycobacterium smegmatis and Mycobacterium marinum (ii) sequence and annotate the complete genome sequence of this species obtained using Pacific Bioscience technology (iii) perform comparative genomics analyses of the various surrogate strains with M. tuberculosis (iv) discuss how the choice of the surrogate model used for drug screening can affect the drug discovery process. We describe the complete genome sequence of M. aurum, a surrogate model for anti-tuberculosis drug discovery. Most of the genes already reported to be associated with drug resistance are shared between all the surrogate strains and M. tuberculosis. We consider that M. aurum might be used in high-throughput screening for tuberculosis drug discovery. We also highly recommend the use of different model species during the drug discovery screening process.

  12. Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery.

    Science.gov (United States)

    Karthikeyan, Muthukumarasamy; Vyas, Renu

    2015-01-01

    Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.

  13. Freely Accessible Chemical Database Resources of Compounds for in Silico Drug Discovery.

    Science.gov (United States)

    Yang, JingFang; Wang, Di; Jia, Chenyang; Wang, Mengyao; Hao, GeFei; Yang, GuangFu

    2018-05-07

    In silico drug discovery has been proved to be a solidly established key component in early drug discovery. However, this task is hampered by the limitation of quantity and quality of compound databases for screening. In order to overcome these obstacles, freely accessible database resources of compounds have bloomed in recent years. Nevertheless, how to choose appropriate tools to treat these freely accessible databases are crucial. To the best of our knowledge, this is the first systematic review on this issue. The existed advantages and drawbacks of chemical databases were analyzed and summarized based on the collected six categories of freely accessible chemical databases from literature in this review. Suggestions on how and in which conditions the usage of these databases could be reasonable were provided. Tools and procedures for building 3D structure chemical libraries were also introduced. In this review, we described the freely accessible chemical database resources for in silico drug discovery. In particular, the chemical information for building chemical database appears as attractive resources for drug design to alleviate experimental pressure. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  14. Lessons from hot spot analysis for fragment-based drug discovery

    Science.gov (United States)

    Hall, David R.; Vajda, Sandor

    2015-01-01

    Analysis of binding energy hot spots at protein surfaces can provide crucial insights into the prospects for successful application of fragment-based drug discovery (FBDD), and whether a fragment hit can be advanced into a high affinity, druglike ligand. The key factor is the strength of the top ranking hot spot, and how well a given fragment complements it. We show that published data are sufficient to provide a sophisticated and quantitative understanding of how hot spots derive from protein three-dimensional structure, and how their strength, number and spatial arrangement govern the potential for a surface site to bind to fragment-sized and larger ligands. This improved understanding provides important guidance for the effective application of FBDD in drug discovery. PMID:26538314

  15. Stem cells: a model for screening, discovery and development of drugs

    Directory of Open Access Journals (Sweden)

    Kitambi SS

    2011-09-01

    Full Text Available Satish Srinivas Kitambi1, Gayathri Chandrasekar21Department of Medical Biochemistry and Biophysics; 2Department of Biosciences, Karolinska Institutet, Stockholm, SwedenAbstract: The identification of normal and cancerous stem cells and the recent advances made in isolation and culture of stem cells have rapidly gained attention in the field of drug discovery and regenerative medicine. The prospect of performing screens aimed at proliferation, directed differentiation, and toxicity and efficacy studies using stem cells offers a reliable platform for the drug discovery process. Advances made in the generation of induced pluripotent stem cells from normal or diseased tissue serves as a platform to perform drug screens aimed at developing cell-based therapies against conditions like Parkinson's disease and diabetes. This review discusses the application of stem cells and cancer stem cells in drug screening and their role in complementing, reducing, and replacing animal testing. In addition to this, target identification and major advances in the field of personalized medicine using induced pluripotent cells are also discussed.Keywords: therapeutics, stem cells, cancer stem cells, screening models, drug development, high throughput screening

  16. Institutional profile: the national Swedish academic drug discovery & development platform at SciLifeLab.

    Science.gov (United States)

    Arvidsson, Per I; Sandberg, Kristian; Sakariassen, Kjell S

    2017-06-01

    The Science for Life Laboratory Drug Discovery and Development Platform (SciLifeLab DDD) was established in Stockholm and Uppsala, Sweden, in 2014. It is one of ten platforms of the Swedish national SciLifeLab which support projects run by Swedish academic researchers with large-scale technologies for molecular biosciences with a focus on health and environment. SciLifeLab was created by the coordinated effort of four universities in Stockholm and Uppsala: Stockholm University, Karolinska Institutet, KTH Royal Institute of Technology and Uppsala University, and has recently expanded to other Swedish university locations. The primary goal of the SciLifeLab DDD is to support selected academic discovery and development research projects with tools and resources to discover novel lead therapeutics, either molecules or human antibodies. Intellectual property developed with the help of SciLifeLab DDD is wholly owned by the academic research group. The bulk of SciLifeLab DDD's research and service activities are funded from the Swedish state, with only consumables paid by the academic research group through individual grants.

  17. Lowering industry firewalls: pre-competitive informatics initiatives in drug discovery.

    Science.gov (United States)

    Barnes, Michael R; Harland, Lee; Foord, Steven M; Hall, Matthew D; Dix, Ian; Thomas, Scott; Williams-Jones, Bryn I; Brouwer, Cory R

    2009-09-01

    Pharmaceutical research and development is facing substantial challenges that have prompted the industry to shift funding from early- to late-stage projects. Among the effects is a major change in the attitude of many companies to their internal bioinformatics resources: the focus has moved from the vigorous pursuit of intellectual property towards exploration of pre-competitive cross-industry collaborations and engagement with the public domain. High-quality, open and accessible data are the foundation of pre-competitive research, and strong public-private partnerships have considerable potential to enhance public data resources, which would benefit everyone engaged in drug discovery. In this article, we discuss the background to these changes and propose new areas of collaboration in computational biology and chemistry between the public domain and the pharmaceutical industry.

  18. Test systems in drug discovery for hazard identification and risk assessment of human drug-induced liver injury.

    Science.gov (United States)

    Weaver, Richard J; Betts, Catherine; Blomme, Eric A G; Gerets, Helga H J; Gjervig Jensen, Klaus; Hewitt, Philip G; Juhila, Satu; Labbe, Gilles; Liguori, Michael J; Mesens, Natalie; Ogese, Monday O; Persson, Mikael; Snoeys, Jan; Stevens, James L; Walker, Tracy; Park, B Kevin

    2017-07-01

    The liver is an important target for drug-induced toxicities. Early detection of hepatotoxic drugs requires use of well-characterized test systems, yet current knowledge, gaps and limitations of tests employed remains an important issue for drug development. Areas Covered: The current state of the science, understanding and application of test systems in use for the detection of drug-induced cytotoxicity, mitochondrial toxicity, cholestasis and inflammation is summarized. The test systems highlighted herein cover mostly in vitro and some in vivo models and endpoint measurements used in the assessment of small molecule toxic liabilities. Opportunities for research efforts in areas necessitating the development of specific tests and improved mechanistic understanding are highlighted. Expert Opinion: Use of in vitro test systems for safety optimization will remain a core activity in drug discovery. Substantial inroads have been made with a number of assays established for human Drug-induced Liver Injury. There nevertheless remain significant gaps with a need for improved in vitro tools and novel tests to address specific mechanisms of human Drug-Induced Liver Injury. Progress in these areas will necessitate not only models fit for application, but also mechanistic understanding of how chemical insult on the liver occurs in order to identify translational and quantifiable readouts for decision-making.

  19. Drug discovery and the impact of the safe harbor provision of the Hatch- Waxman Act.

    Science.gov (United States)

    Goodson, Susanne H

    2010-01-01

    Many facets of drug discovery involve the use of patented materials and methods, subjecting the researcher to potential liability from infringement of the underlying patents. Enacted in 1984, the Hatch-Waxman Act established a “safe harbor” for activities that would otherwise constitute infringement of a patented invention, if those activities were “solely for uses reasonably related to the development and submission of information under a Federal law which regulates the manufacture, use, or sale of drugs or veterinary biological products”. This article examines the major court decisions interpreting the scope of the safe harbor and their application to various activities in drug development.

  20. Dynamic Docking: A Paradigm Shift in Computational Drug Discovery

    Directory of Open Access Journals (Sweden)

    Dario Gioia

    2017-11-01

    Full Text Available Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking. Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.

  1. A kernel for open source drug discovery in tropical diseases.

    Science.gov (United States)

    Ortí, Leticia; Carbajo, Rodrigo J; Pieper, Ursula; Eswar, Narayanan; Maurer, Stephen M; Rai, Arti K; Taylor, Ginger; Todd, Matthew H; Pineda-Lucena, Antonio; Sali, Andrej; Marti-Renom, Marc A

    2009-01-01

    Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such "kernels". HERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases.

  2. OSIRIS, an entirely in-house developed drug discovery informatics system.

    Science.gov (United States)

    Sander, Thomas; Freyss, Joel; von Korff, Modest; Reich, Jacqueline Renée; Rufener, Christian

    2009-02-01

    We present OSIRIS, an entirely in-house developed drug discovery informatics system. Its components cover all information handling aspects from compound synthesis via biological testing to preclinical development. Its design principles are platform and vendor independence, a consistent look and feel, and complete coverage of the drug discovery process by custom tailored applications. These include electronic laboratory notebook applications for biology and chemistry, tools for high-throughput and secondary screening evaluation, chemistry-aware data visualization, physicochemical property prediction, 3D-pharmacophore comparisons, interactive modeling, computing grid based ligand-protein docking, and more. Most applications are developed in Java and are built on top of a Java library layer that provides reusable cheminformatics functionality and GUI components such as chemical editors, structure canonicalization, substructure search, combinatorial enumeration, enhanced stereo perception, force field minimization, and conformation generation.

  3. Designing multi-targeted agents: An emerging anticancer drug discovery paradigm.

    Science.gov (United States)

    Fu, Rong-Geng; Sun, Yuan; Sheng, Wen-Bing; Liao, Duan-Fang

    2017-08-18

    The dominant paradigm in drug discovery is to design ligands with maximum selectivity to act on individual drug targets. With the target-based approach, many new chemical entities have been discovered, developed, and further approved as drugs. However, there are a large number of complex diseases such as cancer that cannot be effectively treated or cured only with one medicine to modulate the biological function of a single target. As simultaneous intervention of two (or multiple) cancer progression relevant targets has shown improved therapeutic efficacy, the innovation of multi-targeted drugs has become a promising and prevailing research topic and numerous multi-targeted anticancer agents are currently at various developmental stages. However, most multi-pharmacophore scaffolds are usually discovered by serendipity or screening, while rational design by combining existing pharmacophore scaffolds remains an enormous challenge. In this review, four types of multi-pharmacophore modes are discussed, and the examples from literature will be used to introduce attractive lead compounds with the capability of simultaneously interfering with different enzyme or signaling pathway of cancer progression, which will reveal the trends and insights to help the design of the next generation multi-targeted anticancer agents. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  4. Therapeutics discovery: From bench to first in-human trials.

    Science.gov (United States)

    Al-Hujaily, Ensaf M; Khatlani, Tanvir; Alehaideb, Zeyad; Ali, Rizwan; Almuzaini, Bader; Alrfaei, Bahauddeen M; Iqbal, Jahangir; Islam, Imadul; Malik, Shuja; Marwani, Bader A; Massadeh, Salam; Nehdi, Atef; Alsomaie, Barrak; Debasi, Bader; Bushnak, Ibraheem; Noibi, Saeed; Hussain, Syed; Wajid, Wahid Abdul; Armand, Jean-Pierre; Gul, Sheraz; Oyarzabal, Julen; Rais, Rana; Bountra, Chas; Alaskar, Ahmed; Knawy, Bander Al; Boudjelal, Mohamed

    2018-03-01

    The 'Therapeutics discovery: From bench to first in-human trials' conference, held at the King Abdullah International Medical Research Center (KAIMRC), Ministry of National Guard Health Affairs (MNGHA), Kingdom of Saudi Arabia (KSA) from October 10-12, 2017, provided a unique opportunity for experts worldwide to discuss advances in drug discovery and development, focusing on phase I clinical trials. It was the first event of its kind to be hosted at the new research center, which was constructed to boost drug discovery and development in the KSA in collaboration with institutions, such as the Academic Drug Discovery Consortium in the United States of America (USA), Structural Genomics Consortium of the University of Oxford in the United Kingdom (UK), and Institute of Materia Medica of the Chinese Academy of Medical Sciences in China. The program was divided into two parts. A pre-symposium day took place on October 10, during which courses were conducted on clinical trials, preclinical drug discovery, molecular biology and nanofiber research. The attendees had the opportunity for one-to-one meetings with international experts to exchange information and foster collaborations. In the second part of the conference, which took place on October 11 and 12, the clinical trials pipeline, design and recruitment of volunteers, and economic impact of clinical trials were discussed. The Saudi Food and Drug Administration presented the regulations governing clinical trials in the KSA. The process of preclinical drug discovery from small molecules, cellular and immunologic therapies, and approaches to identifying new targets were also presented. The recommendation of the conference was that researchers in the KSA must invest more fund, talents and infrastructure to lead the region in phase I clinical trials and preclinical drug discovery. Diseases affecting the local population, such as Middle East Respiratory Syndrome and resistant bacterial infections, represent the optimal

  5. Medicinal chemistry in drug discovery in big pharma: past, present and future.

    Science.gov (United States)

    Campbell, Ian B; Macdonald, Simon J F; Procopiou, Panayiotis A

    2018-02-01

    The changes in synthetic and medicinal chemistry and related drug discovery science as practiced in big pharma over the past few decades are described. These have been predominantly driven by wider changes in society namely the computer, internet and globalisation. Thoughts about the future of medicinal chemistry are also discussed including sharing the risks and costs of drug discovery and the future of outsourcing. The continuing impact of access to substantial computing power and big data, the use of algorithms in data analysis and drug design are also presented. The next generation of medicinal chemists will communicate in ways that reflect social media and the results of constantly being connected to each other and data. Copyright © 2017. Published by Elsevier Ltd.

  6. FLIPR assays of intracellular calcium in GPCR drug discovery

    DEFF Research Database (Denmark)

    Hansen, Kasper Bø; Bräuner-Osborne, Hans

    2009-01-01

    Fluorescent dyes sensitive to changes in intracellular calcium have become increasingly popular in G protein-coupled receptor (GPCR) drug discovery for several reasons. First of all, the assays using the dyes are easy to perform and are of low cost compared to other assays. Second, most non...

  7. Bioactive secondary metabolites from marine microbes for drug discovery.

    Science.gov (United States)

    Nikapitiya, Chamilani

    2012-01-01

    The isolation and extraction of novel bioactive secondary metabolites from marine microorganisms have a biomedical potential for future drug discovery as the oceans cover 70% of the planet's surface and life on earth originates from sea. Wide range of novel bioactive secondary metabolites exhibiting pharmacodynamic properties has been isolated from marine microorganisms and many to be discovered. The compounds isolated from marine organisms (macro and micro) are important in their natural form and also as templates for synthetic modifications for the treatments for variety of deadly to minor diseases. Many technical issues are yet to overcome before wide-scale bioprospecting of marine microorganisms becomes a reality. This chapter focuses on some novel secondary metabolites having antitumor, antivirus, enzyme inhibitor, and other bioactive properties identified and isolated from marine microorganisms including bacteria, actinomycetes, fungi, and cyanobacteria, which could serve as potentials for drug discovery after their clinical trials. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. SWEETLEAD: an in silico database of approved drugs, regulated chemicals, and herbal isolates for computer-aided drug discovery.

    Directory of Open Access Journals (Sweden)

    Paul A Novick

    Full Text Available In the face of drastically rising drug discovery costs, strategies promising to reduce development timelines and expenditures are being pursued. Computer-aided virtual screening and repurposing approved drugs are two such strategies that have shown recent success. Herein, we report the creation of a highly-curated in silico database of chemical structures representing approved drugs, chemical isolates from traditional medicinal herbs, and regulated chemicals, termed the SWEETLEAD database. The motivation for SWEETLEAD stems from the observance of conflicting information in publicly available chemical databases and the lack of a highly curated database of chemical structures for the globally approved drugs. A consensus building scheme surveying information from several publicly accessible databases was employed to identify the correct structure for each chemical. Resulting structures are filtered for the active pharmaceutical ingredient, standardized, and differing formulations of the same drug were combined in the final database. The publically available release of SWEETLEAD (https://simtk.org/home/sweetlead provides an important tool to enable the successful completion of computer-aided repurposing and drug discovery campaigns.

  9. Drug Discovery Gets a Boost from Data Science.

    Science.gov (United States)

    Amaro, Rommie E

    2016-08-02

    In this issue of Structure, Schiebel et al. (2016) describe a workflow-driven approach to high-throughput X-ray crystallographic fragment screening and refinement. In doing so, they extend the applicability of X-ray crystallography as a primary fragment-screening tool and show how data science techniques can favorably impact drug discovery efforts. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Competitive intelligence and patent analysis in drug discovery.

    Science.gov (United States)

    Grandjean, Nicolas; Charpiot, Brigitte; Pena, Carlos Andres; Peitsch, Manuel C

    2005-01-01

    Patents are a major source of information in drug discovery and, when properly processed and analyzed, can yield a wealth of information on competitors activities, R&D trends, emerging fields, collaborations, among others. This review discusses the current state-of-the-art in textual data analysis and exploration methods as applied to patent analysis.: © 2005 Elsevier Ltd . All rights reserved.

  11. A high content screening assay to predict human drug-induced liver injury during drug discovery.

    Science.gov (United States)

    Persson, Mikael; Løye, Anni F; Mow, Tomas; Hornberg, Jorrit J

    2013-01-01

    Adverse drug reactions are a major cause for failures of drug development programs, drug withdrawals and use restrictions. Early hazard identification and diligent risk avoidance strategies are therefore essential. For drug-induced liver injury (DILI), this is difficult using conventional safety testing. To reduce the risk for DILI, drug candidates with a high risk need to be identified and deselected. And, to produce drug candidates without that risk associated, risk factors need to be assessed early during drug discovery, such that lead series can be optimized on safety parameters. This requires methods that allow for medium-to-high throughput compound profiling and that generate quantitative results suitable to establish structure-activity-relationships during lead optimization programs. We present the validation of such a method, a novel high content screening assay based on six parameters (nuclei counts, nuclear area, plasma membrane integrity, lysosomal activity, mitochondrial membrane potential (MMP), and mitochondrial area) using ~100 drugs of which the clinical hepatotoxicity profile is known. We find that a 100-fold TI between the lowest toxic concentration and the therapeutic Cmax is optimal to classify compounds as hepatotoxic or non-hepatotoxic, based on the individual parameters. Most parameters have ~50% sensitivity and ~90% specificity. Drugs hitting ≥2 parameters at a concentration below 100-fold their Cmax are typically hepatotoxic, whereas non-hepatotoxic drugs typically hit based on nuclei count, MMP and human Cmax, we identified an area without a single false positive, while maintaining 45% sensitivity. Hierarchical clustering using the multi-parametric dataset roughly separates toxic from non-toxic compounds. We employ the assay in discovery projects to prioritize novel compound series during hit-to-lead, to steer away from a DILI risk during lead optimization, for risk assessment towards candidate selection and to provide guidance of safe

  12. A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

    Directory of Open Access Journals (Sweden)

    Ginés D. Guerrero

    2014-01-01

    Full Text Available Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO. This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor.

  13. Advances in immobilized artificial membrane (IAM) chromatography for novel drug discovery.

    Science.gov (United States)

    Tsopelas, Fotios; Vallianatou, Theodosia; Tsantili-Kakoulidou, Anna

    2016-01-01

    The development of immobilized artificial membrane (IAM) chromatography has unfolded new perspectives for the use of chromatographic techniques in drug discovery, combining simulation of the environment of cell membranes with rapid measurements. The present review describes the characteristics of phosphatidylcholine-based stationary phases and analyses the molecular factors governing IAM retention in comparison to n-octanol-water and liposomes partitioning systems as well as to reversed phase chromatography. Other biomimetic stationary phases are also briefly discussed. The potential of IAM chromatography to model permeability through the main physiological barriers and drug membrane interactions is outlined. Further applications to calculate complex pharmacokinetic properties, related to tissue binding, and to screen drug candidates for phospholipidosis, as well as to estimate cell accumulation/retention are surveyed. The ambivalent nature of IAM chromatography, as a border case between passive diffusion and binding, defines its multiple potential applications. However, despite its successful performance in many permeability and drug-membrane interactions studies, IAM chromatography is still used as a supportive and not a stand-alone technique. Further studies looking at IAM chromatography in different biological processes are still required if this technique is to have a more focused and consistent application in drug discovery.

  14. Open innovation for phenotypic drug discovery: The PD2 assay panel.

    Science.gov (United States)

    Lee, Jonathan A; Chu, Shaoyou; Willard, Francis S; Cox, Karen L; Sells Galvin, Rachelle J; Peery, Robert B; Oliver, Sarah E; Oler, Jennifer; Meredith, Tamika D; Heidler, Steven A; Gough, Wendy H; Husain, Saba; Palkowitz, Alan D; Moxham, Christopher M

    2011-07-01

    Phenotypic lead generation strategies seek to identify compounds that modulate complex, physiologically relevant systems, an approach that is complementary to traditional, target-directed strategies. Unlike gene-specific assays, phenotypic assays interrogate multiple molecular targets and signaling pathways in a target "agnostic" fashion, which may reveal novel functions for well-studied proteins and discover new pathways of therapeutic value. Significantly, existing compound libraries may not have sufficient chemical diversity to fully leverage a phenotypic strategy. To address this issue, Eli Lilly and Company launched the Phenotypic Drug Discovery Initiative (PD(2)), a model of open innovation whereby external research groups can submit compounds for testing in a panel of Lilly phenotypic assays. This communication describes the statistical validation, operations, and initial screening results from the first PD(2) assay panel. Analysis of PD(2) submissions indicates that chemical diversity from open source collaborations complements internal sources. Screening results for the first 4691 compounds submitted to PD(2) have confirmed hit rates from 1.6% to 10%, with the majority of active compounds exhibiting acceptable potency and selectivity. Phenotypic lead generation strategies, in conjunction with novel chemical diversity obtained via open-source initiatives such as PD(2), may provide a means to identify compounds that modulate biology by novel mechanisms and expand the innovation potential of drug discovery.

  15. Pharmacokinetic properties and in silico ADME modeling in drug discovery.

    Science.gov (United States)

    Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D

    2013-03-01

    The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.

  16. How Phenotypic Screening Influenced Drug Discovery: Lessons from Five Years of Practice.

    Science.gov (United States)

    Haasen, Dorothea; Schopfer, Ulrich; Antczak, Christophe; Guy, Chantale; Fuchs, Florian; Selzer, Paul

    Since 2011, phenotypic screening has been a trend in the pharmaceutical industry as well as in academia. This renaissance was triggered by analyses that suggested that phenotypic screening is a superior strategy to discover first-in-class drugs. Despite these promises and considerable investments, pharmaceutical research organizations have encountered considerable challenges with the approach. Few success stories have emerged in the past 5 years and companies are questioning their investment in this area. In this contribution, we outline what we have learned about success factors and challenges of phenotypic screening. We then describe how our efforts in phenotypic screening have influenced our approach to drug discovery in general. We predict that concepts from phenotypic screening will be incorporated into target-based approaches and will thus remain influential beyond the current trend.

  17. Renaissance in Antibiotic Discovery: Some Novel Approaches for Finding Drugs to Treat Bad Bugs.

    Science.gov (United States)

    Gadakh, Bharat; Van Aerschot, Arthur

    2015-01-01

    With the alarming resistance to currently used antibiotics, there is a serious worldwide threat to public health. Therefore, there is an urgent need to search for new antibiotics or new cellular targets which are essential for survival of the pathogens. However, during the past 50 years, only two new classes of antibiotics (oxazolidinone and lipopeptides) have reached the clinic. This suggests that the success rate in discovering new/novel antibiotics using conventional approaches is limited and that we must reconsider our antibiotic discovery approaches. While many new strategies are being pursued lately, this review primarily focuses only on a few of these novel/new approaches for antibiotic discovery. These include structure-based drug design (SBDD), the genomic approach, anti-virulence strategy, targeting nonmultiplying bacteria and the use of bacteriophages. In general, recent advancements in nuclear magnetic resonance, Xcrystallography, and genomic evolution have significant impact on antibacterial drug research. This review therefore aims to discuss recent strategies in searching new antibacterial agents making use of these technical novelties, their advantages, disadvantages and limitations.

  18. Phenotypic Screening Approaches to Develop Aurora Kinase Inhibitors: Drug Discovery Perspectives.

    Science.gov (United States)

    Marugán, Carlos; Torres, Raquel; Lallena, María José

    2015-01-01

    Targeting mitotic regulators as a strategy to fight cancer implies the development of drugs against key proteins, such as Aurora-A and -B. Current drugs, which target mitosis through a general mechanism of action (stabilization/destabilization of microtubules), have several side effects (neutropenia, alopecia, and emesis). Pharmaceutical companies aim at avoiding these unwanted effects by generating improved and selective drugs that increase the quality of life of the patients. However, the development of these drugs is an ambitious task that involves testing thousands of compounds through biochemical and cell-based assays. In addition, molecules usually target complex biological processes, involving several proteins and different molecular pathways, further emphasizing the need for high-throughput screening techniques and multiplexing technologies in order to identify drugs with the desired phenotype. We will briefly describe two multiplexing technologies [high-content imaging (HCI) and flow cytometry] and two key processes for drug discovery research (assay development and validation) following our own published industry quality standards. We will further focus on HCI as a useful tool for phenotypic screening and will provide a concrete example of HCI assay to detect Aurora-A or -B selective inhibitors discriminating the off-target effects related to the inhibition of other cell cycle or non-cell cycle key regulators. Finally, we will describe other assays that can help to characterize the in vitro pharmacology of the inhibitors.

  19. A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

    Science.gov (United States)

    Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

    2018-05-01

    The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

  20. A Bioinorganic Approach to Fragment-Based Drug Discovery Targeting Metalloenzymes.

    Science.gov (United States)

    Cohen, Seth M

    2017-08-15

    Metal-dependent enzymes (i.e., metalloenzymes) make up a large fraction of all enzymes and are critically important in a wide range of biological processes, including DNA modification, protein homeostasis, antibiotic resistance, and many others. Consequently, metalloenzymes represent a vast and largely untapped space for drug development. The discovery of effective therapeutics that target metalloenzymes lies squarely at the interface of bioinorganic and medicinal chemistry and requires expertise, methods, and strategies from both fields to mount an effective campaign. In this Account, our research program that brings together the principles and methods of bioinorganic and medicinal chemistry are described, in an effort to bridge the gap between these fields and address an important class of medicinal targets. Fragment-based drug discovery (FBDD) is an important drug discovery approach that is particularly well suited for metalloenzyme inhibitor development. FBDD uses relatively small but diverse chemical structures that allow for the assembly of privileged molecular collections that focus on a specific feature of the target enzyme. For metalloenzyme inhibition, the specific feature is rather obvious, namely, a metal-dependent active site. Surprisingly, prior to our work, the exploration of diverse molecular fragments for binding the metal active sites of metalloenzymes was largely unexplored. By assembling a modest library of metal-binding pharmacophores (MBPs), we have been able to find lead hits for many metalloenzymes and, from these hits, develop inhibitors that act via novel mechanisms of action. A specific case study on the use of this strategy to identify a first-in-class inhibitor of zinc-dependent Rpn11 (a component of the proteasome) is highlighted. The application of FBDD for the development of metalloenzyme inhibitors has raised several other compelling questions, such as how the metalloenzyme active site influences the coordination chemistry of bound

  1. Understanding mechanisms of toxicity: Insights from drug discovery research

    International Nuclear Information System (INIS)

    Houck, Keith A.; Kavlock, Robert J.

    2008-01-01

    Toxicology continues to rely heavily on use of animal testing for prediction of potential for toxicity in humans. Where mechanisms of toxicity have been elucidated, for example endocrine disruption by xenoestrogens binding to the estrogen receptor, in vitro assays have been developed as surrogate assays for toxicity prediction. This mechanistic information can be combined with other data such as exposure levels to inform a risk assessment for the chemical. However, there remains a paucity of such mechanistic assays due at least in part to lack of methods to determine specific mechanisms of toxicity for many toxicants. A means to address this deficiency lies in utilization of a vast repertoire of tools developed by the drug discovery industry for interrogating the bioactivity of chemicals. This review describes the application of high-throughput screening assays as experimental tools for profiling chemicals for potential for toxicity and understanding underlying mechanisms. The accessibility of broad panels of assays covering an array of protein families permits evaluation of chemicals for their ability to directly modulate many potential targets of toxicity. In addition, advances in cell-based screening have yielded tools capable of reporting the effects of chemicals on numerous critical cell signaling pathways and cell health parameters. Novel, more complex cellular systems are being used to model mammalian tissues and the consequences of compound treatment. Finally, high-throughput technology is being applied to model organism screens to understand mechanisms of toxicity. However, a number of formidable challenges to these methods remain to be overcome before they are widely applicable. Integration of successful approaches will contribute towards building a systems approach to toxicology that will provide mechanistic understanding of the effects of chemicals on biological systems and aid in rationale risk assessments

  2. Pharmacologically directed strategies in academic anticancer drug discovery based on the European NCI compounds initiative.

    Science.gov (United States)

    Hendriks, Hans R; Govaerts, Anne-Sophie; Fichtner, Iduna; Burtles, Sally; Westwell, Andrew D; Peters, Godefridus J

    2017-07-11

    The European NCI compounds programme, a joint initiative of the EORTC Research Branch, Cancer Research Campaign and the US National Cancer Institute, was initiated in 1993. The objective was to help the NCI in reducing the backlog of in vivo testing of potential anticancer compounds, synthesised in Europe that emerged from the NCI in vitro 60-cell screen. Over a period of more than twenty years the EORTC-Cancer Research Campaign panel reviewed ∼2000 compounds of which 95 were selected for further evaluation. Selected compounds were stepwise developed with clear go/no go decision points using a pharmacologically directed programme. This approach eliminated quickly compounds with unsuitable pharmacological properties. A few compounds went into Phase I clinical evaluation. The lessons learned and many of the principles outlined in the paper can easily be applied to current and future drug discovery and development programmes. Changes in the review panel, restrictions regarding numbers and types of compounds tested in the NCI in vitro screen and the appearance of targeted agents led to the discontinuation of the European NCI programme in 2017 and its transformation into an academic platform of excellence for anticancer drug discovery and development within the EORTC-PAMM group. This group remains open for advice and collaboration with interested parties in the field of cancer pharmacology.

  3. Protein-Templated Fragment Ligations-From Molecular Recognition to Drug Discovery.

    Science.gov (United States)

    Jaegle, Mike; Wong, Ee Lin; Tauber, Carolin; Nawrotzky, Eric; Arkona, Christoph; Rademann, Jörg

    2017-06-19

    Protein-templated fragment ligation is a novel concept to support drug discovery and can help to improve the efficacy of protein ligands. Protein-templated fragment ligations are chemical reactions between small molecules ("fragments") utilizing a protein's surface as a reaction vessel to catalyze the formation of a protein ligand with increased binding affinity. The approach exploits the molecular recognition of reactive small-molecule fragments by proteins both for ligand assembly and for the identification of bioactive fragment combinations. In this way, chemical synthesis and bioassay are integrated in one single step. This Review discusses the biophysical basis of reversible and irreversible fragment ligations and gives an overview of the available methods to detect protein-templated ligation products. The chemical scope and recent applications as well as future potential of the concept in drug discovery are reviewed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. The current state of GPCR-based drug discovery to treat metabolic disease.

    Science.gov (United States)

    Sloop, Kyle W; Emmerson, Paul J; Statnick, Michael A; Willard, Francis S

    2018-02-02

    One approach of modern drug discovery is to identify agents that enhance or diminish signal transduction cascades in various cell types and tissues by modulating the activity of GPCRs. This strategy has resulted in the development of new medicines to treat many conditions, including cardiovascular disease, psychiatric disorders, HIV/AIDS, certain forms of cancer and Type 2 diabetes mellitus (T2DM). These successes justify further pursuit of GPCRs as disease targets and provide key learning that should help guide identifying future therapeutic agents. This report reviews the current landscape of GPCR drug discovery with emphasis on efforts aimed at developing new molecules for treating T2DM and obesity. We analyse historical efforts to generate GPCR-based drugs to treat metabolic disease in terms of causal factors leading to success and failure in this endeavour. © 2018 The British Pharmacological Society.

  5. Ebola virus: A gap in drug design and discovery - experimental and computational perspective.

    Science.gov (United States)

    Balmith, Marissa; Faya, Mbuso; Soliman, Mahmoud E S

    2017-03-01

    The Ebola virus, formally known as the Ebola hemorrhagic fever, is an acute viral syndrome causing sporadic outbreaks that have ravaged West Africa. Due to its extreme virulence and highly transmissible nature, Ebola has been classified as a category A bioweapon organism. Only recently have vaccine or drug regimens for the Ebola virus been developed, including Zmapp and peptides. In addition, existing drugs which have been repurposed toward anti-Ebola virus activity have been re-examined and are seen to be promising candidates toward combating Ebola. Drug development involving computational tools has been widely employed toward target-based drug design. Screening large libraries have greatly stimulated research toward effective anti-Ebola virus drug regimens. Current emphasis has been placed on the investigation of host proteins and druggable viral targets. There is a huge gap in the literature regarding guidelines in the discovery of Ebola virus inhibitors, which may be due to the lack of information on the Ebola drug targets, binding sites, and mechanism of action of the virus. This review focuses on Ebola virus inhibitors, drugs which could be repurposed to combat the Ebola virus, computational methods which study drug-target interactions as well as providing further insight into the mode of action of the Ebola virus. © 2016 John Wiley & Sons A/S.

  6. Innovating Chinese Herbal Medicine: From Traditional Health Practice to Scientific Drug Discovery

    Directory of Open Access Journals (Sweden)

    Shuo Gu

    2017-06-01

    Full Text Available As one of the major contemporary alternative medicines, traditional Chinese medicine (TCM continues its influence in Chinese communities and has begun to attract the academic attention in the world of western medicine. This paper aims to examine Chinese herbal medicine (CHM, the essential branch of TCM, from both narrative and scientific perspectives. CHM is a traditional health practice originated from Chinese philosophy and religion, holding the belief of holism and balance in the body. With the development of orthodox medicine and science during the last centuries, CHM also seized the opportunity to change from traditional health practice to scientific drug discovery illustrated in the famous story of the herb-derived drug artemisinin. However, hindered by its culture and founding principles, CHM faces the questions of the research paradigm posed by the convention of science. To address these questions, we discussed two essential questions concerning the relationship of CHM and science, and then upheld the paradigm of methodological reductionism in scientific research. Finally, the contemporary narrative of CHM in the 21st century was discussed in the hope to preserve this medical tradition in tandem with scientific research.

  7. Innovating Chinese Herbal Medicine: From Traditional Health Practice to Scientific Drug Discovery.

    Science.gov (United States)

    Gu, Shuo; Pei, Jianfeng

    2017-01-01

    As one of the major contemporary alternative medicines, traditional Chinese medicine (TCM) continues its influence in Chinese communities and has begun to attract the academic attention in the world of western medicine. This paper aims to examine Chinese herbal medicine (CHM), the essential branch of TCM, from both narrative and scientific perspectives. CHM is a traditional health practice originated from Chinese philosophy and religion, holding the belief of holism and balance in the body. With the development of orthodox medicine and science during the last centuries, CHM also seized the opportunity to change from traditional health practice to scientific drug discovery illustrated in the famous story of the herb-derived drug artemisinin. However, hindered by its culture and founding principles, CHM faces the questions of the research paradigm posed by the convention of science. To address these questions, we discussed two essential questions concerning the relationship of CHM and science, and then upheld the paradigm of methodological reductionism in scientific research. Finally, the contemporary narrative of CHM in the 21st century was discussed in the hope to preserve this medical tradition in tandem with scientific research.

  8. Harnessing the potential of natural products in drug discovery from a cheminformatics vantage point.

    Science.gov (United States)

    Rodrigues, Tiago

    2017-11-15

    Natural products (NPs) present a privileged source of inspiration for chemical probe and drug design. Despite the biological pre-validation of the underlying molecular architectures and their relevance in drug discovery, the poor accessibility to NPs, complexity of the synthetic routes and scarce knowledge of their macromolecular counterparts in phenotypic screens still hinder their broader exploration. Cheminformatics algorithms now provide a powerful means of circumventing the abovementioned challenges and unlocking the full potential of NPs in a drug discovery context. Herein, I discuss recent advances in the computer-assisted design of NP mimics and how artificial intelligence may accelerate future NP-inspired molecular medicine.

  9. Discovery and Development of Therapeutic Drugs against Lethal Human RNA Viruses: a Multidisciplinary Assault.

    Science.gov (United States)

    1991-07-16

    AD-A239 742 AD GRANT NO: DAMD17-89-Z-9021 TITLE: DISCOVERY AND DEVELOPMENT OF THERAPEUTIC DRUGS AGAINST LETHAL HUMAN RNA VIRUSES: A MULTIDISCIPLINARY...62787A871 AB WrJDA317987 11. TITLE (Include Securty Classification) DISCOVERY AND DEVELOPMENT OF THERAPEUTIC DRUGS AGAINST LETHAL HUMAN RNA VIRUSES: A...G. R. Pettit, III, D.-S. Huang, and G. R. Pettit, 23rd Int’l. Horticulture Congress, Italy, 8/27 - 9/1/90. "Bryostatins Define the Role of Protein

  10. Epigenetics and cancer: implications for drug discovery and safety assessment

    International Nuclear Information System (INIS)

    Moggs, Jonathan G.; Goodman, Jay I.; Trosko, James E.; Roberts, Ruth A.

    2004-01-01

    It is necessary to determine whether chemicals or drugs have the potential to pose a threat to human health. Research conducted over the last two decades has led to the paradigm that chemicals can cause cancer either by damaging DNA or by altering cellular growth, probably via receptor-mediated changes in gene expression. However, recent evidence suggests that gene expression can be altered markedly via several diverse epigenetic mechanisms that can lead to permanent or reversible changes in cellular behavior. Key molecular events underlying these mechanisms include the alteration of DNA methylation and chromatin, and changes in the function of cell surface molecules. Thus, for example, DNA methyltransferase enzymes together with chromatin-associated proteins such as histone modifying enzymes and remodelling factors can modify the genetic code and contribute to the establishment and maintenance of altered epigenetic states. This is relevant to many types of toxicity including but not limited to cancer. In this paper, we describe the potential for interplay between genetic alteration and epigenetic changes in cell growth regulation and discuss the implications for drug discovery and safety assessment

  11. RNA Editing and Drug Discovery for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Wei-Hsuan Huang

    2013-01-01

    Full Text Available RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.

  12. Advances in drug metabolism and pharmacogenetics research in Australia.

    Science.gov (United States)

    Mackenzie, Peter I; Somogyi, Andrew A; Miners, John O

    2017-02-01

    Metabolism facilitates the elimination, detoxification and excretion in urine or bile (as biotransformation products) of a myriad of structurally diverse drugs and other chemicals. The metabolism of drugs, non-drug xenobiotics and many endogenous compounds is catalyzed by families of drug metabolizing enzymes (DMEs). These include the hemoprotein-containing cytochromes P450, which function predominantly as monooxygenases, and conjugation enzymes that transfer a sugar, sulfate, acetate or glutathione moiety to substrates containing a suitable acceptor functional group. Drug and chemical metabolism, especially the enzymes that catalyse these reactions, has been the research focus of several groups in Australia for over four decades. In this review, we highlight the role of recent and current drug metabolism research in Australia, including elucidation of the structure and function of enzymes from the various DME families, factors that modulate enzyme activity in humans (e.g. drug-drug interactions, gene expression and genetic polymorphism) and the application of in vitro approaches for the prediction of drug metabolism parameters in humans, along with the broader pharmacological/clinical pharmacological and toxicological significance of drug metabolism and DMEs and their relevance to drug discovery and development, and to clinical practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Robin Ganellin gives his views on medicinal chemistry and drug discovery. Interview by Stephen L. Carney.

    Science.gov (United States)

    Ganellin, C Robin

    2004-02-15

    Robin Ganellin was born in East London and studied chemistry at Queen Mary College, London, receiving a PhD in 1958 under Professor Michael Dewar for his research on tropylium chemistry. He joined Smith Kline & French Laboratories (SK&F) in the UK in 1958 and was one of the co-inventors of the revolutionary drug cimetidine (Tagamet(R)) He subsequently became Vice-President for Research at the company's Welwyn facility. In 1986 he was awarded a DSc from London University for his work on the medicinal chemistry of drugs acting at histamine receptors and was also made a Fellow of the Royal Society and appointed to the SK&F Chair of Medicinal Chemistry at University College London, where he is now Emeritus Professor of Medicinal Chemistry. Professor Ganellin has been honoured extensively, including such awards as the Royal Society of Chemistry Award for Medicinal Chemistry, their Tilden Medal and Lectureship and their Adrien Albert Medal and Lectureship, Le Prix Charles Mentzer de France, the ACS Division of Medicinal Chemistry Award, the Society of Chemical Industry Messel Medal and the Society for Drug Research Award for Drug Discovery. He is a past Chairman of the Society for Drug Research, was President of the Medicinal Chemistry Section of IUPAC, and is currently Chairman of the IUPAC Subcommittee on Medicinal Chemistry and Drug Development.

  14. In silico tools used for compound selection during target-based drug discovery and development.

    Science.gov (United States)

    Caldwell, Gary W

    2015-01-01

    The target-based drug discovery process, including target selection, screening, hit-to-lead (H2L) and lead optimization stage gates, is the most common approach used in drug development. The full integration of in vitro and/or in vivo data with in silico tools across the entire process would be beneficial to R&D productivity by developing effective selection criteria and drug-design optimization strategies. This review focuses on understanding the impact and extent in the past 5 years of in silico tools on the various stage gates of the target-based drug discovery approach. There are a large number of in silico tools available for establishing selection criteria and drug-design optimization strategies in the target-based approach. However, the inconsistent use of in vitro and/or in vivo data integrated with predictive in silico multiparameter models throughout the process is contributing to R&D productivity issues. In particular, the lack of reliable in silico tools at the H2L stage gate is contributing to the suboptimal selection of viable lead compounds. It is suggested that further development of in silico multiparameter models and organizing biologists, medicinal and computational chemists into one team with a single accountable objective to expand the utilization of in silico tools in all phases of drug discovery would improve R&D productivity.

  15. Phenotypic screening approaches to develop Aurora kinase inhibitors: Drug Discovery perspectives

    Directory of Open Access Journals (Sweden)

    Carlos eMarugán

    2016-01-01

    Full Text Available Targeting mitotic regulators as a strategy to fight cancer implies the development of drugs against key proteins such as Aurora A and B. Current drugs which target mitosis through a general mechanism of action (stabilization/destabilization of microtubules, have several side effects (neutropenia, alopecia, emesis. Pharmaceutical companies aim at avoiding these unwanted effects by generating improved and selective drugs that increase the quality of life of the patients. However, the development of these drugs is an ambitious task that involves testing thousands of compounds through biochemical and cell-based assays. In addition, molecules usually target complex biological processes, involving several proteins and different molecular pathways, further emphasizing the need for high-throughput screening techniques and multiplexing technologies in order to identify drugs with the desired phenotype.We will briefly describe two multiplexing technologies (high-content imaging, microarrays and flow cytometry and two key processes for drug discovery research (assay development and validation following our own published industry quality standards. We will further focus on high-content imaging as a useful tool for phenotypic screening and will provide a concrete example of high-content imaging assay to detect Aurora A or B selective inhibitors discriminating the off-target effects related to inhibition of other cell cycle or non-cell cycle key regulators. Finally, we will describe other assays that can help to characterize the in vitro pharmacology of the inhibitors.

  16. Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond

    Science.gov (United States)

    Van Voorhis, Wesley C.; Adams, John H.; Adelfio, Roberto; Ahyong, Vida; Akabas, Myles H.; Alano, Pietro; Alday, Aintzane; Alemán Resto, Yesmalie; Alsibaee, Aishah; Alzualde, Ainhoa; Andrews, Katherine T.; Avery, Simon V.; Avery, Vicky M.; Ayong, Lawrence; Baker, Mark; Baker, Stephen; Ben Mamoun, Choukri; Bhatia, Sangeeta; Bickle, Quentin; Bounaadja, Lotfi; Bowling, Tana; Bosch, Jürgen; Boucher, Lauren E.; Boyom, Fabrice F.; Brea, Jose; Brennan, Marian; Burton, Audrey; Caffrey, Conor R.; Camarda, Grazia; Carrasquilla, Manuela; Carter, Dee; Belen Cassera, Maria; Chih-Chien Cheng, Ken; Chindaudomsate, Worathad; Chubb, Anthony; Colon, Beatrice L.; Colón-López, Daisy D.; Corbett, Yolanda; Crowther, Gregory J.; Cowan, Noemi; D’Alessandro, Sarah; Le Dang, Na; Delves, Michael; Du, Alan Y.; Duffy, Sandra; Abd El-Salam El-Sayed, Shimaa; Ferdig, Michael T.; Fernández Robledo, José A.; Fidock, David A.; Florent, Isabelle; Fokou, Patrick V. T.; Galstian, Ani; Gamo, Francisco Javier; Gold, Ben; Golub, Todd; Goldgof, Gregory M.; Guha, Rajarshi; Guiguemde, W. Armand; Gural, Nil; Guy, R. Kiplin; Hansen, Michael A. E.; Hanson, Kirsten K.; Hemphill, Andrew; Hooft van Huijsduijnen, Rob; Horii, Takaaki; Horrocks, Paul; Hughes, Tyler B.; Huston, Christopher; Igarashi, Ikuo; Ingram-Sieber, Katrin; Itoe, Maurice A.; Jadhav, Ajit; Naranuntarat Jensen, Amornrat; Jensen, Laran T.; Jiang, Rays H. Y.; Kaiser, Annette; Keiser, Jennifer; Ketas, Thomas; Kicka, Sebastien; Kim, Sunyoung; Kirk, Kiaran; Kumar, Vidya P.; Kyle, Dennis E.; Lafuente, Maria Jose; Landfear, Scott; Lee, Nathan; Lee, Sukjun; Lehane, Adele M.; Li, Fengwu; Little, David; Liu, Liqiong; Llinás, Manuel; Loza, Maria I.; Lubar, Aristea; Lucantoni, Leonardo; Lucet, Isabelle; Maes, Louis; Mancama, Dalu; Mansour, Nuha R.; March, Sandra; McGowan, Sheena; Medina Vera, Iset; Meister, Stephan; Mercer, Luke; Mestres, Jordi; Mfopa, Alvine N.; Misra, Raj N.; Moon, Seunghyun; Moore, John P.; Morais Rodrigues da Costa, Francielly; Müller, Joachim; Muriana, Arantza; Nakazawa Hewitt, Stephen; Nare, Bakela; Nathan, Carl; Narraidoo, Nathalie; Nawaratna, Sujeevi; Ojo, Kayode K.; Ortiz, Diana; Panic, Gordana; Papadatos, George; Parapini, Silvia; Patra, Kailash; Pham, Ngoc; Prats, Sarah; Plouffe, David M.; Poulsen, Sally-Ann; Pradhan, Anupam; Quevedo, Celia; Quinn, Ronald J.; Rice, Christopher A.; Abdo Rizk, Mohamed; Ruecker, Andrea; St. Onge, Robert; Salgado Ferreira, Rafaela; Samra, Jasmeet; Robinett, Natalie G.; Schlecht, Ulrich; Schmitt, Marjorie; Silva Villela, Filipe; Silvestrini, Francesco; Sinden, Robert; Smith, Dennis A.; Soldati, Thierry; Spitzmüller, Andreas; Stamm, Serge Maximilian; Sullivan, David J.; Sullivan, William; Suresh, Sundari; Suzuki, Brian M.; Suzuki, Yo; Swamidass, S. Joshua; Taramelli, Donatella; Tchokouaha, Lauve R. Y.; Theron, Anjo; Thomas, David; Tonissen, Kathryn F.; Townson, Simon; Tripathi, Abhai K.; Trofimov, Valentin; Udenze, Kenneth O.; Ullah, Imran; Vallieres, Cindy; Vigil, Edgar; Vinetz, Joseph M.; Voong Vinh, Phat; Vu, Hoan; Watanabe, Nao-aki; Weatherby, Kate; White, Pamela M.; Wilks, Andrew F.; Winzeler, Elizabeth A.; Wojcik, Edward; Wree, Melanie; Wu, Wesley; Yokoyama, Naoaki; Zollo, Paul H. A.; Abla, Nada; Blasco, Benjamin; Burrows, Jeremy; Laleu, Benoît; Leroy, Didier; Spangenberg, Thomas; Wells, Timothy; Willis, Paul A.

    2016-01-01

    A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal

  17. Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond.

    Directory of Open Access Journals (Sweden)

    Wesley C Van Voorhis

    2016-07-01

    Full Text Available A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34% of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments

  18. Genetics of rheumatoid arthritis conributes to biology and drug discovery

    NARCIS (Netherlands)

    Okada, Yukinori; Wu, Di; Trynka, Gosia; Raj, Towfique; Terao, Chikashi; Ikari, Katsunori; Kochi, Yuta; Ohmura, Koichiro; Suzuki, A.; Yoshida, S.; Graham, R.R.; Manoharan, A.; Ortmann, W.; Bhangale, T.; Denny, J.C.; Carroll, R.J.; Eyler, A.E.; Greenberg, J.D.; Kremer, J.M.; Pappas, D.A.; Jiang, L.; Yin, L.; Ye, L.; Su, D.F.; Yang, J.; Xie, G.; Keystone, E.; Westra, H.J.; Esko, T.; Metspalu, A.; Zhou, X.; Gupta, N.; Mirel, D.; Stahl, Eli A.; Diogo, D.; Cui, J.; Liao, K.; Guo, M.H.; Myouzen, K.; Kawaguchi, T.; Coenen, M.J.; van Riel, P.L.; van de Laar, Mart A.F.J.; Guchelaar, H.J.; Huizinga, T.W.; Dieudé, P.; Mariette, X.; Louis Bridges Jr, S.; Zhernakova, A.; Toes, R.E.; Tak, P.P.; Miceli-Richard, C.; Bang, S.Y.; Lee, H.S.; Martin, J.; Gonzales-Gay, M.A.; Rodriguez-Rodriguez, L.; Rantapää-Dhlqvist, S.; Arlestig, L.; Choi, H.K.; Kamatani, Y.; Galan, P.; Lathrop, M.; Eyre, S.; Bowes, J.; Barton, A.; de Vries, N.; Moreland, L.W.; Criswell, L.A.; Karlson, E.W.; Taniguchi, A.; Yamada, R; Kubo, M.; Bae, S.C.; Worthington, J.; Padyukov, L.; Klareskog, L.; Gregersen, Peter K.; Raychaudhuri, S.; Stranger, B.E.; de Jager, P.L.; Franke, L.; Visscher, P.M.; Brown, M.A.; Yamanaka, H.; Mimori, T.; Takahashi, A.; Xu, H.; Behrens, T.W.; Siminovitch, K.A.; Momohara, S.; Matsuda, F.; Yamamoto, K.; Plenge, Robert M.

    2013-01-01

    A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed

  19. Fluorescence lifetime assays: current advances and applications in drug discovery.

    Science.gov (United States)

    Pritz, Stephan; Doering, Klaus; Woelcke, Julian; Hassiepen, Ulrich

    2011-06-01

    Fluorescence lifetime assays complement the portfolio of established assay formats available in drug discovery, particularly with the recent advances in microplate readers and the commercial availability of novel fluorescent labels. Fluorescence lifetime assists in lowering complexity of compound screening assays, affording a modular, toolbox-like approach to assay development and yielding robust homogeneous assays. To date, materials and procedures have been reported for biochemical assays on proteases, as well as on protein kinases and phosphatases. This article gives an overview of two assay families, distinguished by the origin of the fluorescence signal modulation. The pharmaceutical industry demands techniques with a robust, integrated compound profiling process and short turnaround times. Fluorescence lifetime assays have already helped the drug discovery field, in this sense, by enhancing productivity during the hit-to-lead and lead optimization phases. Future work will focus on covering other biochemical molecular modifications by investigating the detailed photo-physical mechanisms underlying the fluorescence signal.

  20. Development of anti-inflammatory drugs - the research and development process.

    Science.gov (United States)

    Knowles, Richard Graham

    2014-01-01

    The research and development process for novel drugs to treat inflammatory diseases is described, and several current issues and debates relevant to this are raised: the decline in productivity, attrition, challenges and trends in developing anti-inflammatory drugs, the poor clinical predictivity of experimental models of inflammatory diseases, heterogeneity within inflammatory diseases, 'improving on the Beatles' in treating inflammation, and the relationships between big pharma and biotechs. The pharmaceutical research and development community is responding to these challenges in multiple ways which it is hoped will lead to the discovery and development of a new generation of anti-inflammatory medicines. © 2013 Nordic Pharmacological Society. Published by John Wiley & Sons Ltd.

  1. The heat is on: thermodynamic analysis in fragment-based drug discovery

    NARCIS (Netherlands)

    Edink, E.S.; Jansen, C.J.W.; Leurs, R.; De Esch, I.J.

    2010-01-01

    Thermodynamic analysis provides access to the determinants of binding affinity, enthalpy and entropy. In fragment-based drug discovery (FBDD), thermodynamic analysis provides a powerful tool to discriminate fragments based on their potential for successful optimization. The thermodynamic data

  2. West Nile Virus Drug Discovery

    Directory of Open Access Journals (Sweden)

    Siew Pheng Lim

    2013-12-01

    Full Text Available The outbreak of West Nile virus (WNV in 1999 in the USA, and its continued spread throughout the Americas, parts of Europe, the Middle East and Africa, underscored the need for WNV antiviral development. Here, we review the current status of WNV drug discovery. A number of approaches have been used to search for inhibitors of WNV, including viral infection-based screening, enzyme-based screening, structure-based virtual screening, structure-based rationale design, and antibody-based therapy. These efforts have yielded inhibitors of viral or cellular factors that are critical for viral replication. For small molecule inhibitors, no promising preclinical candidate has been developed; most of the inhibitors could not even be advanced to the stage of hit-to-lead optimization due to their poor drug-like properties. However, several inhibitors developed for related members of the family Flaviviridae, such as dengue virus and hepatitis C virus, exhibited cross-inhibition of WNV, suggesting the possibility to re-purpose these antivirals for WNV treatment. Most promisingly, therapeutic antibodies have shown excellent efficacy in mouse model; one of such antibodies has been advanced into clinical trial. The knowledge accumulated during the past fifteen years has provided better rationale for the ongoing WNV and other flavivirus antiviral development.

  3. Trends in GPCR drug discovery: new agents, targets and indications.

    Science.gov (United States)

    Hauser, Alexander S; Attwood, Misty M; Rask-Andersen, Mathias; Schiöth, Helgi B; Gloriam, David E

    2017-12-01

    G protein-coupled receptors (GPCRs) are the most intensively studied drug targets, mostly due to their substantial involvement in human pathophysiology and their pharmacological tractability. Here, we report an up-to-date analysis of all GPCR drugs and agents in clinical trials, which reveals current trends across molecule types, drug targets and therapeutic indications, including showing that 475 drugs (~34% of all drugs approved by the US Food and Drug Administration (FDA)) act at 108 unique GPCRs. Approximately 321 agents are currently in clinical trials, of which ~20% target 66 potentially novel GPCR targets without an approved drug, and the number of biological drugs, allosteric modulators and biased agonists has increased. The major disease indications for GPCR modulators show a shift towards diabetes, obesity and Alzheimer disease, although several central nervous system disorders are also highly represented. The 224 (56%) non-olfactory GPCRs that have not yet been explored in clinical trials have broad untapped therapeutic potential, particularly in genetic and immune system disorders. Finally, we provide an interactive online resource to analyse and infer trends in GPCR drug discovery.

  4. Optogenetic Approaches to Drug Discovery in Neuroscience and Beyond.

    Science.gov (United States)

    Zhang, Hongkang; Cohen, Adam E

    2017-07-01

    Recent advances in optogenetics have opened new routes to drug discovery, particularly in neuroscience. Physiological cellular assays probe functional phenotypes that connect genomic data to patient health. Optogenetic tools, in particular tools for all-optical electrophysiology, now provide a means to probe cellular disease models with unprecedented throughput and information content. These techniques promise to identify functional phenotypes associated with disease states and to identify compounds that improve cellular function regardless of whether the compound acts directly on a target or through a bypass mechanism. This review discusses opportunities and unresolved challenges in applying optogenetic techniques throughout the discovery pipeline - from target identification and validation, to target-based and phenotypic screens, to clinical trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Hot-spot analysis for drug discovery targeting protein-protein interactions.

    Science.gov (United States)

    Rosell, Mireia; Fernández-Recio, Juan

    2018-04-01

    Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

  6. Structural Biology Guides Antibiotic Discovery

    Science.gov (United States)

    Polyak, Steven

    2014-01-01

    Modern drug discovery programs require the contribution of researchers in a number of specialist areas. One of these areas is structural biology. Using X-ray crystallography, the molecular basis of how a drug binds to its biological target and exerts its mode of action can be defined. For example, a drug that binds into the active site of an…

  7. Application of Combination High-Throughput Phenotypic Screening and Target Identification Methods for the Discovery of Natural Product-Based Combination Drugs.

    Science.gov (United States)

    Isgut, Monica; Rao, Mukkavilli; Yang, Chunhua; Subrahmanyam, Vangala; Rida, Padmashree C G; Aneja, Ritu

    2018-03-01

    Modern drug discovery efforts have had mediocre success rates with increasing developmental costs, and this has encouraged pharmaceutical scientists to seek innovative approaches. Recently with the rise of the fields of systems biology and metabolomics, network pharmacology (NP) has begun to emerge as a new paradigm in drug discovery, with a focus on multiple targets and drug combinations for treating disease. Studies on the benefits of drug combinations lay the groundwork for a renewed focus on natural products in drug discovery. Natural products consist of a multitude of constituents that can act on a variety of targets in the body to induce pharmacodynamic responses that may together culminate in an additive or synergistic therapeutic effect. Although natural products cannot be patented, they can be used as starting points in the discovery of potent combination therapeutics. The optimal mix of bioactive ingredients in natural products can be determined via phenotypic screening. The targets and molecular mechanisms of action of these active ingredients can then be determined using chemical proteomics, and by implementing a reverse pharmacokinetics approach. This review article provides evidence supporting the potential benefits of natural product-based combination drugs, and summarizes drug discovery methods that can be applied to this class of drugs. © 2017 Wiley Periodicals, Inc.

  8. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines.

    Science.gov (United States)

    Ru, Jinlong; Li, Peng; Wang, Jinan; Zhou, Wei; Li, Bohui; Huang, Chao; Li, Pidong; Guo, Zihu; Tao, Weiyang; Yang, Yinfeng; Xu, Xue; Li, Yan; Wang, Yonghua; Yang, Ling

    2014-01-01

    Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski's rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.

  9. Lost in translation? Role of metabolomics in solving translational problems in drug discovery and development

    NARCIS (Netherlands)

    Greef, J. van der; Adourian, A.; Muntendam, P.; McBurney, R.N.

    2006-01-01

    Too few drug discovery projects generate a marketed drug product, often because preclinical studies fail to predict the clinical experience with a drug candidate. Improving the success of preclinical-to-clinical translation is of paramount importance in optimizing the pharmaceutical value chain.

  10. Binding thermodynamics discriminates fragments from druglike compounds: a thermodynamic description of fragment-based drug discovery.

    Science.gov (United States)

    Williams, Glyn; Ferenczy, György G; Ulander, Johan; Keserű, György M

    2017-04-01

    Small is beautiful - reducing the size and complexity of chemical starting points for drug design allows better sampling of chemical space, reveals the most energetically important interactions within protein-binding sites and can lead to improvements in the physicochemical properties of the final drug. The impact of fragment-based drug discovery (FBDD) on recent drug discovery projects and our improved knowledge of the structural and thermodynamic details of ligand binding has prompted us to explore the relationships between ligand-binding thermodynamics and FBDD. Information on binding thermodynamics can give insights into the contributions to protein-ligand interactions and could therefore be used to prioritise compounds with a high degree of specificity in forming key interactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. In vivo brain microdialysis: advances in neuropsychopharmacology and drug discovery.

    Science.gov (United States)

    Darvesh, Altaf S; Carroll, Richard T; Geldenhuys, Werner J; Gudelsky, Gary A; Klein, Jochen; Meshul, Charles K; Van der Schyf, Cornelis J

    2011-02-01

    INTRODUCTION: Microdialysis is an important in vivo sampling technique, useful in the assay of extracellular tissue fluid. The technique has both pre-clinical and clinical applications but is most widely used in neuroscience. The in vivo microdialysis technique allows measurement of neurotransmitters such as acetycholine (ACh), the biogenic amines including dopamine (DA), norepinephrine (NE) and serotonin (5-HT), amino acids such as glutamate (Glu) and gamma aminobutyric acid (GABA), as well as the metabolites of the aforementioned neurotransmitters, and neuropeptides in neuronal extracellular fluid in discrete brain regions of laboratory animals such as rodents and non-human primates. AREAS COVERED: In this review we present a brief overview of the principles and procedures related to in vivo microdialysis and detail the use of this technique in the pre-clinical measurement of drugs designed to be used in the treatment of chemical addiction, neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD) and as well as psychiatric disorders such as attention-deficit/hyperactivity disorder (ADHD) and schizophrenia. This review offers insight into the tremendous utility and versatility of this technique in pursuing neuropharmacological investigations as well its significant potential in rational drug discovery. EXPERT OPINION: In vivo microdialysis is an extremely versatile technique, routinely used in the neuropharmacological investigation of drugs used for the treatment of neurological disorders. This technique has been a boon in the elucidation of the neurochemical profile and mechanism of action of several classes of drugs especially their effects on neurotransmitter systems. The exploitation and development of this technique for drug discovery in the near future will enable investigational new drug candidates to be rapidly moved into the clinical trial stages and to market thus providing new successful therapies for neurological diseases

  12. Leveraging the contribution of thermodynamics in drug discovery with the help of fluorescence-based thermal shift assays.

    Science.gov (United States)

    Hau, Jean Christophe; Fontana, Patrizia; Zimmermann, Catherine; De Pover, Alain; Erdmann, Dirk; Chène, Patrick

    2011-06-01

    The development of new drugs with better pharmacological and safety properties mandates the optimization of several parameters. Today, potency is often used as the sole biochemical parameter to identify and select new molecules. Surprisingly, thermodynamics, which is at the core of any interaction, is rarely used in drug discovery, even though it has been suggested that the selection of scaffolds according to thermodynamic criteria may be a valuable strategy. This poor integration of thermodynamics in drug discovery might be due to difficulties in implementing calorimetry experiments despite recent technological progress in this area. In this report, the authors show that fluorescence-based thermal shift assays could be used as prescreening methods to identify compounds with different thermodynamic profiles. This approach allows a reduction in the number of compounds to be tested in calorimetry experiments, thus favoring greater integration of thermodynamics in drug discovery.

  13. Utility of Glioblastoma Patient-Derived Orthotopic Xenografts in Drug Discovery and Personalized Therapy

    Directory of Open Access Journals (Sweden)

    Michele Patrizii

    2018-02-01

    Full Text Available Despite substantial effort and resources dedicated to drug discovery and development, new anticancer agents often fail in clinical trials. Among many reasons, the lack of reliable predictive preclinical cancer models is a fundamental one. For decades, immortalized cancer cell cultures have been used to lay the groundwork for cancer biology and the quest for therapeutic responses. However, cell lines do not usually recapitulate cancer heterogeneity or reveal therapeutic resistance cues. With the rapidly evolving exploration of cancer “omics,” the scientific community is increasingly investigating whether the employment of short-term patient-derived tumor cell cultures (two- and three-dimensional and/or patient-derived xenograft models might provide a more representative delineation of the cancer core and its therapeutic response. Patient-derived cancer models allow the integration of genomic with drug sensitivity data on a personalized basis and currently represent the ultimate approach for preclinical drug development and biomarker discovery. The proper use of these patient-derived cancer models might soon influence clinical outcomes and allow the implementation of tailored personalized therapy. When assessing drug efficacy for the treatment of glioblastoma multiforme (GBM, currently, the most reliable models are generated through direct injection of patient-derived cells or more frequently the isolation of glioblastoma cells endowed with stem-like features and orthotopically injecting these cells into the cerebrum of immunodeficient mice. Herein, we present the key strengths, weaknesses, and potential applications of cell- and animal-based models of GBM, highlighting our experience with the glioblastoma stem-like patient cell-derived xenograft model and its utility in drug discovery.

  14. The University of Kansas High-Throughput Screening laboratory. Part I: meeting drug-discovery needs in the heartland of America with entrepreneurial flair.

    Science.gov (United States)

    McDonald, Peter R; Roy, Anuradha; Chaguturu, Rathnam

    2011-05-01

    The University of Kansas High-Throughput Screening (KU HTS) core is a state-of-the-art drug-discovery facility with an entrepreneurial open-service policy, which provides centralized resources supporting public- and private-sector research initiatives. The KU HTS core applies pharmaceutical industry project-management principles in an academic setting by bringing together multidisciplinary teams to fill critical scientific and technology gaps, using an experienced team of industry-trained researchers and project managers. The KU HTS proactively engages in supporting grant applications for extramural funding, intellectual-property management and technology transfer. The KU HTS staff further provides educational opportunities for the KU faculty and students to learn cutting-edge technologies in drug-discovery platforms through seminars, workshops, internships and course teaching. This is the first instalment of a two-part contribution from the KU HTS laboratory.

  15. Exploring open innovation with a patient focus in drug discovery: an evolving paradigm of patient engagement.

    Science.gov (United States)

    Allarakhia, Minna

    2015-06-01

    It is suggested in this article that patient engagement should occur further upstream during the drug discovery stage. 'Lead patients', namely those patients who are proactive with respect to their health, possess knowledge of their disease and resulting symptoms. They are also well informed about the conventional as well as non-conventional treatments for disease management; and so can provide a nuanced perspective to drug design. Understanding how patients view the management of their diseases and how they view the use of conventional versus non-conventional interventions is of imperative importance to researchers. Indeed, this can provide insight into how conventional treatments might be designed from the outset to encourage compliance and positive health outcomes. Consequently, a continuum of lead patient engagement is employed that focuses on drug discovery processes ranging from participative, informative to collaborative engagement. This article looks at a variety of open innovation models that are currently employed across this engagement spectrum. It is no longer sufficient for industry stakeholders to consider conventional therapies as the only mechanisms being sought after by patients. Without patient engagement, the industry risks being re-prioritized in terms of its role in the patient journey towards not only recovery of health, but also sustained health and wellness before disease onset.

  16. Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery.

    Science.gov (United States)

    Heifetz, Alexander; Southey, Michelle; Morao, Inaki; Townsend-Nicholson, Andrea; Bodkin, Mike J

    2018-01-01

    GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

  17. Applicability of bioanalysis of multiple analytes in drug discovery and development: review of select case studies including assay development considerations.

    Science.gov (United States)

    Srinivas, Nuggehally R

    2006-05-01

    The development of sound bioanalytical method(s) is of paramount importance during the process of drug discovery and development culminating in a marketing approval. Although the bioanalytical procedure(s) originally developed during the discovery stage may not necessarily be fit to support the drug development scenario, they may be suitably modified and validated, as deemed necessary. Several reviews have appeared over the years describing analytical approaches including various techniques, detection systems, automation tools that are available for an effective separation, enhanced selectivity and sensitivity for quantitation of many analytes. The intention of this review is to cover various key areas where analytical method development becomes necessary during different stages of drug discovery research and development process. The key areas covered in this article with relevant case studies include: (a) simultaneous assay for parent compound and metabolites that are purported to display pharmacological activity; (b) bioanalytical procedures for determination of multiple drugs in combating a disease; (c) analytical measurement of chirality aspects in the pharmacokinetics, metabolism and biotransformation investigations; (d) drug monitoring for therapeutic benefits and/or occupational hazard; (e) analysis of drugs from complex and/or less frequently used matrices; (f) analytical determination during in vitro experiments (metabolism and permeability related) and in situ intestinal perfusion experiments; (g) determination of a major metabolite as a surrogate for the parent molecule; (h) analytical approaches for universal determination of CYP450 probe substrates and metabolites; (i) analytical applicability to prodrug evaluations-simultaneous determination of prodrug, parent and metabolites; (j) quantitative determination of parent compound and/or phase II metabolite(s) via direct or indirect approaches; (k) applicability in analysis of multiple compounds in select

  18. Natural products against cancer: A comprehensive bibliometric study of the research projects, publications, patents and drugs

    Directory of Open Access Journals (Sweden)

    Jian Du

    2014-01-01

    Full Text Available Objectives: To analyze multi-source data including awards, publications, patents and drugs, and try to draw the whole landscape of the research and development community in the area of natural products (NPs against cancer. Materials and Methods: Awards, publications, patents and drugs data from National Institute of Health/Natural Science Foundation of China (NIH/NSFC, PubMed, Derwent Innovation Index and Cortellis were collected. Bibliometric methodologies and technology are used to investigate publications/patents/drugs, their contents and relationships. Results: NIH and NSFC respectively demonstrated a stable and sustained expenditure growth in this area. The number of publications is continuously increasing. Yet the annual patent applications worldwide and FDA drug approvals were little changed or not obviously fluctuated in 2003-2013. USA and several Asia-pacific countries/territories are important contributing powers. We described the evolution of major research topics by those MeSH Major Topics indexed in PubMed with the largest growth range in three intervals, and analyzed hot research topics in the recent 10 years which include NPs or NPs derivatives, cell line/animal model, laboratory technologies and activation mechanisms. Conclusions: China published the most publications and received the most patent applications, but drug discovery performance is no better than USA and Japan. Research on anti-neoplastic structures and compounds originated from Chinese traditional medicine (TCM, medicinal plants, herbal medicine and marine NPs are major research topics in the recent 10 years. There still exits translational gap between basic research and drug discovery. Translational research should be undertaken to strengthen the applicability of NPs.

  19. Fungal Anticancer Metabolites: Synthesis Towards Drug Discovery.

    Science.gov (United States)

    Barbero, Margherita; Artuso, Emma; Prandi, Cristina

    2018-01-01

    Fungi are a well-known and valuable source of compounds of therapeutic relevance, in particular of novel anticancer compounds. Although seldom obtainable through isolation from the natural source, the total organic synthesis still remains one of the most efficient alternatives to resupply them. Furthermore, natural product total synthesis is a valuable tool not only for discovery of new complex biologically active compounds but also for the development of innovative methodologies in enantioselective organic synthesis. We undertook an in-depth literature searching by using chemical bibliographic databases (SciFinder, Reaxys) in order to have a comprehensive insight into the wide research field. The literature has been then screened, refining the obtained results by subject terms focused on both biological activity and innovative synthetic procedures. The literature on fungal metabolites has been recently reviewed and these publications have been used as a base from which we consider the synthetic feasibility of the most promising compounds, in terms of anticancer properties and drug development. In this paper, compounds are classified according to their chemical structure. This review summarizes the anticancer potential of fungal metabolites, highlighting the role of total synthesis outlining the feasibility of innovative synthetic procedures that facilitate the development of fungal metabolites into drugs that may become a real future perspective. To our knowledge, this review is the first effort to deal with the total synthesis of these active fungi metabolites and demonstrates that total chemical synthesis is a fruitful means of yielding fungal derivatives as aided by recent technological and innovative advancements. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. The Current Landscape of 3D In Vitro Tumor Models: What Cancer Hallmarks Are Accessible for Drug Discovery?

    Science.gov (United States)

    Rodenhizer, Darren; Dean, Teresa; D'Arcangelo, Elisa; McGuigan, Alison P

    2018-04-01

    Cancer prognosis remains a lottery dependent on cancer type, disease stage at diagnosis, and personal genetics. While investment in research is at an all-time high, new drugs are more likely to fail in clinical trials today than in the 1970s. In this review, a summary of current survival statistics in North America is provided, followed by an overview of the modern drug discovery process, classes of models used throughout different stages, and challenges associated with drug development efficiency are highlighted. Then, an overview of the cancer hallmarks that drive clinical progression is provided, and the range of available clinical therapies within the context of these hallmarks is categorized. Specifically, it is found that historically, the development of therapies is limited to a subset of possible targets. This provides evidence for the opportunities offered by novel disease-relevant in vitro models that enable identification of novel targets that facilitate interactions between the tumor cells and their surrounding microenvironment. Next, an overview of the models currently reported in literature is provided, and the cancer biology they have been used to explore is highlighted. Finally, four priority areas are suggested for the field to accelerate adoption of in vitro tumour models for cancer drug discovery. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Laboratory informatics tools integration strategies for drug discovery: integration of LIMS, ELN, CDS, and SDMS.

    Science.gov (United States)

    Machina, Hari K; Wild, David J

    2013-04-01

    There are technologies on the horizon that could dramatically change how informatics organizations design, develop, deliver, and support applications and data infrastructures to deliver maximum value to drug discovery organizations. Effective integration of data and laboratory informatics tools promises the ability of organizations to make better informed decisions about resource allocation during the drug discovery and development process and for more informed decisions to be made with respect to the market opportunity for compounds. We propose in this article a new integration model called ELN-centric laboratory informatics tools integration.

  2. Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

    Science.gov (United States)

    Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

    2013-01-01

    Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

  3. Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

    Directory of Open Access Journals (Sweden)

    Daniele D'Agostino

    2013-01-01

    Full Text Available Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

  4. Development of novel, 384-well high-throughput assay panels for human drug transporters: drug interaction and safety assessment in support of discovery research.

    Science.gov (United States)

    Tang, Huaping; Shen, Ding Ren; Han, Yong-Hae; Kong, Yan; Balimane, Praveen; Marino, Anthony; Gao, Mian; Wu, Sophie; Xie, Dianlin; Soars, Matthew G; O'Connell, Jonathan C; Rodrigues, A David; Zhang, Litao; Cvijic, Mary Ellen

    2013-10-01

    Transporter proteins are known to play a critical role in affecting the overall absorption, distribution, metabolism, and excretion characteristics of drug candidates. In addition to efflux transporters (P-gp, BCRP, MRP2, etc.) that limit absorption, there has been a renewed interest in influx transporters at the renal (OATs, OCTs) and hepatic (OATPs, BSEP, NTCP, etc.) organ level that can cause significant clinical drug-drug interactions (DDIs). Several of these transporters are also critical for hepatobiliary disposition of bilirubin and bile acid/salts, and their inhibition is directly implicated in hepatic toxicities. Regulatory agencies took action to address transporter-mediated DDI with the goal of ensuring drug safety in the clinic and on the market. To meet regulatory requirements, advanced bioassay technology and automation solutions were implemented for high-throughput transporter screening to provide structure-activity relationship within lead optimization. To enhance capacity, several functional assay formats were miniaturized to 384-well throughput including novel fluorescence-based uptake and efflux inhibition assays using high-content image analysis as well as cell-based radioactive uptake and vesicle-based efflux inhibition assays. This high-throughput capability enabled a paradigm shift from studying transporter-related issues in the development space to identifying and dialing out these concerns early on in discovery for enhanced mechanism-based efficacy while circumventing DDIs and transporter toxicities.

  5. Big Data in Drug Discovery.

    Science.gov (United States)

    Brown, Nathan; Cambruzzi, Jean; Cox, Peter J; Davies, Mark; Dunbar, James; Plumbley, Dean; Sellwood, Matthew A; Sim, Aaron; Williams-Jones, Bryn I; Zwierzyna, Magdalena; Sheppard, David W

    2018-01-01

    Interpretation of Big Data in the drug discovery community should enhance project timelines and reduce clinical attrition through improved early decision making. The issues we encounter start with the sheer volume of data and how we first ingest it before building an infrastructure to house it to make use of the data in an efficient and productive way. There are many problems associated with the data itself including general reproducibility, but often, it is the context surrounding an experiment that is critical to success. Help, in the form of artificial intelligence (AI), is required to understand and translate the context. On the back of natural language processing pipelines, AI is also used to prospectively generate new hypotheses by linking data together. We explain Big Data from the context of biology, chemistry and clinical trials, showcasing some of the impressive public domain sources and initiatives now available for interrogation. © 2018 Elsevier B.V. All rights reserved.

  6. Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 2.

    Science.gov (United States)

    McBride, Christopher; Cheruvallath, Zacharia; Komandla, Mallareddy; Tang, Mingnam; Farrell, Pamela; Lawson, J David; Vanderpool, Darin; Wu, Yiqin; Dougan, Douglas R; Plonowski, Artur; Holub, Corine; Larson, Chris

    2016-06-15

    Methionine aminopeptidase-2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. This step is required before they will fold or function correctly. Pre-clinical and clinical studies with a MetAP2 inhibitor suggest that they could be used as a novel treatment for obesity. Herein we describe the discovery of a series of pyrazolo[4,3-b]indoles as reversible MetAP2 inhibitors. A fragment-based drug discovery (FBDD) approach was used, beginning with the screening of fragment libraries to generate hits with high ligand-efficiency (LE). An indazole core was selected for further elaboration, guided by structural information. SAR from the indazole series led to the design of a pyrazolo[4,3-b]indole core and accelerated knowledge-based fragment growth resulted in potent and efficient MetAP2 inhibitors, which have shown robust and sustainable body weight loss in DIO mice when dosed orally. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. "Seeing is believing": perspectives of applying imaging technology in discovery toxicology.

    Science.gov (United States)

    Xu, Jinghai James; Dunn, Margaret Condon; Smith, Arthur Russell

    2009-11-01

    Efficiency and accuracy in addressing drug safety issues proactively are critical in minimizing late-stage drug attritions. Discovery toxicology has become a specialty subdivision of toxicology seeking to effectively provide early predictions and safety assessment in the drug discovery process. Among the many technologies utilized to select safer compounds for further development, in vitro imaging technology is one of the best characterized and validated to provide translatable biomarkers towards clinically-relevant outcomes of drug safety. By carefully applying imaging technologies in genetic, hepatic, and cardiac toxicology, and integrating them with the rest of the drug discovery processes, it was possible to demonstrate significant impact of imaging technology on drug research and development and substantial returns on investment.

  8. Residual Complexity Does Impact Organic Chemistry and Drug Discovery: The Case of Rufomyazine and Rufomycin.

    Science.gov (United States)

    Choules, Mary P; Klein, Larry L; Lankin, David C; McAlpine, James B; Cho, Sang-Hyun; Cheng, Jinhua; Lee, Hanki; Suh, Joo-Won; Jaki, Birgit U; Franzblau, Scott G; Pauli, Guido F

    2018-05-24

    Residual complexity (RC) involves the impact of subtle but critical structural and biological features on drug lead validation, including unexplained effects related to unidentified impurities. RC commonly plagues drug discovery efforts due to the inherent imperfections of chromatographic separation methods. The new diketopiperazine, rufomyazine (6), and the previously known antibiotic, rufomycin (7), represent a prototypical case of RC that (almost) resulted in the misassignment of biological activity. The case exemplifies that impurities well below the natural abundance of 13 C (1.1%) can be highly relevant and calls for advanced analytical characterization of drug leads with extended molar dynamic ranges of >1:1,000 using qNMR and LC-MS. Isolated from an actinomycete strain, 6 was originally found to be active against Mycobacterium tuberculosis with a minimum inhibitory concentration (MIC) of 2 μg/mL and high selectivity. As a part of lead validation, the dipeptide was synthesized and surprisingly found to be inactive. The initially observed activity was eventually attributed to a very minor contamination (0.24% [m/m]) with a highly active cyclic peptide (MIC ∼ 0.02 μM), subsequently identified as an analogue of 7. This study illustrates the serious implications RC can exert on organic chemistry and drug discovery, and what efforts are vital to improve lead validation and efficiency, especially in NP-related drug discovery programs.

  9. Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project.

    Science.gov (United States)

    Verbist, Bie; Klambauer, Günter; Vervoort, Liesbet; Talloen, Willem; Shkedy, Ziv; Thas, Olivier; Bender, Andreas; Göhlmann, Hinrich W H; Hochreiter, Sepp

    2015-05-01

    The pharmaceutical industry is faced with steadily declining R&D efficiency which results in fewer drugs reaching the market despite increased investment. A major cause for this low efficiency is the failure of drug candidates in late-stage development owing to safety issues or previously undiscovered side-effects. We analyzed to what extent gene expression data can help to de-risk drug development in early phases by detecting the biological effects of compounds across disease areas, targets and scaffolds. For eight drug discovery projects within a global pharmaceutical company, gene expression data were informative and able to support go/no-go decisions. Our studies show that gene expression profiling can detect adverse effects of compounds, and is a valuable tool in early-stage drug discovery decision making. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Inositol Polyphosphate Kinases, Fungal Virulence and Drug Discovery

    Directory of Open Access Journals (Sweden)

    Cecilia Li

    2016-09-01

    Full Text Available Opportunistic fungi are a major cause of morbidity and mortality world-wide, particularly in immunocompromised individuals. Developing new treatments to combat invasive fungal disease is challenging given that fungal and mammalian host cells are eukaryotic, with similar organization and physiology. Even therapies targeting unique fungal cell features have limitations and drug resistance is emerging. New approaches to the development of antifungal drugs are therefore needed urgently. Cryptococcus neoformans, the commonest cause of fungal meningitis worldwide, is an accepted model for studying fungal pathogenicity and driving drug discovery. We recently characterized a phospholipase C (Plc1-dependent pathway in C. neoformans comprising of sequentially-acting inositol polyphosphate kinases (IPK, which are involved in synthesizing inositol polyphosphates (IP. We also showed that the pathway is essential for fungal cellular function and pathogenicity. The IP products of the pathway are structurally diverse, each consisting of an inositol ring, with phosphate (P and pyrophosphate (PP groups covalently attached at different positions. This review focuses on (1 the characterization of the Plc1/IPK pathway in C. neoformans; (2 the identification of PP-IP5 (IP7 as the most crucial IP species for fungal fitness and virulence in a mouse model of fungal infection; and (3 why IPK enzymes represent suitable candidates for drug development.

  11. The University of New Mexico Center for Molecular Discovery

    Science.gov (United States)

    Edwards, Bruce S.; Gouveia, Kristine; Oprea, Tudor I.; Sklar, Larry A.

    2015-01-01

    The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as “up-front” services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH’s Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of “smart” oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise. PMID:24409953

  12. Recent Advances in Drug Discovery from South African Marine Invertebrates

    Directory of Open Access Journals (Sweden)

    Michael T. Davies-Coleman

    2015-10-01

    Full Text Available Recent developments in marine drug discovery from three South African marine invertebrates, the tube worm Cephalodiscus gilchristi, the ascidian Lissoclinum sp. and the sponge Topsentia pachastrelloides, are presented. Recent reports of the bioactivity and synthesis of the anti-cancer secondary metabolites cephalostatin and mandelalides (from C. gilchristi and Lissoclinum sp., respectively and various analogues are presented. The threat of drug-resistant pathogens, e.g., methicillin-resistant Staphylococcus aureus (MRSA, is assuming greater global significance, and medicinal chemistry strategies to exploit the potent MRSA PK inhibition, first revealed by two marine secondary metabolites, cis-3,4-dihydrohamacanthin B and bromodeoxytopsentin from T. pachastrelloides, are compared.

  13. Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery.

    Science.gov (United States)

    Nagamani, S; Gaur, A S; Tanneeru, K; Muneeswaran, G; Madugula, S S; Consortium, Mpds; Druzhilovskiy, D; Poroikov, V V; Sastry, G N

    2017-11-01

    Molecular property diagnostic suite (MPDS) is a Galaxy-based open source drug discovery and development platform. MPDS web portals are designed for several diseases, such as tuberculosis, diabetes mellitus, and other metabolic disorders, specifically aimed to evaluate and estimate the drug-likeness of a given molecule. MPDS consists of three modules, namely data libraries, data processing, and data analysis tools which are configured and interconnected to assist drug discovery for specific diseases. The data library module encompasses vast information on chemical space, wherein the MPDS compound library comprises 110.31 million unique molecules generated from public domain databases. Every molecule is assigned with a unique ID and card, which provides complete information for the molecule. Some of the modules in the MPDS are specific to the diseases, while others are non-specific. Importantly, a suitably altered protocol can be effectively generated for another disease-specific MPDS web portal by modifying some of the modules. Thus, the MPDS suite of web portals shows great promise to emerge as disease-specific portals of great value, integrating chemoinformatics, bioinformatics, molecular modelling, and structure- and analogue-based drug discovery approaches.

  14. Regenerative Medicine, Disease Modelling, and Drug Discovery in Human Pluripotent Stem Cell-Derived Kidney Tissue

    Directory of Open Access Journals (Sweden)

    Navin Gupta

    2017-08-01

    Full Text Available The multitude of research clarifying critical factors in embryonic organ development has been instrumental in human stem cell research. Mammalian organogenesis serves as the archetype for directed differentiation protocols, subdividing the process into a series of distinct intermediate stages that can be chemically induced and monitored for the expression of stage-specific markers. Significant advances over the past few years include established directed differentiation protocols of human embryonic stem cells and human induced pluripotent stem cells (hiPSC into human kidney organoids in vitro. Human kidney tissue in vitro simulates the in vivo response when subjected to nephrotoxins, providing a novel screening platform during drug discovery to facilitate identification of lead candidates, reduce developmental expenditures, and reduce future rates of drug-induced acute kidney injury. Patient-derived hiPSC, which bear naturally occurring DNA mutations, may allow for modelling of human genetic diseases to enable determination of pathological mechanisms and screening for novel therapeutics. In addition, recent advances in genome editing with clustered regularly interspaced short palindromic repeats (CRISPR/Cas9 enable the generation of specific mutations to study genetic disease, with non-mutated lines serving as an ideal isogenic control. The growing population of patients with end-stage kidney disease is a worldwide healthcare problem, with high morbidity and mortality rates, that warrants the discovery of novel forms of renal replacement therapy. Coupling the outlined advances in hiPSC research with innovative bioengineering techniques, such as decellularised kidney and three-dimensional printed scaffolds, may contribute to the development of bioengineered transplantable human kidney tissue as a means of renal replacement therapy.

  15. Patient-derived stem cells: pathways to drug discovery for brain diseases

    Directory of Open Access Journals (Sweden)

    Alan eMackay-Sim

    2013-03-01

    Full Text Available The concept of drug discovery through stem cell biology is based on technological developments whose genesis is now coincident. The first is automated cell microscopy with concurrent advances in image acquisition and analysis, known as high content screening (HCS. The second is patient-derived stem cells for modelling the cell biology of brain diseases. HCS has developed from the requirements of the pharmaceutical industry for high throughput assays to screen thousands of chemical compounds in the search for new drugs. HCS combines new fluorescent probes with automated microscopy and computational power to quantify the effects of compounds on cell functions. Stem cell biology has advanced greatly since the discovery of genetic reprogramming of somatic cells into induced pluripotent stem cells (iPSCs. There is now a rush of papers describing their generation from patients with various diseases of the nervous system. Although the majority of these have been genetic diseases, iPSCs have been generated from patients with complex diseases (schizophrenia and sporadic Parkinson’s disease. Some genetic diseases are also modelled in embryonic stem cells generated from blastocysts rejected during in vitro fertilisation. Neural stem cells have been isolated from post-mortem brain of Alzheimer’s patients and neural stem cells generated from biopsies of the olfactory organ of patients is another approach. These olfactory neurosphere-derived cells demonstrate robust disease-specific phenotypes in patients with schizophrenia and Parkinson’s disease. High content screening is already in use to find small molecules for the generation and differentiation of embryonic stem cells and induced pluripotent stem cells. The challenges for using stem cells for drug discovery are to develop robust stem cell culture methods that meet the rigorous requirements for repeatable, consistent quantities of defined cell types at the industrial scale necessary for high

  16. [Challenges and strategies of drug innovation].

    Science.gov (United States)

    Guo, Zong-Ru; Zhao, Hong-Yu

    2013-07-01

    Drug research involves scientific discovery, technological inventions and product development. This multiple dimensional effort embodies both high risk and high reward and is considered one of the most complicated human activities. Prior to the initiation of a program, an in-depth analysis of "what to do" and "how to do it" must be conducted. On the macro level, market prospects, capital required, risk assessment, necessary human resources, etc. need to be evaluated critically. For execution, drug candidates need to be optimized in multiple properties such as potency, selectivity, pharmacokinetics, safety, formulation, etc., all with the constraint of finite amount of time and resources, to maximize the probability of success in clinical development. Drug discovery is enormously complicated, both in terms of technological innovation and organizing capital and other resources. A deep understanding of the complexity of drug research and our competitive edge is critical for success. Our unique government-enterprise-academia system represents a distinct advantage. As a new player, we have not heavily invested in any particular discovery paradigm, which allows us to select the optimal approach with little organizational burden. Virtue R&D model using CROs has gained momentum lately and China is a global leader in CRO market. Essentially all technological support for drug discovery can be found in China, which greatly enables domestic R&D efforts. The information technology revolution ensures the globalization of drug discovery knowledge, which has bridged much of the gap between China and the developed countries. The blockbuster model and the target-centric drug discovery paradigm have overlooked the research in several important fields such as injectable drugs, orphan drugs, and following high quality therapeutic leads, etc. Prejudice against covalent ligands, prodrugs, nondrug-like ligands can also be taken advantage of to find novel medicines. This article will

  17. The case for open-source software in drug discovery.

    Science.gov (United States)

    DeLano, Warren L

    2005-02-01

    Widespread adoption of open-source software for network infrastructure, web servers, code development, and operating systems leads one to ask how far it can go. Will "open source" spread broadly, or will it be restricted to niches frequented by hopeful hobbyists and midnight hackers? Here we identify reasons for the success of open-source software and predict how consumers in drug discovery will benefit from new open-source products that address their needs with increased flexibility and in ways complementary to proprietary options.

  18. PharMillenium '99--the second world pharmaceutical congress and exhibition. Accelerating the pipeline: from drug discovery to market. 1-3 February 1999, Washington DC, USA.

    Science.gov (United States)

    Fernandes, M

    1999-04-01

    This highly interactive meeting effectively covered critical issues on every transaction from drug discovery through to development and commercialization. The program included company-specific descriptions of new discovery products, together with seminars by clinical research and site management organizations on the acceleration of development, pharmaco-economics, branding of products, direct-to-consumer advertising, global marketing, management, information technology and business strategy. There were approximately 50 sessions covered by 70 speakers.

  19. Current status and future prospects for enabling chemistry technology in the drug discovery process [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Stevan W. Djuric

    2016-09-01

    Full Text Available This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of “dangerous” reagents. Also featured are advances in the “computer-assisted drug design” area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.

  20. [From the discovery of antibiotics to emerging highly drug-resistant bacteria].

    Science.gov (United States)

    Meunier, Olivier

    2015-01-01

    The discovery of antibiotics has enabled serious infections to be treated. However, bacteria resistant to several families of antibiotics and the emergence of new highly drug-resistant bacteria constitute a public health issue in France and across the world. Actions to prevent their transmission are being put in place. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  1. Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

    Science.gov (United States)

    Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

    2018-05-17

    In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Weak affinity chromatography for evaluation of stereoisomers in early drug discovery.

    Science.gov (United States)

    Duong-Thi, Minh-Dao; Bergström, Maria; Fex, Tomas; Svensson, Susanne; Ohlson, Sten; Isaksson, Roland

    2013-07-01

    In early drug discovery (e.g., in fragment screening), recognition of stereoisomeric structures is valuable and guides medicinal chemists to focus only on useful configurations. In this work, we concurrently screened mixtures of stereoisomers and estimated their affinities to a protein target (thrombin) using weak affinity chromatography-mass spectrometry (WAC-MS). Affinity determinations by WAC showed that minor changes in stereoisomeric configuration could have a major impact on affinity. The ability of WAC-MS to provide instant information about stereoselectivity and binding affinities directly from analyte mixtures is a great advantage in fragment library screening and drug lead development.

  3. The evolution of the matrix metalloproteinase inhibitor drug discovery program at abbott laboratories.

    Science.gov (United States)

    Wada, Carol K

    2004-01-01

    Matrix metalloproteinases (MMPs) have been implicated in several pathologies. At Abbott Laboratories, the matrix metalloproteinases inhibitor drug discovery program has focused on the discovery of a potent, selective, orally bioavailable MMP inhibitor for the treatment of cancer. The program evolved from early succinate-based inhibitors to utilizing in-house technology such as SAR by NMR to develop a novel class of biaryl hydroxamate MMP inhibitors. The metabolic instability of the biaryl hydroxamates led to the discovery of a new class of N-formylhydroxylamine (retrohydroxamate) biaryl ethers, exemplified by ABT-770 (16). Toxicity issues with this pre-clinical candidate led to the discovery of another novel class of retrohydroxamate MMP inhibitors, the phenoxyphenyl sulfones such as ABT-518 (19j). ABT-518 is a potent, orally bioavailable, selective inhibitor of MMP-2 and 9 over MMP-1 that has been evaluated in Phase I clinical trials in cancer patients.

  4. When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis.

    Directory of Open Access Journals (Sweden)

    Jack W Scannell

    Full Text Available A striking contrast runs through the last 60 years of biopharmaceutical discovery, research, and development. Huge scientific and technological gains should have increased the quality of academic science and raised industrial R&D efficiency. However, academia faces a "reproducibility crisis"; inflation-adjusted industrial R&D costs per novel drug increased nearly 100 fold between 1950 and 2010; and drugs are more likely to fail in clinical development today than in the 1970s. The contrast is explicable only if powerful headwinds reversed the gains and/or if many "gains" have proved illusory. However, discussions of reproducibility and R&D productivity rarely address this point explicitly. The main objectives of the primary research in this paper are: (a to provide quantitatively and historically plausible explanations of the contrast; and (b identify factors to which R&D efficiency is sensitive. We present a quantitative decision-theoretic model of the R&D process. The model represents therapeutic candidates (e.g., putative drug targets, molecules in a screening library, etc. within a "measurement space", with candidates' positions determined by their performance on a variety of assays (e.g., binding affinity, toxicity, in vivo efficacy, etc. whose results correlate to a greater or lesser degree. We apply decision rules to segment the space, and assess the probability of correct R&D decisions. We find that when searching for rare positives (e.g., candidates that will successfully complete clinical development, changes in the predictive validity of screening and disease models that many people working in drug discovery would regard as small and/or unknowable (i.e., an 0.1 absolute change in correlation coefficient between model output and clinical outcomes in man can offset large (e.g., 10 fold, even 100 fold changes in models' brute-force efficiency. We also show how validity and reproducibility correlate across a population of simulated

  5. Translational Research 2.0: a framework for accelerating collaborative discovery.

    Science.gov (United States)

    Asakiewicz, Chris

    2014-05-01

    The world wide web has revolutionized the conduct of global, cross-disciplinary research. In the life sciences, interdisciplinary approaches to problem solving and collaboration are becoming increasingly important in facilitating knowledge discovery and integration. Web 2.0 technologies promise to have a profound impact - enabling reproducibility, aiding in discovery, and accelerating and transforming medical and healthcare research across the healthcare ecosystem. However, knowledge integration and discovery require a consistent foundation upon which to operate. A foundation should be capable of addressing some of the critical issues associated with how research is conducted within the ecosystem today and how it should be conducted for the future. This article will discuss a framework for enhancing collaborative knowledge discovery across the medical and healthcare research ecosystem. A framework that could serve as a foundation upon which ecosystem stakeholders can enhance the way data, information and knowledge is created, shared and used to accelerate the translation of knowledge from one area of the ecosystem to another.

  6. An In Vivo Platform for Rapid High-Throughput Antitubercular Drug Discovery

    Directory of Open Access Journals (Sweden)

    Kevin Takaki

    2012-07-01

    Full Text Available Treatment of tuberculosis, like other infectious diseases, is increasingly hindered by the emergence of drug resistance. Drug discovery efforts would be facilitated by facile screening tools that incorporate the complexities of human disease. Mycobacterium marinum-infected zebrafish larvae recapitulate key aspects of tuberculosis pathogenesis and drug treatment. Here, we develop a model for rapid in vivo drug screening using fluorescence-based methods for serial quantitative assessment of drug efficacy and toxicity. We provide proof-of-concept that both traditional bacterial-targeting antitubercular drugs and newly identified host-targeting drugs would be discovered through the use of this model. We demonstrate the model’s utility for the identification of synergistic combinations of antibacterial drugs and demonstrate synergy between bacterial- and host-targeting compounds. Thus, the platform can be used to identify new antibacterial agents and entirely new classes of drugs that thwart infection by targeting host pathways. The methods developed here should be widely applicable to small-molecule screens for other infectious and noninfectious diseases.

  7. Native Mass Spectrometry in Fragment-Based Drug Discovery

    Directory of Open Access Journals (Sweden)

    Liliana Pedro

    2016-07-01

    Full Text Available The advent of native mass spectrometry (MS in 1990 led to the development of new mass spectrometry instrumentation and methodologies for the analysis of noncovalent protein–ligand complexes. Native MS has matured to become a fast, simple, highly sensitive and automatable technique with well-established utility for fragment-based drug discovery (FBDD. Native MS has the capability to directly detect weak ligand binding to proteins, to determine stoichiometry, relative or absolute binding affinities and specificities. Native MS can be used to delineate ligand-binding sites, to elucidate mechanisms of cooperativity and to study the thermodynamics of binding. This review highlights key attributes of native MS for FBDD campaigns.

  8. Native Mass Spectrometry in Fragment-Based Drug Discovery.

    Science.gov (United States)

    Pedro, Liliana; Quinn, Ronald J

    2016-07-28

    The advent of native mass spectrometry (MS) in 1990 led to the development of new mass spectrometry instrumentation and methodologies for the analysis of noncovalent protein-ligand complexes. Native MS has matured to become a fast, simple, highly sensitive and automatable technique with well-established utility for fragment-based drug discovery (FBDD). Native MS has the capability to directly detect weak ligand binding to proteins, to determine stoichiometry, relative or absolute binding affinities and specificities. Native MS can be used to delineate ligand-binding sites, to elucidate mechanisms of cooperativity and to study the thermodynamics of binding. This review highlights key attributes of native MS for FBDD campaigns.

  9. A Multimodal Data Analysis Approach for Targeted Drug Discovery Involving Topological Data Analysis (TDA).

    Science.gov (United States)

    Alagappan, Muthuraman; Jiang, Dadi; Denko, Nicholas; Koong, Albert C

    In silico drug discovery refers to a combination of computational techniques that augment our ability to discover drug compounds from compound libraries. Many such techniques exist, including virtual high-throughput screening (vHTS), high-throughput screening (HTS), and mechanisms for data storage and querying. However, presently these tools are often used independent of one another. In this chapter, we describe a new multimodal in silico technique for the hit identification and lead generation phases of traditional drug discovery. Our technique leverages the benefits of three independent methods-virtual high-throughput screening, high-throughput screening, and structural fingerprint analysis-by using a fourth technique called topological data analysis (TDA). We describe how a compound library can be independently tested with vHTS, HTS, and fingerprint analysis, and how the results can be transformed into a topological data analysis network to identify compounds from a diverse group of structural families. This process of using TDA or similar clustering methods to identify drug leads is advantageous because it provides a mechanism for choosing structurally diverse compounds while maintaining the unique advantages of already established techniques such as vHTS and HTS.

  10. Integrated quantitative and qualitative workflow for in vivo bioanalytical support in drug discovery using hybrid Q-TOF-MS.

    Science.gov (United States)

    Ranasinghe, Asoka; Ramanathan, Ragu; Jemal, Mohammed; D'Arienzo, Celia J; Humphreys, W Griffith; Olah, Timothy V

    2012-03-01

    UHPLC coupled with orthogonal acceleration hybrid quadrupole-TOF (Q-TOF)-MS is an emerging technique offering new strategies for the efficient screening of new chemical entities and related molecules at the early discovery stage within the pharmaceutical industry. In the first part of this article, we examine the main instrumental parameters that are critical for the integration of UHPLC-Q-TOF technology to existing bioanalytical workflows, in order to provide simultaneous quantitative and qualitative bioanalysis of samples generated following in vivo studies. Three modern Q-TOF mass spectrometers, including Bruker maXis™, Agilent 6540 and Sciex TripleTOF™ 5600, all interfaced with UHPLC systems, are evaluated in the second part of the article. The scope of this work is to demonstrate the potential of Q-TOF for the analysis of typical small molecules, therapeutic peptides (molecular weight <6000 Da), and enzymatically (i.e., trypsin, chymotrypsin and pepsin) cleaved peptides from larger proteins. This work focuses mainly on full-scan TOF data obtained under ESI conditions, the major mode of TOF operation in discovery bioanalytical research, where the compounds are selected based on their pharmacokinetic/pharmacodynamic behaviors using animal models prior to selecting a few desirable candidates for further development. Finally, important emerging TOF technologies that could potentially benefit bioanalytical research in the semi-quantification of metabolites without synthesized standards are discussed. Particularly, the utility of captive spray ionization coupled with TripleTOF 5600 was evaluated for improving sensitivity and providing normalized MS response for drugs and their metabolites. The workflow proposed compromises neither the efficiency, nor the quality of pharmacokinetic data in support of early drug discovery programs.

  11. Feature Issue Introduction: Bio-Optics in Clinical Applications, Nanotechnology, and Drug Discovery

    OpenAIRE

    Nordstrom, Robert J.; Almutairi, Adah; Hillman, Elizabeth M.C.

    2010-01-01

    The editors introduce the Biomedical Optics Express feature issue, “Bio-Optics in Clinical Applications, Nanotechnology, and Drug Discovery,” which combines three technical areas from the 2010 Optical Society of America (OSA), Biomedical Optics (BIOMED) Topical Meeting held on 11–14 April in Miami, FL and includes contributions from conference attendees.

  12. Non human primate models for Alzheimer's disease-related research and drug discovery

    NARCIS (Netherlands)

    Van Dam, Debby; De Deyn, Peter Paul

    2017-01-01

    Introduction: Pathophysiological mechanisms underlying Alzheimer's disease (AD) remain insufficiently documented for the identification of accurate diagnostic markers and purposeful target discovery and development. Nonhuman primates (NHPs) have important translational value given their close

  13. Research synergy and drug development: Bright stars in neighboring constellations

    Directory of Open Access Journals (Sweden)

    Samet Keserci

    2017-11-01

    Full Text Available Drug discovery and subsequent availability of a new breakthrough therapeutic or ‘cure’ is a compelling example of societal benefit from research advances. These advances are invariably collaborative, involving the contributions of many scientists to a discovery network in which theory and experiment are built upon. To document and understand such scientific advances, data mining of public and commercial data sources coupled with network analysis can be used as a digital methodology to assemble and analyze component events in the history of a therapeutic. This methodology is extensible beyond the history of therapeutics and its use more generally supports (i efficiency in exploring the scientific history of a research advance (ii documenting and understanding collaboration (iii portfolio analysis, planning and optimization (iv communication of the societal value of research. Building upon prior art, we have conducted a case study of five anti-cancer therapeutics to identify the collaborations that resulted in the successful development of these therapeutics both within and across their respective networks. We have linked the work of over 235,000 authors in roughly 106,000 scientific publications that capture the research crucial for the development of these five therapeutics. Applying retrospective citation discovery, we have identified a core set of publications cited in the networks of all five therapeutics and additional intersections in combinations of networks. We have enriched the content of these networks by annotating them with information on research awards from the US National Institutes of Health (NIH. Lastly, we have mapped these awards to their cognate peer review panels, identifying another layer of collaborative scientific activity that influenced the research represented in these networks. Keywords: Information science, Cancer research

  14. Toxicophore exploration as a screening technology for drug design and discovery: techniques, scope and limitations.

    Science.gov (United States)

    Singh, Pankaj Kumar; Negi, Arvind; Gupta, Pawan Kumar; Chauhan, Monika; Kumar, Raj

    2016-08-01

    Toxicity is a common drawback of newly designed chemotherapeutic agents. With the exception of pharmacophore-induced toxicity (lack of selectivity at higher concentrations of a drug), the toxicity due to chemotherapeutic agents is based on the toxicophore moiety present in the drug. To date, methodologies implemented to determine toxicophores may be broadly classified into biological, bioanalytical and computational approaches. The biological approach involves analysis of bioactivated metabolites, whereas the computational approach involves a QSAR-based method, mapping techniques, an inverse docking technique and a few toxicophore identification/estimation tools. Being one of the major steps in drug discovery process, toxicophore identification has proven to be an essential screening step in drug design and development. The paper is first of its kind, attempting to cover and compare different methodologies employed in predicting and determining toxicophores with an emphasis on their scope and limitations. Such information may prove vital in the appropriate selection of methodology and can be used as screening technology by researchers to discover the toxicophoric potentials of their designed and synthesized moieties. Additionally, it can be utilized in the manipulation of molecules containing toxicophores in such a manner that their toxicities might be eliminated or removed.

  15. Integrity, standards, and QC-related issues with big data in pre-clinical drug discovery.

    Science.gov (United States)

    Brothers, John F; Ung, Matthew; Escalante-Chong, Renan; Ross, Jermaine; Zhang, Jenny; Cha, Yoonjeong; Lysaght, Andrew; Funt, Jason; Kusko, Rebecca

    2018-06-01

    The tremendous expansion of data analytics and public and private big datasets presents an important opportunity for pre-clinical drug discovery and development. In the field of life sciences, the growth of genetic, genomic, transcriptomic and proteomic data is partly driven by a rapid decline in experimental costs as biotechnology improves throughput, scalability, and speed. Yet far too many researchers tend to underestimate the challenges and consequences involving data integrity and quality standards. Given the effect of data integrity on scientific interpretation, these issues have significant implications during preclinical drug development. We describe standardized approaches for maximizing the utility of publicly available or privately generated biological data and address some of the common pitfalls. We also discuss the increasing interest to integrate and interpret cross-platform data. Principles outlined here should serve as a useful broad guide for existing analytical practices and pipelines and as a tool for developing additional insights into therapeutics using big data. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. Incorporation of rapid thermodynamic data in fragment-based drug discovery.

    Science.gov (United States)

    Kobe, Akihiro; Caaveiro, Jose M M; Tashiro, Shinya; Kajihara, Daisuke; Kikkawa, Masato; Mitani, Tomoya; Tsumoto, Kouhei

    2013-03-14

    Fragment-based drug discovery (FBDD) has enjoyed increasing popularity in recent years. We introduce SITE (single-injection thermal extinction), a novel thermodynamic methodology that selects high-quality hits early in FBDD. SITE is a fast calorimetric competitive assay suitable for automation that captures the essence of isothermal titration calorimetry but using significantly fewer resources. We describe the principles of SITE and identify a novel family of fragment inhibitors of the enzyme ketosteroid isomerase displaying high values of enthalpic efficiency.

  17. Exploring Chemical Space for Drug Discovery Using the Chemical Universe Database

    Science.gov (United States)

    2012-01-01

    Herein we review our recent efforts in searching for bioactive ligands by enumeration and virtual screening of the unknown chemical space of small molecules. Enumeration from first principles shows that almost all small molecules (>99.9%) have never been synthesized and are still available to be prepared and tested. We discuss open access sources of molecules, the classification and representation of chemical space using molecular quantum numbers (MQN), its exhaustive enumeration in form of the chemical universe generated databases (GDB), and examples of using these databases for prospective drug discovery. MQN-searchable GDB, PubChem, and DrugBank are freely accessible at www.gdb.unibe.ch. PMID:23019491

  18. Structural biology contributions to the discovery of drugs to treat chronic myelogenous leukaemia

    International Nuclear Information System (INIS)

    Cowan-Jacob, Sandra W.; Fendrich, Gabriele; Floersheimer, Andreas; Furet, Pascal; Liebetanz, Janis; Rummel, Gabriele; Rheinberger, Paul; Centeleghe, Mario; Fabbro, Doriano; Manley, Paul W.

    2006-01-01

    A case study showing how the determination of multiple cocrystal structures of the protein tyrosine kinase c-Abl was used to support drug discovery, resulting in a compound effective in the treatment of chronic myelogenous leukaemia. Chronic myelogenous leukaemia (CML) results from the Bcr-Abl oncoprotein, which has a constitutively activated Abl tyrosine kinase domain. Although most chronic phase CML patients treated with imatinib as first-line therapy maintain excellent durable responses, patients who have progressed to advanced-stage CML frequently fail to respond or lose their response to therapy owing to the emergence of drug-resistant mutants of the protein. More than 40 such point mutations have been observed in imatinib-resistant patients. The crystal structures of wild-type and mutant Abl kinase in complex with imatinib and other small-molecule Abl inhibitors were determined, with the aim of understanding the molecular basis of resistance and to aid in the design and optimization of inhibitors active against the resistance mutants. These results are presented in a way which illustrates the approaches used to generate multiple structures, the type of information that can be gained and the way that this information is used to support drug discovery

  19. Establishing MALDI-TOF as Versatile Drug Discovery Readout to Dissect the PTP1B Enzymatic Reaction.

    Science.gov (United States)

    Winter, Martin; Bretschneider, Tom; Kleiner, Carola; Ries, Robert; Hehn, Jörg P; Redemann, Norbert; Luippold, Andreas H; Bischoff, Daniel; Büttner, Frank H

    2018-07-01

    Label-free, mass spectrometric (MS) detection is an emerging technology in the field of drug discovery. Unbiased deciphering of enzymatic reactions is a proficient advantage over conventional label-based readouts suffering from compound interference and intricate generation of tailored signal mediators. Significant evolvements of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, as well as associated liquid handling instrumentation, triggered extensive efforts in the drug discovery community to integrate the comprehensive MS readout into the high-throughput screening (HTS) portfolio. Providing speed, sensitivity, and accuracy comparable to those of conventional, label-based readouts, combined with merits of MS-based technologies, such as label-free parallelized measurement of multiple physiological components, emphasizes the advantages of MALDI-TOF for HTS approaches. Here we describe the assay development for the identification of protein tyrosine phosphatase 1B (PTP1B) inhibitors. In the context of this precious drug target, MALDI-TOF was integrated into the HTS environment and cross-compared with the well-established AlphaScreen technology. We demonstrate robust and accurate IC 50 determination with high accordance to data generated by AlphaScreen. Additionally, a tailored MALDI-TOF assay was developed to monitor compound-dependent, irreversible modification of the active cysteine of PTP1B. Overall, the presented data proves the promising perspective for the integration of MALDI-TOF into drug discovery campaigns.

  20. Rational drug design paradigms: the odyssey for designing better drugs.

    Science.gov (United States)

    Kellici, Tahsin; Ntountaniotis, Dimitrios; Vrontaki, Eleni; Liapakis, George; Moutevelis-Minakakis, Panagiota; Kokotos, George; Hadjikakou, Sotiris; Tzakos, Andreas G; Afantitis, Antreas; Melagraki, Georgia; Bryant, Sharon; Langer, Thierry; Di Marzo, Vincenzo; Mavromoustakos, Thomas

    2015-01-01

    Due to the time and effort requirements for the development of a new drug, and the high attrition rates associated with this developmental process, there is an intense effort by academic and industrial researchers to find novel ways for more effective drug development schemes. The first step in the discovery process of a new drug is the identification of the lead compound. The modern research tendency is to avoid the synthesis of new molecules based on chemical intuition, which is time and cost consuming, and instead to apply in silico rational drug design. This approach reduces the consumables and human personnel involved in the initial steps of the drug design. In this review real examples from our research activity aiming to discover new leads will be given for various dire warnings diseases. There is no recipe to follow for discovering new leads. The strategy to be followed depends on the knowledge of the studied system and the experience of the researchers. The described examples constitute successful and unsuccessful efforts and reflect the reality which medicinal chemists have to face in drug design and development. The drug stability is also discussed in both organic molecules and metallotherapeutics. This is an important issue in drug discovery as drug metabolism in the body can lead to various toxic and undesired molecules.

  1. Research synergy and drug development: Bright stars in neighboring constellations.

    Science.gov (United States)

    Keserci, Samet; Livingston, Eric; Wan, Lingtian; Pico, Alexander R; Chacko, George

    2017-11-01

    Drug discovery and subsequent availability of a new breakthrough therapeutic or 'cure' is a compelling example of societal benefit from research advances. These advances are invariably collaborative, involving the contributions of many scientists to a discovery network in which theory and experiment are built upon. To document and understand such scientific advances, data mining of public and commercial data sources coupled with network analysis can be used as a digital methodology to assemble and analyze component events in the history of a therapeutic. This methodology is extensible beyond the history of therapeutics and its use more generally supports (i) efficiency in exploring the scientific history of a research advance (ii) documenting and understanding collaboration (iii) portfolio analysis, planning and optimization (iv) communication of the societal value of research. Building upon prior art, we have conducted a case study of five anti-cancer therapeutics to identify the collaborations that resulted in the successful development of these therapeutics both within and across their respective networks. We have linked the work of over 235,000 authors in roughly 106,000 scientific publications that capture the research crucial for the development of these five therapeutics. Applying retrospective citation discovery, we have identified a core set of publications cited in the networks of all five therapeutics and additional intersections in combinations of networks. We have enriched the content of these networks by annotating them with information on research awards from the US National Institutes of Health (NIH). Lastly, we have mapped these awards to their cognate peer review panels, identifying another layer of collaborative scientific activity that influenced the research represented in these networks.

  2. Pharmacogenetics in diverse ethnic populations--implications for drug discovery and development.

    Science.gov (United States)

    McCarthy, Linda C; Davies, Kirstie J; Campbell, David A

    2002-07-01

    It is widely acknowledged that the vast quantities of data now publicly available as a result of the human genome initiative have the potential to revolutionize the pharmaceutical industry. More tangibly to the drug development business, the dawn of the pharmacogenetics era has the potential to impact not only the discovery of new medicines but also the safety and efficacy of pharmaceutical agents. Coincident with these scientific advances is the emergence of new markets for pharmaceutical agents. Japan, which represents the world's second biggest market, is a good example. With the ICH E5 agreement in 1998 and a rapid change in the drug registration process in Japan, there are increasing opportunities to improve access to more medicines in all parts of the world. However, it is increasingly clear that significant genetic variation still exists between populations, with a host of data on interethnic variation in drug metabolizing enzyme and drug transporter activity. Evidence suggesting that this genetic variation may play an important role in defining some of the interethnic variation in drug response to currently marketed compounds is reviewed here, and future possibilities of using such information to better streamline the drug development process are discussed.

  3. Anticancer drug discovery and pharmaceutical chemistry: a history.

    Science.gov (United States)

    Braña, Miguel F; Sánchez-Migallón, Ana

    2006-10-01

    There are several procedures for the chemical discovery and design of new drugs from the point of view of the pharmaceutical or medicinal chemistry. They range from classical methods to the very new ones, such as molecular modeling or high throughput screening. In this review, we will consider some historical approaches based on the screening of natural products, the chances for luck, the systematic screening of new chemical entities and serendipity. Another group comprises rational design, as in the case of metabolic pathways, conformation versus configuration and, finally, a brief description on available new targets to be carried out. In each approach, the structure of some examples of clinical interest will be shown.

  4. Drug discovery for male subfertility using high-throughput screening: a new approach to an unsolved problem.

    Science.gov (United States)

    Martins da Silva, Sarah J; Brown, Sean G; Sutton, Keith; King, Louise V; Ruso, Halil; Gray, David W; Wyatt, Paul G; Kelly, Mark C; Barratt, Christopher L R; Hope, Anthony G

    2017-05-01

    Can pharma drug discovery approaches be utilized to transform investigation into novel therapeutics for male infertility? High-throughput screening (HTS) is a viable approach to much-needed drug discovery for male factor infertility. There is both huge demand and a genuine clinical need for new treatment options for infertile men. However, the time, effort and resources required for drug discovery are currently exorbitant, due to the unique challenges of the cellular, physical and functional properties of human spermatozoa and a lack of appropriate assay platform. Spermatozoa were obtained from healthy volunteer research donors and subfertile patients undergoing IVF/ICSI at a hospital-assisted reproductive techniques clinic between January 2012 and November 2016. A HTS assay was developed and validated using intracellular calcium ([Ca2+]i) as a surrogate for motility in human spermatozoa. Calcium fluorescence was detected using a Flexstation microplate reader (384-well platform) and compared with responses evoked by progesterone, a compound known to modify a number of biologically relevant behaviours in human spermatozoa. Hit compounds identified following single point drug screen (10 μM) of an ion channel-focussed library assembled by the University of Dundee Drug Discovery Unit were rescreened to ensure potency using standard 10 point half-logarithm concentration curves, and tested for purity and integrity using liquid chromatography and mass spectrometry. Hit compounds were grouped by structure activity relationships and five representative compounds then further investigated for direct effects on spermatozoa, using computer-assisted sperm assessment, sperm penetration assay and whole-cell patch clamping. Of the 3242 ion channel library ligands screened, 384 compounds (11.8%) elicited a statistically significant increase in calcium fluorescence, with greater than 3× median absolute deviation above the baseline. Seventy-four compounds eliciting ≥50% increase

  5. Software Infrastructure for Computer-aided Drug Discovery and Development, a Practical Example with Guidelines.

    Science.gov (United States)

    Moretti, Loris; Sartori, Luca

    2016-09-01

    In the field of Computer-Aided Drug Discovery and Development (CADDD) the proper software infrastructure is essential for everyday investigations. The creation of such an environment should be carefully planned and implemented with certain features in order to be productive and efficient. Here we describe a solution to integrate standard computational services into a functional unit that empowers modelling applications for drug discovery. This system allows users with various level of expertise to run in silico experiments automatically and without the burden of file formatting for different software, managing the actual computation, keeping track of the activities and graphical rendering of the structural outcomes. To showcase the potential of this approach, performances of five different docking programs on an Hiv-1 protease test set are presented. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Stem cells: a model for screening, discovery and development of drugs

    OpenAIRE

    Kitambi, Satish Srinivas; Chandrasekar, Gayathri

    2011-01-01

    Satish Srinivas Kitambi1, Gayathri Chandrasekar21Department of Medical Biochemistry and Biophysics; 2Department of Biosciences, Karolinska Institutet, Stockholm, SwedenAbstract: The identification of normal and cancerous stem cells and the recent advances made in isolation and culture of stem cells have rapidly gained attention in the field of drug discovery and regenerative medicine. The prospect of performing screens aimed at proliferation, directed differentiation, and toxicity and efficac...

  7. Drug Discovery of Host CLK1 Inhibitors for Influenza Treatment

    Directory of Open Access Journals (Sweden)

    Mian Zu

    2015-11-01

    Full Text Available The rapid evolution of influenza virus makes antiviral drugs less effective, which is considered to be a major bottleneck in antiviral therapy. The key proteins in the host cells, which are related with the replication cycle of influenza virus, are regarded as potential drug targets due to their distinct advantage of lack of evolution and drug resistance. Cdc2-like kinase 1 (CLK1 in the host cells is responsible for alternative splicing of the M2 gene of influenza virus during influenza infection and replication. In this study, we carried out baculovirus-mediated expression and purification of CLK1 and established a reliable screening assay for CLK1 inhibitors. After a virtual screening of CLK1 inhibitors was performed, the activities of the selected compounds were evaluated. Finally, several compounds with strong inhibitory activity against CLK1 were discovered and their in vitro anti-influenza virus activities were validated using a cytopathic effect (CPE reduction assay. The assay results showed that clypearin, corilagin, and pinosylvine were the most potential anti-influenza virus compounds as CLK1 inhibitors among the compounds tested. These findings will provide important information for new drug design and development in influenza treatment, and CLK1 may be a potent drug target for anti-influenza drug screening and discovery.

  8. Therapeutic approaches to genetic ion channelopathies and perspectives in drug discovery

    Directory of Open Access Journals (Sweden)

    Paola eImbrici

    2016-05-01

    Full Text Available In the human genome more than 400 genes encode ion channels, which are transmembrane proteins mediating ion fluxes across membranes. Being expressed in all cell types, they are involved in almost all physiological processes, including sense perception, neurotransmission, muscle contraction, secretion, immune response, cell proliferation and differentiation. Due to the widespread tissue distribution of ion channels and their physiological functions, mutations in genes encoding ion channel subunits, or their interacting proteins, are responsible for inherited ion channelopathies. These diseases can range from common to very rare disorders and their severity can be mild, disabling, or life-threatening. In spite of this, ion channels are the primary target of only about 5% of the marketed drugs suggesting their potential in drug discovery. The current review summarizes the therapeutic management of the principal ion channelopathies of central and peripheral nervous system, heart, kidney, bone, skeletal muscle and pancreas, resulting from mutations in calcium, sodium, potassium and chloride ion channels. For most channelopathies the therapy is mainly empirical and symptomatic, often limited by lack of efficacy and tolerability for a significant number of patients. Other channelopathies can exploit ion channel targeted drugs, such as marketed sodium channel blockers. Developing new and more specific therapeutic approaches is therefore required. To this aim, a major advancement in the pharmacotherapy of channelopathies has been the discovery that ion channel mutations lead to change in biophysics that can in turn specifically modify the sensitivity to drugs: this opens the way to a pharmacogenetics strategy, allowing the development of a personalized therapy with increased efficacy and reduced side effects. In addition, the identification of disease modifiers in ion channelopathies appears an alternative strategy to discover novel druggable targets.

  9. Proceedings of the 2013 CINP summit: innovative partnerships to accelerate CNS drug discovery for improved patient care.

    Science.gov (United States)

    Phillips, Anthony George; Hongaard-Andersen, Peter; Moscicki, Richard A; Sahakian, Barbara; Quirion, Rémi; Krishnan, K Ranga Rama; Race, Tim

    2014-12-25

    Central nervous system (CNS) diseases and, in particular, mental health disorders, are becoming recognized as the health challenge of the 21(st) century. Currently, at least 10% of the global population is affected by a mental health disorder, a figure that is set to increase year on year. Meanwhile, the rate of development of new CNS drugs has not increased for many years, despite unprecedented levels of investment. In response to this state of affairs, the Collegium Internationale Neuro-Psychopharmacologicum (CINP) convened a summit to discuss ways to reverse this disturbing trend through new partnerships to accelerate CNS drug discovery. The objectives of the Summit were to explore the issues affecting the value chain (i.e. the chain of activities or stakeholders that a company engages in/with to deliver a product to market) in brain research, thereby gaining insights from key stakeholders and developing actions to address unmet needs; to identify achievable objectives to address the issues; to develop action plans to bring about measurable improvements across the value chain and accelerate CNS drug discovery; and finally, to communicate recommendations to governments, the research and development community, and other relevant stakeholders. Summit outputs include the following action plans, aligned to the pressure points within the brain research-drug development value chain: Code of conduct dealing with conflict of interest issues, Prevention, early diagnosis, and treatment, Linking science and regulation, Patient involvement in trial design, definition of endpoints, etc., Novel trial design, Reproduction and confirmation of data, Update of intellectual property (IP) laws to facilitate repurposing and combination therapy (low priority), Large-scale, global patient registries, Editorials on nomenclature, biomarkers, and diagnostic tools, and Public awareness, with brain disease advocates to attend G8 meetings and World Economic Forum (WEF) Annual meetings in

  10. Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.

    Science.gov (United States)

    Wagner, Jeffrey R; Lee, Christopher T; Durrant, Jacob D; Malmstrom, Robert D; Feher, Victoria A; Amaro, Rommie E

    2016-06-08

    Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

  11. High Throughput Screening in Duchenne Muscular Dystrophy: From Drug Discovery to Functional Genomics

    Directory of Open Access Journals (Sweden)

    Thomas J.J. Gintjee

    2014-11-01

    Full Text Available Centers for the screening of biologically active compounds and genomic libraries are becoming common in the academic setting and have enabled researchers devoted to developing strategies for the treatment of diseases or interested in studying a biological phenomenon to have unprecedented access to libraries that, until few years ago, were accessible only by pharmaceutical companies. As a result, new drugs and genetic targets have now been identified for the treatment of Duchenne muscular dystrophy (DMD, the most prominent of the neuromuscular disorders affecting children. Although the work is still at an early stage, the results obtained to date are encouraging and demonstrate the importance that these centers may have in advancing therapeutic strategies for DMD as well as other diseases. This review will provide a summary of the status and progress made toward the development of a cure for this disorder and implementing high-throughput screening (HTS technologies as the main source of discovery. As more academic institutions are gaining access to HTS as a valuable discovery tool, the identification of new biologically active molecules is likely to grow larger. In addition, the presence in the academic setting of experts in different aspects of the disease will offer the opportunity to develop novel assays capable of identifying new targets to be pursued as potential therapeutic options. These assays will represent an excellent source to be used by pharmaceutical companies for the screening of larger libraries providing the opportunity to establish strong collaborations between the private and academic sectors and maximizing the chances of bringing into the clinic new drugs for the treatment of DMD.

  12. High throughput screening in duchenne muscular dystrophy: from drug discovery to functional genomics.

    Science.gov (United States)

    Gintjee, Thomas J J; Magh, Alvin S H; Bertoni, Carmen

    2014-11-14

    Centers for the screening of biologically active compounds and genomic libraries are becoming common in the academic setting and have enabled researchers devoted to developing strategies for the treatment of diseases or interested in studying a biological phenomenon to have unprecedented access to libraries that, until few years ago, were accessible only by pharmaceutical companies. As a result, new drugs and genetic targets have now been identified for the treatment of Duchenne muscular dystrophy (DMD), the most prominent of the neuromuscular disorders affecting children. Although the work is still at an early stage, the results obtained to date are encouraging and demonstrate the importance that these centers may have in advancing therapeutic strategies for DMD as well as other diseases. This review will provide a summary of the status and progress made toward the development of a cure for this disorder and implementing high-throughput screening (HTS) technologies as the main source of discovery. As more academic institutions are gaining access to HTS as a valuable discovery tool, the identification of new biologically active molecules is likely to grow larger. In addition, the presence in the academic setting of experts in different aspects of the disease will offer the opportunity to develop novel assays capable of identifying new targets to be pursued as potential therapeutic options. These assays will represent an excellent source to be used by pharmaceutical companies for the screening of larger libraries providing the opportunity to establish strong collaborations between the private and academic sectors and maximizing the chances of bringing into the clinic new drugs for the treatment of DMD.

  13. Optimizing Oral Bioavailability in Drug Discovery: An Overview of Design and Testing Strategies and Formulation Options.

    Science.gov (United States)

    Aungst, Bruce J

    2017-04-01

    For discovery teams working toward new, orally administered therapeutic agents, one requirement is to attain adequate systemic exposure after oral dosing, which is best accomplished when oral bioavailability is optimized. This report summarizes the bioavailability challenges currently faced in drug discovery, and the design and testing methods and strategies currently utilized to address the challenges. Profiling of discovery compounds usually includes separate assessments of solubility, permeability, and susceptibility to first-pass metabolism, which are the 3 most likely contributors to incomplete oral bioavailability. An initial assessment of absorption potential may be made computationally, and high throughput in vitro assays are typically performed to prioritize compounds for in vivo studies. The initial pharmacokinetic study is a critical decision point in compound evaluation, and the importance of the effect the dosing vehicle or formulation can have on oral bioavailability, especially for poorly water soluble compounds, is emphasized. Dosing vehicles and bioavailability-enabling formulations that can be used for discovery and preclinical studies are described. Optimizing oral bioavailability within a chemical series or for a lead compound requires identification of the barrier limiting bioavailability, and methods used for this purpose are outlined. Finally, a few key guidelines are offered for consideration when facing the challenges of optimizing oral bioavailability in drug discovery. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  14. Neurotransmitter transporters in schistosomes: structure, function and prospects for drug discovery.

    Science.gov (United States)

    Ribeiro, Paula; Patocka, Nicholas

    2013-12-01

    Neurotransmitter transporters (NTTs) play a fundamental role in the control of neurotransmitter signaling and homeostasis. Sodium symporters of the plasma membrane mediate the cellular uptake of neurotransmitter from the synaptic cleft, whereas proton-driven vesicular transporters sequester the neurotransmitter into synaptic vesicles for subsequent release. Together these transporters control how much transmitter is released and how long it remains in the synaptic cleft, thereby regulating the intensity and duration of signaling. NTTs have been the subject of much research in mammals and there is growing interest in their activities among invertebrates as well. In this review we will focus our attention on NTTs of the parasitic flatworm Schistosoma mansoni. Bloodflukes of the genus Schistosoma are the causative agents of human schistosomiasis, a devastating disease that afflicts over 200 million people worldwide. Schistosomes have a well-developed nervous system and a rich diversity of neurotransmitters, including many of the small-molecule ("classical") neurotransmitters that normally employ NTTs in their mechanism of signaling. Recent advances in schistosome genomics have unveiled numerous NTTs in this parasite, some of which have now been cloned and characterized in vitro. Moreover new genetic and pharmacological evidence suggests that NTTs are required for proper control of neuromuscular signaling and movement of the worm. Among these carriers are proteins that have been successfully targeted for drug discovery in other organisms, in particular sodium symporters for biogenic amine neurotransmitters such as serotonin and dopamine. Our goal in this chapter is to review the current status of research on schistosome NTTs, with emphasis on biogenic amine sodium symporters, and to evaluate their potential for anti-schistosomal drug targeting. Through this discussion we hope to draw attention to this important superfamily of parasite proteins and to identify new

  15. The future workforce in cancer prevention: advancing discovery, research, and technology.

    Science.gov (United States)

    Newhauser, Wayne D; Scheurer, Michael E; Faupel-Badger, Jessica M; Clague, Jessica; Weitzel, Jeffrey; Woods, Kendra V

    2012-05-01

    As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.

  16. Applications of fiber-optics-based nanosensors to drug discovery.

    Science.gov (United States)

    Vo-Dinh, Tuan; Scaffidi, Jonathan; Gregas, Molly; Zhang, Yan; Seewaldt, Victoria

    2009-08-01

    Fiber-optic nanosensors are fabricated by heating and pulling optical fibers to yield sub-micron diameter tips and have been used for in vitro analysis of individual living mammalian cells. Immobilization of bioreceptors (e.g., antibodies, peptides, DNA) selective to targeting analyte molecules of interest provides molecular specificity. Excitation light can be launched into the fiber, and the resulting evanescent field at the tip of the nanofiber can be used to excite target molecules bound to the bioreceptor molecules. The fluorescence or surface-enhanced Raman scattering produced by the analyte molecules is detected using an ultra-sensitive photodetector. This article provides an overview of the development and application of fiber-optic nanosensors for drug discovery. The nanosensors provide minimally invasive tools to probe subcellular compartments inside single living cells for health effect studies (e.g., detection of benzopyrene adducts) and medical applications (e.g., monitoring of apoptosis in cells treated with anticancer drugs).

  17. The impact of assay technology as applied to safety assessment in reducing compound attrition in drug discovery.

    Science.gov (United States)

    Thomas, Craig E; Will, Yvonne

    2012-02-01

    Attrition in the drug industry due to safety findings remains high and requires a shift in the current safety testing paradigm. Many companies are now positioning safety assessment at each stage of the drug development process, including discovery, where an early perspective on potential safety issues is sought, often at chemical scaffold level, using a variety of emerging technologies. Given the lengthy development time frames of drugs in the pharmaceutical industry, the authors believe that the impact of new technologies on attrition is best measured as a function of the quality and timeliness of candidate compounds entering development. The authors provide an overview of in silico and in vitro models, as well as more complex approaches such as 'omics,' and where they are best positioned within the drug discovery process. It is important to take away that not all technologies should be applied to all projects. Technologies vary widely in their validation state, throughput and cost. A thoughtful combination of validated and emerging technologies is crucial in identifying the most promising candidates to move to proof-of-concept testing in humans. In spite of the challenges inherent in applying new technologies to drug discovery, the successes and recognition that we cannot continue to rely on safety assessment practices used for decades have led to rather dramatic strategy shifts and fostered partnerships across government agencies and industry. We are optimistic that these efforts will ultimately benefit patients by delivering effective and safe medications in a timely fashion.

  18. Scientometrics of drug discovery efforts: pain-related molecular targets

    Directory of Open Access Journals (Sweden)

    Kissin I

    2015-07-01

    Full Text Available Igor KissinDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USAAbstract: The aim of this study was to make a scientometric assessment of drug discovery efforts centered on pain-related molecular targets. The following scientometric indices were used: the popularity index, representing the share of articles (or patents on a specific topic among all articles (or patents on pain over the same 5-year period; the index of change, representing the change in the number of articles (or patents on a topic from one 5-year period to the next; the index of expectations, representing the ratio of the number of all types of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000 biomedical journals covered by PubMed over a 5-year period; the total number of articles representing Phase I–III trials of investigational drugs over a 5-year period; and the trial balance index, a ratio of Phase I–II publications to Phase III publications. Articles (PubMed database and patents (US Patent and Trademark Office database on 17 topics related to pain mechanisms were assessed during six 5-year periods from 1984 to 2013. During the most recent 5-year period (2009–2013, seven of 17 topics have demonstrated high research activity (purinergic receptors, serotonin, transient receptor potential channels, cytokines, gamma aminobutyric acid, glutamate, and protein kinases. However, even with these seven topics, the index of expectations decreased or did not change compared with the 2004–2008 period. In addition, publications representing Phase I–III trials of investigational drugs (2009–2013 did not indicate great enthusiasm on the part of the pharmaceutical industry regarding drugs specifically designed for treatment of pain. A promising development related to the new tool of molecular targeting, ie, monoclonal antibodies, for pain treatment has not

  19. When fragments link : a bibliometric perspective on the development of fragment-based drug discovery

    NARCIS (Netherlands)

    Romasanta, A.K.S.; van der Sijde, P.C.; Hellsten, I.; Hubbard, Roderick E.; Keseru, Gyorgy M.; van Muijlwijk-Koezen, Jacqueline E.; de Esch, I.J.P.

    2018-01-01

    Fragment-based drug discovery (FBDD) is a highly interdisciplinary field, rich in ideas integrated from pharmaceutical sciences, chemistry, biology, and physics, among others. To enrich our understanding of the development of the field, we used bibliometric techniques to analyze 3642 publications in

  20. Pharmacometrics in early clinical drug development

    NARCIS (Netherlands)

    Keizer, R.J.

    2010-01-01

    Pharmacometrics, the science of quantitative clinical pharmacology, has been recognized as one of the main research fields able to improve efficiency in drug development, and to reduce attrition rates on the route from drug discovery to approval. This field of drug research, which builds heavily on

  1. Diterpenes: Advances in Neurobiological Drug Research.

    Science.gov (United States)

    Islam, Md Torequl; da Silva, Claucenira Bandeira; de Alencar, Marcus Vinícius Oliveira Barros; Paz, Márcia Fernanda Correia Jardim; Almeida, Fernanda Regina de Castro; Melo-Cavalcante, Ana Amélia de Carvalho

    2016-06-01

    A significant number of studies have been performed with diterpene effect on the brain. Our study aims to make a systematic revision on them. The initial purpose of this review was to screen diterpenes with neurological activity, in particular those that have already been studied and published in different journals (databases until August 2015). The second purpose was to make an action-wise discussion as results viewed on them by taking into drug discovery and development account. Diterpenes considered in this review were selected on the basis of updated information on them and having sufficient information on their screenings. We identified several examples of diterpenes having an interest in further study. We have included the possible sources of them as observed in evidence, their known molecular neurobiological mechanisms, and the active constituents responsible for such activities with the doses and test systems. Results suggest diterpenes to have neurobiological activities like neuro-protection, anti-epileptic, anxiolytic, anti-Alzheimer's disease, anti-Parkinson's disease, anti-cerebral ischemia, anti-neuropathic pain, anti-neuro-inflammatory, and many more. In conclusion, diterpenes may be the prominent candidates in neurobiological drug research. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  2. Marine Microorganism-Invertebrate Assemblages: Perspectives to Solve the “Supply Problem” in the Initial Steps of Drug Discovery

    Science.gov (United States)

    Leal, Miguel Costa; Sheridan, Christopher; Osinga, Ronald; Dionísio, Gisela; Rocha, Rui Jorge Miranda; Silva, Bruna; Rosa, Rui; Calado, Ricardo

    2014-01-01

    The chemical diversity associated with marine natural products (MNP) is unanimously acknowledged as the “blue gold” in the urgent quest for new drugs. Consequently, a significant increase in the discovery of MNP published in the literature has been observed in the past decades, particularly from marine invertebrates. However, it remains unclear whether target metabolites originate from the marine invertebrates themselves or from their microbial symbionts. This issue underlines critical challenges associated with the lack of biomass required to supply the early stages of the drug discovery pipeline. The present review discusses potential solutions for such challenges, with particular emphasis on innovative approaches to culture invertebrate holobionts (microorganism-invertebrate assemblages) through in toto aquaculture, together with methods for the discovery and initial production of bioactive compounds from these microbial symbionts. PMID:24983638

  3. Marine Microorganism-Invertebrate Assemblages: Perspectives to Solve the “Supply Problem” in the Initial Steps of Drug Discovery

    Directory of Open Access Journals (Sweden)

    Miguel Costa Leal

    2014-06-01

    Full Text Available The chemical diversity associated with marine natural products (MNP is unanimously acknowledged as the “blue gold” in the urgent quest for new drugs. Consequently, a significant increase in the discovery of MNP published in the literature has been observed in the past decades, particularly from marine invertebrates. However, it remains unclear whether target metabolites originate from the marine invertebrates themselves or from their microbial symbionts. This issue underlines critical challenges associated with the lack of biomass required to supply the early stages of the drug discovery pipeline. The present review discusses potential solutions for such challenges, with particular emphasis on innovative approaches to culture invertebrate holobionts (microorganism-invertebrate assemblages through in toto aquaculture, together with methods for the discovery and initial production of bioactive compounds from these microbial symbionts.

  4. Cunninghamella Biotransformation--Similarities to Human Drug Metabolism and Its Relevance for the Drug Discovery Process.

    Science.gov (United States)

    Piska, Kamil; Żelaszczyk, Dorota; Jamrozik, Marek; Kubowicz-Kwaśny, Paulina; Pękala, Elżbieta

    2016-01-01

    Studies of drug metabolism are one of the most significant issues in the process of drug development, its introduction to the market and also in treatment. Even the most promising molecule may show undesirable metabolic properties that would disqualify it as a potential drug. Therefore, such studies are conducted in the early phases of drug discovery and development process. Cunninghamella is a filamentous fungus known for its catalytic properties, which mimics mammalian drug metabolism. It has been proven that C. elegans carries at least one gene coding for a CYP enzyme closely related to the CYP51 family. The transformation profile of xenobiotics in Cunninghamella spp. spans a number of reactions catalyzed by different mammalian CYP isoforms. This paper presents detailed data on similar biotransformation drug products in humans and Cunninghamella spp. and covers the most important aspects of preparative biosynthesis of metabolites, since this model allows to obtain metabolites in sufficient quantities to conduct the further detailed investigations, as quantification, structure analysis and pharmacological activity and toxicity testing. The metabolic activity of three mostly used Cunninghamella species in obtaining hydroxylated, dealkylated and oxidated metabolites of different drugs confirmed its convergence with human biotransformation. Though it cannot replace the standard methods, it can provide support in the field of biotransformation and identifying metabolic soft spots of new chemicals and in predicting possible metabolic pathways. Another aspect is the biosynthesis of metabolites. In this respect, techniques using Cunninghamella spp. seem to be competitive to the chemical methods currently used.

  5. 2013 Philip S. Portoghese Medicinal Chemistry Lectureship: Drug Discovery Targeting Allosteric Sites†

    Science.gov (United States)

    2015-01-01

    The identification of sites on receptors topographically distinct from the orthosteric sites, so-called allosteric sites, has heralded novel approaches and modes of pharmacology for target modulation. Over the past 20 years, our understanding of allosteric modulation has grown significantly, and numerous advantages, as well as caveats (e.g., flat structure–activity relationships, species differences, “molecular switches”), have been identified. For multiple receptors and proteins, numerous examples have been described where unprecedented levels of selectivity are achieved along with improved physiochemical properties. While not a panacea, these novel approaches represent exciting opportunities for tool compound development to probe the pharmacology and therapeutic potential of discrete molecular targets, as well as new medicines. In this Perspective, in commemoration of the 2013 Philip S. Portoghese Medicinal Chemistry Lectureship (LindsleyC. W.Adventures in allosteric drug discovery. Presented at the 246th National Meeting of the American Chemical Society, Indianapolis, IN, September 10, 2013; The 2013 Portoghese Lectureship), several vignettes of drug discovery campaigns targeting novel allosteric mechanisms will be recounted, along with lessons learned and guidelines that have emerged for successful lead optimization. PMID:25180768

  6. The evolution of drug design at Merck Research Laboratories.

    Science.gov (United States)

    Brown, Frank K; Sherer, Edward C; Johnson, Scott A; Holloway, M Katharine; Sherborne, Bradley S

    2017-03-01

    On October 5, 1981, Fortune magazine published a cover article entitled the "Next Industrial Revolution: Designing Drugs by Computer at Merck". With a 40+ year investment, we have been in the drug design business longer than most. During its history, the Merck drug design group has had several names, but it has always been in the "design" business, with the ultimate goal to provide an actionable hypothesis that could be tested experimentally. Often the result was a small molecule but it could just as easily be a peptide, biologic, predictive model, reaction, process, etc. To this end, the concept of design is now front and center in all aspects of discovery, safety assessment and early clinical development. At present, the Merck design group includes computational chemistry, protein structure determination, and cheminformatics. By bringing these groups together under one umbrella, we were able to align activities and capabilities across multiple research sites and departments. This alignment from 2010 to 2016 resulted in an 80% expansion in the size of the department, reflecting the increase in impact due to a significant emphasis across the organization to "design first" along the entire drug discovery path from lead identification (LID) to first in human (FIH) dosing. One of the major advantages of this alignment has been the ability to access all of the data and create an adaptive approach to the overall LID to FIH pathway for any modality, significantly increasing the quality of candidates and their probability of success. In this perspective, we will discuss how we crafted a new strategy, defined the appropriate phenotype for group members, developed the right skillsets, and identified metrics for success in order to drive continuous improvement. We will not focus on the tactical implementation, only giving specific examples as appropriate.

  7. The evolution of drug design at Merck Research Laboratories

    Science.gov (United States)

    Brown, Frank K.; Sherer, Edward C.; Johnson, Scott A.; Holloway, M. Katharine; Sherborne, Bradley S.

    2017-03-01

    On October 5, 1981, Fortune magazine published a cover article entitled the "Next Industrial Revolution: Designing Drugs by Computer at Merck". With a 40+ year investment, we have been in the drug design business longer than most. During its history, the Merck drug design group has had several names, but it has always been in the "design" business, with the ultimate goal to provide an actionable hypothesis that could be tested experimentally. Often the result was a small molecule but it could just as easily be a peptide, biologic, predictive model, reaction, process, etc. To this end, the concept of design is now front and center in all aspects of discovery, safety assessment and early clinical development. At present, the Merck design group includes computational chemistry, protein structure determination, and cheminformatics. By bringing these groups together under one umbrella, we were able to align activities and capabilities across multiple research sites and departments. This alignment from 2010 to 2016 resulted in an 80% expansion in the size of the department, reflecting the increase in impact due to a significant emphasis across the organization to "design first" along the entire drug discovery path from lead identification (LID) to first in human (FIH) dosing. One of the major advantages of this alignment has been the ability to access all of the data and create an adaptive approach to the overall LID to FIH pathway for any modality, significantly increasing the quality of candidates and their probability of success. In this perspective, we will discuss how we crafted a new strategy, defined the appropriate phenotype for group members, developed the right skillsets, and identified metrics for success in order to drive continuous improvement. We will not focus on the tactical implementation, only giving specific examples as appropriate.

  8. High throughput electrophysiology: new perspectives for ion channel drug discovery

    DEFF Research Database (Denmark)

    Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter

    2003-01-01

    Proper function of ion channels is crucial for all living cells. Ion channel dysfunction may lead to a number of diseases, so-called channelopathies, and a number of common diseases, including epilepsy, arrhythmia, and type II diabetes, are primarily treated by drugs that modulate ion channels....... A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct...... characterization of ion channel properties. However, patch clamp is a slow, labor-intensive, and thus expensive, technique. New techniques combining the reliability and high information content of patch clamping with the virtues of high throughput philosophy are emerging and predicted to make a number of ion...

  9. 21 CFR 17.23 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Discovery. 17.23 Section 17.23 Food and Drugs FOOD... HEARINGS § 17.23 Discovery. (a) No later than 60 days prior to the hearing, unless otherwise ordered by the..., depositions, and any forms of discovery, other than those permitted under paragraphs (a) and (e) of this...

  10. Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

    Directory of Open Access Journals (Sweden)

    Jung Me Hwang

    2011-12-01

    Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

  11. Design of diversity and focused combinatorial libraries in drug discovery.

    Science.gov (United States)

    Young, S Stanley; Ge, Nanxiang

    2004-05-01

    Using well-characterized chemical reactions and readily available monomers, chemists are able to create sets of compounds, termed libraries, which are useful in drug discovery processes. The design of combinatorial chemical libraries can be complex and there has been much information recently published offering suggestions on how the design process can be carried out. This review focuses on literature with the goal of organizing current thinking. At this point in time, it is clear that benchmarking of current suggested methods is required as opposed to further new methods.

  12. Colworth prize lecture 2016: exploiting new biological targets from a whole-cell phenotypic screening campaign for TB drug discovery.

    Science.gov (United States)

    Moynihan, Patrick Joseph; Besra, Gurdyal S

    2017-10-01

    Mycobacterium tuberculosis is the aetiological agent of tuberculosis (TB) and is the leading bacterial cause of mortality and morbidity in the world. One third of the world's population is infected with TB, and in conjunction with HIV represents a serious problem that urgently needs addressing. TB is a disease of poverty and mostly affects young adults in their productive years, primarily in the developing world. The most recent report from the World Health Organisation states that 8 million new cases of TB were reported and that ~1.5 million people died from TB. The efficacy of treatment is threatened by the emergence of multi-drug and extensively drug-resistant strains of M. tuberculosis. It can be argued that, globally, M. tuberculosis is the single most important infectious agent affecting mankind. Our research aims to establish an academic-industrial partnership with the goal of discovering new drug targets and hit-to-lead new chemical entities for TB drug discovery.

  13. Exploiting pluripotent stem cell technology for drug discovery, screening, safety, and toxicology assessments.

    Science.gov (United States)

    McGivern, Jered V; Ebert, Allison D

    2014-04-01

    In order for the pharmaceutical industry to maintain a constant flow of novel drugs and therapeutics into the clinic, compounds must be thoroughly validated for safety and efficacy in multiple biological and biochemical systems. Pluripotent stem cells, because of their ability to develop into any cell type in the body and recapitulate human disease, may be an important cellular system to add to the drug development repertoire. This review will discuss some of the benefits of using pluripotent stem cells for drug discovery and safety studies as well as some of the recent applications of stem cells in drug screening studies. We will also address some of the hurdles that need to be overcome in order to make stem cell-based approaches an efficient and effective tool in the quest to produce clinically successful drug compounds. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Human embryonic stem cell technologies and drug discovery.

    Science.gov (United States)

    Jensen, Janne; Hyllner, Johan; Björquist, Petter

    2009-06-01

    Development of new drugs is costly and takes huge resources into consideration. The big pharmaceutical companies are currently facing increasing developmental costs and a lower success-rate of bringing new compounds to the market. Therefore, it is now of outmost importance that the drug-hunting companies minimize late attritions due to sub-optimal pharmacokinetic properties or unexpected toxicity when entering the clinical programs. To achieve this, a strong need to test new candidate drugs in assays of high human relevance in vitro as early as possible has been identified. The traditionally used cell systems are however remarkably limited in this sense, and new improved technologies are of greatest importance. The human embryonic stem cells (hESC) is one of the most powerful cell types known. They have not only the possibility to divide indefinitely; these cells can also differentiate into all mature cell types of the human body. This makes them potentially very valuable for pharmaceutical development, spanning from use as tools in early target studies, DMPK or safety assessment, as screening models to find new chemical entities modulating adult stem cell fate, or as the direct use in cell therapies. This review illustrates the use of hESC in the drug discovery process, today, as well as in a future perspective. This will specifically be exemplified with the most important cell type for pharmaceutical development-the hepatocyte. We discuss how hESC-derived hepatocyte-like cells could improve this process, and how these cells should be cultured if optimized functionality and usefulness should be achieved. J. Cell. Physiol. 219: 513-519, 2009. (c) 2009 Wiley-Liss, Inc.

  15. Report on the 10th anniversary of international drug discovery science and technology conference, 8 - 10 november 2012, nanjing, china.

    Science.gov (United States)

    Everett, Jeremy R

    2013-03-01

    The 10th Anniversary of International Drug Discovery Science and Technology (IDDST) Conference was held in Nanjing, China from 8 to 10 November 2012. The conference ran in parallel with the 2nd Annual Symposium of Drug Delivery Systems. Over 400 delegates from both conferences came together for the Opening Ceremony and Keynote Addresses but otherwise pursued separate paths in the huge facilities of the Nanjing International Expo Centre. The IDDST was arranged into 19 separate Chapters covering drug discovery biology, target validation, chemistry, rational drug design, pharmacology and toxicology, drug screening technology, 'omics' technologies, analytical, automation and enabling technologies, informatics, stem cells and regenerative medicine, bioprocessing, generics, biosimilars and biologicals and seven disease areas: cancer, CNS, respiratory and inflammation, autoimmune, emerging infectious, bone and orphan diseases. There were also two sessions of a 'Bench to Bedside to Business' Program and a Chinese Scientist programme. In each period of the IDDST conference, up to seven sessions were running in parallel. This Meeting Highlight samples just a fraction of the content of this large meeting. The talks included have as a link, the use of new approaches to drug discovery. Many other excellent talks could have been highlighted and the author has necessarily had to be selective.

  16. In vitro membrane binding and protein binding (IAM MB/PB technology to estimate in vivo distribution: applications in early drug discovery

    Directory of Open Access Journals (Sweden)

    Klara Livia Valko

    2017-03-01

    Full Text Available The drug discovery process can be accelerated by chromatographic profiling of the analogs to model in vivo distribution and the major non-specific binding. A balanced potency and chromatographically determined membrane and protein binding (IAM MB/PB data enable selecting drug discovery compounds for further analysis that have the highest probability to show the desired in vivo distribution behavior for efficacy and reduced chance for toxicity. Although the basic principles of the technology have already appeared in numerous publications, the lack of standardized procedures limited its widespread applications especially in academia and small drug discovery biotech companies. In this paper, the standardized procedures are described that has been trademarked as Regis IAM MB/PB Technology®. Comparison between the Drug Efficiency Index (DEI=pIC50-logVdu+2 and generally used Ligand Lipophilicity Efficiency (LLE has been made, demonstrating the advantage of measured IAM and HSA binding over calculated log P. The power of the proposed chromatographic technology is demonstrated using the data of marketed drugs.

  17. Traditional Medicine Collection Tracking System (TM-CTS): a database for ethnobotanically driven drug-discovery programs.

    Science.gov (United States)

    Harris, Eric S J; Erickson, Sean D; Tolopko, Andrew N; Cao, Shugeng; Craycroft, Jane A; Scholten, Robert; Fu, Yanling; Wang, Wenquan; Liu, Yong; Zhao, Zhongzhen; Clardy, Jon; Shamu, Caroline E; Eisenberg, David M

    2011-05-17

    Ethnobotanically driven drug-discovery programs include data related to many aspects of the preparation of botanical medicines, from initial plant collection to chemical extraction and fractionation. The Traditional Medicine Collection Tracking System (TM-CTS) was created to organize and store data of this type for an international collaborative project involving the systematic evaluation of commonly used Traditional Chinese Medicinal plants. The system was developed using domain-driven design techniques, and is implemented using Java, Hibernate, PostgreSQL, Business Intelligence and Reporting Tools (BIRT), and Apache Tomcat. The TM-CTS relational database schema contains over 70 data types, comprising over 500 data fields. The system incorporates a number of unique features that are useful in the context of ethnobotanical projects such as support for information about botanical collection, method of processing, quality tests for plants with existing pharmacopoeia standards, chemical extraction and fractionation, and historical uses of the plants. The database also accommodates data provided in multiple languages and integration with a database system built to support high throughput screening based drug discovery efforts. It is accessed via a web-based application that provides extensive, multi-format reporting capabilities. This new database system was designed to support a project evaluating the bioactivity of Chinese medicinal plants. The software used to create the database is open source, freely available, and could potentially be applied to other ethnobotanically driven natural product collection and drug-discovery programs. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  18. Traditional Medicine Collection Tracking System (TM-CTS): A Database for Ethnobotanically-Driven Drug-Discovery Programs

    Science.gov (United States)

    Harris, Eric S. J.; Erickson, Sean D.; Tolopko, Andrew N.; Cao, Shugeng; Craycroft, Jane A.; Scholten, Robert; Fu, Yanling; Wang, Wenquan; Liu, Yong; Zhao, Zhongzhen; Clardy, Jon; Shamu, Caroline E.; Eisenberg, David M.

    2011-01-01

    Aim of the study. Ethnobotanically-driven drug-discovery programs include data related to many aspects of the preparation of botanical medicines, from initial plant collection to chemical extraction and fractionation. The Traditional Medicine-Collection Tracking System (TM-CTS) was created to organize and store data of this type for an international collaborative project involving the systematic evaluation of commonly used Traditional Chinese Medicinal plants. Materials and Methods. The system was developed using domain-driven design techniques, and is implemented using Java, Hibernate, PostgreSQL, Business Intelligence and Reporting Tools (BIRT), and Apache Tomcat. Results. The TM-CTS relational database schema contains over 70 data types, comprising over 500 data fields. The system incorporates a number of unique features that are useful in the context of ethnobotanical projects such as support for information about botanical collection, method of processing, quality tests for plants with existing pharmacopoeia standards, chemical extraction and fractionation, and historical uses of the plants. The database also accommodates data provided in multiple languages and integration with a database system built to support high throughput screening based drug discovery efforts. It is accessed via a web-based application that provides extensive, multi-format reporting capabilities. Conclusions. This new database system was designed to support a project evaluating the bioactivity of Chinese medicinal plants. The software used to create the database is open source, freely available, and could potentially be applied to other ethnobotanically-driven natural product collection and drug-discovery programs. PMID:21420479

  19. Small Molecule Drug Discovery at the Glucagon-Like Peptide-1 Receptor

    Directory of Open Access Journals (Sweden)

    Francis S. Willard

    2012-01-01

    Full Text Available The therapeutic success of peptide glucagon-like peptide-1 (GLP-1 receptor agonists for the treatment of type 2 diabetes mellitus has inspired discovery efforts aimed at developing orally available small molecule GLP-1 receptor agonists. Although the GLP-1 receptor is a member of the structurally complex class B1 family of GPCRs, in recent years, a diverse array of orthosteric and allosteric nonpeptide ligands has been reported. These compounds include antagonists, agonists, and positive allosteric modulators with intrinsic efficacy. In this paper, a comprehensive review of currently disclosed small molecule GLP-1 receptor ligands is presented. In addition, examples of “ligand bias” and “probe dependency” for the GLP-1 receptor are discussed; these emerging concepts may influence further optimization of known molecules or persuade designs of expanded screening strategies to identify novel chemical starting points for GLP-1 receptor drug discovery.

  20. Current Landscape of Antiviral Drug Discovery [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Wade Blair

    2016-02-01

    Full Text Available Continued discovery and development of new antiviral medications are paramount for global human health, particularly as new pathogens emerge and old ones evolve to evade current therapeutic agents. Great success has been achieved in developing effective therapies to suppress human immunodeficiency virus (HIV and hepatitis B virus (HBV; however, the therapies are not curative and therefore current efforts in HIV and HBV drug discovery are directed toward longer-acting therapies and/or developing new mechanisms of action that could potentially lead to cure, or eradication, of the virus. Recently, exciting early clinical data have been reported for novel antivirals targeting respiratory syncytial virus (RSV and influenza (flu. Preclinical data suggest that these new approaches may be effective in treating high-risk patients afflicted with serious RSV or flu infections. In this review, we highlight new directions in antiviral approaches for HIV, HBV, and acute respiratory virus infections.

  1. The European Lead Factory: A Blueprint for Public-Private Partnerships in Early Drug Discovery.

    Science.gov (United States)

    Karawajczyk, Anna; Orrling, Kristina M; de Vlieger, Jon S B; Rijnders, Ton; Tzalis, Dimitrios

    2016-01-01

    The European Lead Factory (ELF) is a public-private partnership (PPP) that provides researchers in Europe with a unique platform for translation of innovative biology and chemistry into high-quality starting points for drug discovery. It combines an exceptional collection of small molecules, high-throughput screening (HTS) infrastructure, and hit follow-up capabilities to advance research projects from both private companies and publicly funded researchers. By active interactions with the wider European life science community, ELF connects and unites bright ideas, talent, and experience from several disciplines. As a result, ELF is a unique, collaborative lead generation engine that has so far resulted in >4,500 hit compounds with a defined biological activity from 83 successfully completed HTS and hit evaluation campaigns. The PPP has also produced more than 120,000 novel innovative library compounds that complement the 327,000 compounds contributed by the participating pharmaceutical companies. Intrinsic to its setup, ELF enables breakthroughs in areas with unmet medical and societal needs, where no individual entity would be able to create a comparable impact in such a short time.

  2. The European Lead Factory: A Blueprint for Public–Private Partnerships in Early Drug Discovery

    Science.gov (United States)

    Karawajczyk, Anna; Orrling, Kristina M.; de Vlieger, Jon S. B.; Rijnders, Ton; Tzalis, Dimitrios

    2017-01-01

    The European Lead Factory (ELF) is a public–private partnership (PPP) that provides researchers in Europe with a unique platform for translation of innovative biology and chemistry into high-quality starting points for drug discovery. It combines an exceptional collection of small molecules, high-throughput screening (HTS) infrastructure, and hit follow-up capabilities to advance research projects from both private companies and publicly funded researchers. By active interactions with the wider European life science community, ELF connects and unites bright ideas, talent, and experience from several disciplines. As a result, ELF is a unique, collaborative lead generation engine that has so far resulted in >4,500 hit compounds with a defined biological activity from 83 successfully completed HTS and hit evaluation campaigns. The PPP has also produced more than 120,000 novel innovative library compounds that complement the 327,000 compounds contributed by the participating pharmaceutical companies. Intrinsic to its setup, ELF enables breakthroughs in areas with unmet medical and societal needs, where no individual entity would be able to create a comparable impact in such a short time. PMID:28154815

  3. Simulated drug discovery process to conduct a synoptic assessment of pharmacy students.

    Science.gov (United States)

    Richardson, Alan; Curtis, Anthony D M; Moss, Gary P; Pearson, Russell J; White, Simon; Rutten, Frank J M; Perumal, Dhaya; Maddock, Katie

    2014-03-12

    OBJECTIVE. To implement and assess a task-based learning exercise that prompts pharmacy students to integrate their understanding of different disciplines. DESIGN. Master of pharmacy (MPharm degree) students were provided with simulated information from several preclinical science and from clinical trials and asked to synthesize this into a marketing authorization application for a new drug. Students made a link to pharmacy practice by creating an advice leaflet for pharmacists. ASSESSMENT. Students' ability to integrate information from different disciplines was evaluated by oral examination. In 2 successive academic years, 96% and 82% of students demonstrated an integrated understanding of their proposed new drug. Students indicated in a survey that their understanding of the links between different subjects improved. CONCLUSION. Simulated drug discovery provides a learning environment that emphasizes the connectivity of the preclinical sciences with each other and the practice of pharmacy.

  4. From Medicinal Chemistry to Human Health: Current Approaches to Drug Discovery for Cancer and Neglected Tropical Diseases

    Directory of Open Access Journals (Sweden)

    LEONARDO G. FERREIRA

    2018-02-01

    Full Text Available ABSTRACT Scientific and technological breakthroughs have compelled the current players in drug discovery to increasingly incorporate knowledge-based approaches. This evolving paradigm, which has its roots attached to the recent advances in medicinal chemistry, molecular and structural biology, has unprecedentedly demanded the development of up-to-date computational approaches, such as bio- and chemo-informatics. These tools have been pivotal to catalyzing the ever-increasing amount of data generated by the molecular sciences, and to converting the data into insightful guidelines for use in the research pipeline. As a result, ligand- and structure-based drug design have emerged as key pathways to address the pharmaceutical industry’s striking demands for innovation. These approaches depend on a keen integration of experimental and molecular modeling methods to surmount the main challenges faced by drug candidates - in vivo efficacy, pharmacodynamics, metabolism, pharmacokinetics and safety. To that end, the Laboratório de Química Medicinal e Computacional (LQMC of the Universidade de São Paulo has developed forefront research on highly prevalent and life-threatening neglected tropical diseases and cancer. By taking part in global initiatives for pharmaceutical innovation, the laboratory has contributed to the advance of these critical therapeutic areas through the use of cutting-edge strategies in medicinal chemistry.

  5. Biochemistry and biomedicine of quantum dots: from biodetection to bioimaging, drug discovery, diagnostics, and therapy.

    Science.gov (United States)

    Yao, Jun; Li, Pingfan; Li, Lin; Yang, Mei

    2018-07-01

    According to recent research, nanotechnology based on quantum dots (QDs) has been widely applied in the field of bioimaging, drug delivery, and drug analysis. Therefore, it has become one of the major forces driving basic and applied research. The application of nanotechnology in bioimaging has been of concern. Through in vitro labeling, it was found that luminescent QDs possess many properties such as narrow emission, broad UV excitation, bright fluorescence, and high photostability. The QDs also show great potential in whole-body imaging. The QDs can be combined with biomolecules, and hence, they can be used for targeted drug delivery and diagnosis. The characteristics of QDs make them useful for application in pharmacy and pharmacology. This review focuses on various applications of QDs, especially in imaging, drug delivery, pharmaceutical analysis, photothermal therapy, biochips, and targeted surgery. Finally, conclusions are made by providing some critical challenges and a perspective of how this field can be expected to develop in the future. Quantum dots (QDs) is an emerging field of interdisciplinary subject that involves physics, chemistry, materialogy, biology, medicine, and so on. In addition, nanotechnology based on QDs has been applied in depth in biochemistry and biomedicine. Some forward-looking fields emphatically reflected in some extremely vital areas that possess inspiring potential applicable prospects, such as immunoassay, DNA analysis, biological monitoring, drug discovery, in vitro labelling, in vivo imaging, and tumor target are closely connected to human life and health and has been the top and forefront in science and technology to date. Furthermore, this review has not only involved the traditional biochemical detection but also particularly emphasized its potential applications in life science and biomedicine. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  6. Brivaracetam: a rational drug discovery success story

    Science.gov (United States)

    Rogawski, M A

    2008-01-01

    Levetiracetam, the α-ethyl analogue of the nootropic piracetam, is a widely used antiepileptic drug (AED) that provides protection against partial seizures and is also effective in the treatment of primary generalized seizure syndromes including juvenile myoclonic epilepsy. Levetiracetam was discovered in 1992 through screening in audiogenic seizure susceptible mice and, 3 years later, was reported to exhibit saturable, stereospecific binding in brain to a ∼90 kDa protein, later identified as the ubiquitous synaptic vesicle glycoprotein SV2A. A large-scale screening effort to optimize binding affinity identified the 4-n-propyl analogue, brivaracetam, as having greater potency and a broadened spectrum of activity in animal seizure models. Recent phase II clinical trials demonstrating that brivaracetam is efficacious and well tolerated in the treatment of partial onset seizures have validated the strategy of the discovery programme. Brivaracetam is among the first clinically effective AEDs to be discovered by optimization of pharmacodynamic activity at a molecular target. PMID:18552880

  7. Drug Repositioning Discovery for Early- and Late-Stage Non-Small-Cell Lung Cancer

    Directory of Open Access Journals (Sweden)

    Chien-Hung Huang

    2014-01-01

    Full Text Available Drug repositioning is a popular approach in the pharmaceutical industry for identifying potential new uses for existing drugs and accelerating the development time. Non-small-cell lung cancer (NSCLC is one of the leading causes of death worldwide. To reduce the biological heterogeneity effects among different individuals, both normal and cancer tissues were taken from the same patient, hence allowing pairwise testing. By comparing early- and late-stage cancer patients, we can identify stage-specific NSCLC genes. Differentially expressed genes are clustered separately to form up- and downregulated communities that are used as queries to perform enrichment analysis. The results suggest that pathways for early- and late-stage cancers are different. Sets of up- and downregulated genes were submitted to the cMap web resource to identify potential drugs. To achieve high confidence drug prediction, multiple microarray experimental results were merged by performing meta-analysis. The results of a few drug findings are supported by MTT assay or clonogenic assay data. In conclusion, we have been able to assess the potential existing drugs to identify novel anticancer drugs, which may be helpful in drug repositioning discovery for NSCLC.

  8. Combining NMR and X-ray crystallography in fragment-based drug discovery: discovery of highly potent and selective BACE-1 inhibitors.

    Science.gov (United States)

    Wyss, Daniel F; Wang, Yu-Sen; Eaton, Hugh L; Strickland, Corey; Voigt, Johannes H; Zhu, Zhaoning; Stamford, Andrew W

    2012-01-01

    Fragment-based drug discovery (FBDD) has become increasingly popular over the last decade. We review here how we have used highly structure-driven fragment-based approaches to complement more traditional lead discovery to tackle high priority targets and those struggling for leads. Combining biomolecular nuclear magnetic resonance (NMR), X-ray crystallography, and molecular modeling with structure-assisted chemistry and innovative biology as an integrated approach for FBDD can solve very difficult problems, as illustrated in this chapter. Here, a successful FBDD campaign is described that has allowed the development of a clinical candidate for BACE-1, a challenging CNS drug target. Crucial to this achievement were the initial identification of a ligand-efficient isothiourea fragment through target-based NMR screening and the determination of its X-ray crystal structure in complex with BACE-1, which revealed an extensive H-bond network with the two active site aspartate residues. This detailed 3D structural information then enabled the design and validation of novel, chemically stable and accessible heterocyclic acylguanidines as aspartic acid protease inhibitor cores. Structure-assisted fragment hit-to-lead optimization yielded iminoheterocyclic BACE-1 inhibitors that possess desirable molecular properties as potential therapeutic agents to test the amyloid hypothesis of Alzheimer's disease in a clinical setting.

  9. Computational medicinal chemistry in fragment-based drug discovery: what, how and when.

    Science.gov (United States)

    Rabal, Obdulia; Urbano-Cuadrado, Manuel; Oyarzabal, Julen

    2011-01-01

    The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure-activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario - what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.

  10. FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects.

    Science.gov (United States)

    Lagorce, David; Sperandio, Olivier; Galons, Hervé; Miteva, Maria A; Villoutreix, Bruno O

    2008-09-24

    Drug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making. This paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python) based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries. We have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after) experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules) that can be easily tuned.

  11. Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

    Science.gov (United States)

    Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

    2016-08-01

    The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

  12. Discovery of inhibitors of bacterial histidine kinases

    NARCIS (Netherlands)

    Velikova, N.R.

    2014-01-01

    Discovery of Inhibitors of Bacterial Histidine Kinases Summary

    The thesis is on novel antibacterial drug discovery (http://youtu.be/NRMWOGgeysM). Using structure-based and fragment-based drug discovery approach, we have identified small-molecule histidine-kinase

  13. Drug discovery and development tomorrow -- changing the mindset.

    Science.gov (United States)

    Coleman, Robert A

    2009-09-01

    Today's drug discovery and development paradigm is not working, and something needs to be done about it. There is good reason to believe that a move away from reliance on animal surrogates for human subjects in the Pharma Industry's R&D programmes could provide an important step forward. However, no serious move will be made in that direction until there is some hard evidence that it will be rewarded with improved productivity outcomes. The Safer Medicines Trust are proposing that a study be undertaken, involving a range of drugs that have been approved for human use, but have subsequently proved to have limitations in terms of safety and/or efficacy. The aim is to determine the efficiency of a battery of human-based test methods to identify a compound's safety and efficacy profiles, and to compare this with that of the more traditional, largely animal-based methods that were employed in their original development. Should such an approach prove more reliable, the authorities will be faced with important decisions relating to the role of human biological test data in regulatory submissions, while the Pharma Industry will be faced with the key logistical issue of how to acquire the human biomaterials necessary to make possible the routine application of such test methods. 2009 FRAME.

  14. Have there been improvements in Alzheimer's disease drug discovery over the past 5 years?

    Science.gov (United States)

    Cacabelos, Ramón

    2018-06-01

    Alzheimer's disease (AD) is the most important neurodegenerative disorder with a global cost worldwide of over $700 billion. Pharmacological treatment accounts for 10-20% of direct costs; no new drugs have been approved during the past 15 years; and the available medications are not cost-effective. Areas covered: A massive scrutiny of AD-related PubMed publications (ps)(2013-2017) identified 42,053ps of which 8,380 (19.60%) were associated with AD treatments. The most prevalent pharmacological categories included neurotransmitter enhancers (11.38%), multi-target drugs (2.45%), anti-Amyloid agents (13.30%), anti-Tau agents (2.03%), natural products and derivatives (25.58%), novel drugs (8.13%), novel targets (5.66%), other (old) drugs (11.77%), anti-inflammatory drugs (1.20%), neuroprotective peptides (1.25%), stem cell therapy (1.85%), nanocarriers/nanotherapeutics (1.52%), and others (discovery programs, (vi) the updating of regulatory requirements, (vii) the introduction of pharmacogenomics in drug development and personalized treatments, and (viii) the implementation of preventive programs.

  15. Live Cell in Vitro and in Vivo Imaging Applications: Accelerating Drug Discovery

    Directory of Open Access Journals (Sweden)

    Neil O Carragher

    2011-04-01

    Full Text Available Dynamic regulation of specific molecular processes and cellular phenotypes in live cell systems reveal unique insights into cell fate and drug pharmacology that are not gained from traditional fixed endpoint assays. Recent advances in microscopic imaging platform technology combined with the development of novel optical biosensors and sophisticated image analysis solutions have increased the scope of live cell imaging applications in drug discovery. We highlight recent literature examples where live cell imaging has uncovered novel insight into biological mechanism or drug mode-of-action. We survey distinct types of optical biosensors and associated analytical methods for monitoring molecular dynamics, in vitro and in vivo. We describe the recent expansion of live cell imaging into automated target validation and drug screening activities through the development of dedicated brightfield and fluorescence kinetic imaging platforms. We provide specific examples of how temporal profiling of phenotypic response signatures using such kinetic imaging platforms can increase the value of in vitro high-content screening. Finally, we offer a prospective view of how further application and development of live cell imaging technology and reagents can accelerate preclinical lead optimization cycles and enhance the in vitro to in vivo translation of drug candidates.

  16. Assessment of Dengue virus helicase and methyltransferase as targets for fragment-based drug discovery.

    Science.gov (United States)

    Coutard, Bruno; Decroly, Etienne; Li, Changqing; Sharff, Andrew; Lescar, Julien; Bricogne, Gérard; Barral, Karine

    2014-06-01

    Seasonal and pandemic flaviviruses continue to be leading global health concerns. With the view to help drug discovery against Dengue virus (DENV), a fragment-based experimental approach was applied to identify small molecule ligands targeting two main components of the flavivirus replication complex: the NS3 helicase (Hel) and the NS5 mRNA methyltransferase (MTase) domains. A library of 500 drug-like fragments was first screened by thermal-shift assay (TSA) leading to the identification of 36 and 32 fragment hits binding Hel and MTase from DENV, respectively. In a second stage, we set up a fragment-based X-ray crystallographic screening (FBS-X) in order to provide both validated fragment hits and structural binding information. No fragment hit was confirmed for DENV Hel. In contrast, a total of seven fragments were identified as DENV MTase binders and structures of MTase-fragment hit complexes were solved at resolution at least 2.0Å or better. All fragment hits identified contain either a five- or six-membered aromatic ring or both, and three novel binding sites were located on the MTase. To further characterize the fragment hits identified by TSA and FBS-X, we performed enzymatic assays to assess their inhibition effect on the N7- and 2'-O-MTase enzymatic activities: five of these fragment hits inhibit at least one of the two activities with IC50 ranging from 180μM to 9mM. This work validates the FBS-X strategy for identifying new anti-flaviviral hits targeting MTase, while Hel might not be an amenable target for fragment-based drug discovery (FBDD). This approach proved to be a fast and efficient screening method for FBDD target validation and discovery of starting hits for the development of higher affinity molecules that bind to novel allosteric sites. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. The Roles of Water in the Protein Matrix: A Largely Untapped Resource for Drug Discovery.

    Science.gov (United States)

    Spyrakis, Francesca; Ahmed, Mostafa H; Bayden, Alexander S; Cozzini, Pietro; Mozzarelli, Andrea; Kellogg, Glen E

    2017-08-24

    The value of thoroughly understanding the thermodynamics specific to a drug discovery/design study is well known. Over the past decade, the crucial roles of water molecules in protein structure, function, and dynamics have also become increasingly appreciated. This Perspective explores water in the biological environment by adopting its point of view in such phenomena. The prevailing thermodynamic models of the past, where water was seen largely in terms of an entropic gain after its displacement by a ligand, are now known to be much too simplistic. We adopt a set of terminology that describes water molecules as being "hot" and "cold", which we have defined as being easy and difficult to displace, respectively. The basis of these designations, which involve both enthalpic and entropic water contributions, are explored in several classes of biomolecules and structural motifs. The hallmarks for characterizing water molecules are examined, and computational tools for evaluating water-centric thermodynamics are reviewed. This Perspective's summary features guidelines for exploiting water molecules in drug discovery.

  18. Quantum mechanics implementation in drug-design workflows: does it really help?

    Science.gov (United States)

    Arodola, Olayide A; Soliman, Mahmoud Es

    2017-01-01

    The pharmaceutical industry is progressively operating in an era where development costs are constantly under pressure, higher percentages of drugs are demanded, and the drug-discovery process is a trial-and-error run. The profit that flows in with the discovery of new drugs has always been the motivation for the industry to keep up the pace and keep abreast with the endless demand for medicines. The process of finding a molecule that binds to the target protein using in silico tools has made computational chemistry a valuable tool in drug discovery in both academic research and pharmaceutical industry. However, the complexity of many protein-ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. The usefulness of quantum mechanics (QM) in drug-protein interaction cannot be overemphasized; however, this approach has little significance in some empirical methods. In this review, we discuss recent developments in, and application of, QM to medically relevant biomolecules. We critically discuss the different types of QM-based methods and their proposed application to incorporating them into drug-design and -discovery workflows while trying to answer a critical question: are QM-based methods of real help in drug-design and -discovery research and industry?

  19. Seeking Ligand Bias: Assessing GPCR Coupling to Beta-Arrestins for Drug Discovery

    OpenAIRE

    Bohn, Laura M.; McDonald, Patricia H.

    2010-01-01

    G protein-coupled receptors (GPCR) are the major site of action for endogenous hormones and neurotransmitters. Early drug discovery efforts focused on determining whether ligands could engage G protein coupling and subsequently activate or inhibit cognate “second messengers.” Gone are those simple days as we now realize that receptors can also couple βarrestins. As we delve into the complexity of ligand-directed signaling and receptosome scaffolds, we are faced with what may seem like endless...

  20. FAF-Drugs2: Free ADME/tox filtering tool to assist drug discovery and chemical biology projects

    Directory of Open Access Journals (Sweden)

    Miteva Maria A

    2008-09-01

    Full Text Available Abstract Background Drug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making. Results This paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries. Conclusion We have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules that can be easily tuned.

  1. The application of molecular topology for ulcerative colitis drug discovery.

    Science.gov (United States)

    Bellera, Carolina L; Di Ianni, Mauricio E; Talevi, Alan

    2018-01-01

    Although the therapeutic arsenal against ulcerative colitis has greatly expanded (including the revolutionary advent of biologics), there remain patients who are refractory to current medications while the safety of the available therapeutics could also be improved. Molecular topology provides a theoretic framework for the discovery of new therapeutic agents in a very efficient manner, and its applications in the field of ulcerative colitis have slowly begun to flourish. Areas covered: After discussing the basics of molecular topology, the authors review QSAR models focusing on validated targets for the treatment of ulcerative colitis, entirely or partially based on topological descriptors. Expert opinion: The application of molecular topology to ulcerative colitis drug discovery is still very limited, and many of the existing reports seem to be strictly theoretic, with no experimental validation or practical applications. Interestingly, mechanism-independent models based on phenotypic responses have recently been reported. Such models are in agreement with the recent interest raised by network pharmacology as a potential solution for complex disorders. These and other similar studies applying molecular topology suggest that some therapeutic categories may present a 'topological pattern' that goes beyond a specific mechanism of action.

  2. Prediction of potential drug targets based on simple sequence properties

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    Lai Luhua

    2007-09-01

    Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

  3. Improving the quality of biomarker discovery research: the right samples and enough of them.

    Science.gov (United States)

    Pepe, Margaret S; Li, Christopher I; Feng, Ziding

    2015-06-01

    Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

  4. Opportunities and challenges provided by cloud repositories for bioinformatics-enabled drug discovery.

    Science.gov (United States)

    Dalpé, Gratien; Joly, Yann

    2014-09-01

    Healthcare-related bioinformatics databases are increasingly offering the possibility to maintain, organize, and distribute DNA sequencing data. Different national and international institutions are currently hosting such databases that offer researchers website platforms where they can obtain sequencing data on which they can perform different types of analysis. Until recently, this process remained mostly one-dimensional, with most analysis concentrated on a limited amount of data. However, newer genome sequencing technology is producing a huge amount of data that current computer facilities are unable to handle. An alternative approach has been to start adopting cloud computing services for combining the information embedded in genomic and model system biology data, patient healthcare records, and clinical trials' data. In this new technological paradigm, researchers use virtual space and computing power from existing commercial or not-for-profit cloud service providers to access, store, and analyze data via different application programming interfaces. Cloud services are an alternative to the need of larger data storage; however, they raise different ethical, legal, and social issues. The purpose of this Commentary is to summarize how cloud computing can contribute to bioinformatics-based drug discovery and to highlight some of the outstanding legal, ethical, and social issues that are inherent in the use of cloud services. © 2014 Wiley Periodicals, Inc.

  5. Cardiac Arrhythmia: In vivo screening in the zebrafish to overcome complexity in drug discovery.

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    Macrae, Calum A

    2010-07-01

    IMPORTANCE OF THE FIELD: Cardiac arrhythmias remain a major challenge for modern drug discovery. Clinical events are paroxysmal, often rare and may be asymptomatic until a highly morbid complication. Target selection is often based on limited information and though highly specific agents are identified in screening, the final efficacy is often compromised by unanticipated systemic responses, a narrow therapeutic index and substantial toxicities. AREAS COVERED IN THIS REVIEW: Our understanding of complexity of arrhythmogenesis has grown dramatically over the last two decades, and the range of potential disease mechanisms now includes pathways previously thought only tangentially involved in arrhythmia. This review surveys the literature on arrhythmia mechanisms from 1965 to the present day, outlines the complex biology underlying potentially each and every rhythm disturbance, and highlights the problems for rational target identification. The rationale for in vivo screening is described and the utility of the zebrafish for this approach and for complementary work in functional genomics is discussed. Current limitations of the model in this setting and the need for careful validation in new disease areas are also described. WHAT THE READER WILL GAIN: An overview of the complex mechanisms underlying most clinical arrhythmias, and insight into the limits of ion channel conductances as drug targets. An introduction to the zebrafish as a model organism, in particular for cardiovascular biology. Potential approaches to overcoming the hurdles to drug discovery in the face of complex biology including in vivo screening of zebrafish genetic disease models. TAKE HOME MESSAGE: In vivo screening in faithful disease models allows the effects of drugs on integrative physiology and disease biology to be captured during the screening process, in a manner agnostic to potential drug target or targets. This systematic strategy bypasses current gaps in our understanding of disease

  6. pH-Dependent solubility and permeability criteria for provisional biopharmaceutics classification (BCS and BDDCS) in early drug discovery.

    Science.gov (United States)

    Varma, Manthena V; Gardner, Iain; Steyn, Stefanus J; Nkansah, Paul; Rotter, Charles J; Whitney-Pickett, Carrie; Zhang, Hui; Di, Li; Cram, Michael; Fenner, Katherine S; El-Kattan, Ayman F

    2012-05-07

    The Biopharmaceutics Classification System (BCS) is a scientific framework that provides a basis for predicting the oral absorption of drugs. These concepts have been extended in the Biopharmaceutics Drug Disposition Classification System (BDDCS) to explain the potential mechanism of drug clearance and understand the effects of uptake and efflux transporters on absorption, distribution, metabolism, and elimination. The objective of present work is to establish criteria for provisional biopharmaceutics classification using pH-dependent passive permeability and aqueous solubility data generated from high throughput screening methodologies in drug discovery settings. The apparent permeability across monolayers of clonal cell line of Madin-Darby canine kidney cells, selected for low endogenous efflux transporter expression, was measured for a set of 105 drugs, with known BCS and BDDCS class. The permeability at apical pH 6.5 for acidic drugs and at pH 7.4 for nonacidic drugs showed a good correlation with the fraction absorbed in human (Fa). Receiver operating characteristic (ROC) curve analysis was utilized to define the permeability class boundary. At permeability ≥ 5 × 10(-6) cm/s, the accuracy of predicting Fa of ≥ 0.90 was 87%. Also, this cutoff showed more than 80% sensitivity and specificity in predicting the literature permeability classes (BCS), and the metabolism classes (BDDCS). The equilibrium solubility of a subset of 49 drugs was measured in pH 1.2 medium, pH 6.5 phosphate buffer, and in FaSSIF medium (pH 6.5). Although dose was not considered, good concordance of the measured solubility with BCS and BDDCS solubility class was achieved, when solubility at pH 1.2 was used for acidic compounds and FaSSIF solubility was used for basic, neutral, and zwitterionic compounds. Using a cutoff of 200 μg/mL, the data set suggested a 93% sensitivity and 86% specificity in predicting both the BCS and BDDCS solubility classes. In conclusion, this study identified

  7. Anti-amyloid aggregation activity of novel carotenoids: implications for Alzheimer’s drug discovery

    Directory of Open Access Journals (Sweden)

    Lakey-Beitia J

    2017-05-01

    Full Text Available Johant Lakey-Beitia,1,2 Deborah Doens,2,3 D Jagadeesh Kumar,4 Enrique Murillo,5 Patricia L Fernandez,3 KS Rao,6 Armando A Durant-Archibold1,5 1Center for Biodiversity and Drug Discovery, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP, Panama, Republic of Panama; 2Department of Biotechnology, Acharya Nagarjuna University, Guntur, India; 3Center for Molecular and Cellular Biology of Diseases, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP, Panama, Republic of Panama; 4Department of Biotechnology, Sir M Visvesvaraya Institute of Technology, Bangalore, India; 5Department of Biochemistry, College of Natural, Exact Sciences and Technology, University of Panama, Panama, Republic of Panama; 6Center for Neuroscience, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP, Panama, Republic of Panama Abstract: Alzheimer’s disease (AD is the leading cause of dementia, affecting approximately 33.5 million people worldwide. Aging is the main risk factor associated with AD. Drug discovery based on nutraceutical molecules for prevention and treatment of AD is a growing topic. In this sense, carotenoids are phytochemicals present mainly in fruits and vegetables with reported benefits for human health. In this research, the anti-amyloidogenic activity of three carotenoids, cryptocapsin, cryptocapsin-5,6-epoxide, and zeaxanthin, was assessed. Cryptocapsin showed the highest bioactivity, while cryptocapsin-5,6-epoxide and zeaxanthin exhibited similar activity on anti-aggregation assays. Molecular modeling analysis revealed that the evaluated carotenoids might follow two mechanisms for inhibiting Aβ aggregation: by preventing the formation of the fibril and through disruption of the Aβ aggregates. Our studies provided evidence that cryptocapsin, cryptocapsin-5,6-epoxide, and zeaxanthin have anti-amyloidogenic potential and could be used for

  8. Allosteric modulation of endogenous metabolites as an avenue for drug discovery.

    Science.gov (United States)

    Wootten, Denise; Savage, Emilia E; Valant, Celine; May, Lauren T; Sloop, Kyle W; Ficorilli, James; Showalter, Aaron D; Willard, Francis S; Christopoulos, Arthur; Sexton, Patrick M

    2012-08-01

    G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors and a key drug target class. Recently, allosteric drugs that can co-bind with and modulate the activity of the endogenous ligand(s) for the receptor have become a major focus of the pharmaceutical and biotechnology industry for the development of novel GPCR therapeutic agents. This class of drugs has distinct properties compared with drugs targeting the endogenous (orthosteric) ligand-binding site that include the ability to sculpt cellular signaling and to respond differently in the presence of discrete orthosteric ligands, a behavior termed "probe dependence." Here, using cell signaling assays combined with ex vivo and in vivo studies of insulin secretion, we demonstrate that allosteric ligands can cause marked potentiation of previously "inert" metabolic products of neurotransmitters and peptide hormones, a novel consequence of the phenomenon of probe dependence. Indeed, at the muscarinic M(2) receptor and glucagon-like peptide 1 (GLP-1) receptor, allosteric potentiation of the metabolites, choline and GLP-1(9-36)NH(2), respectively, was ~100-fold and up to 200-fold greater than that seen with the physiological signaling molecules acetylcholine and GLP-1(7-36)NH(2). Modulation of GLP-1(9-36)NH(2) was also demonstrated in ex vivo and in vivo assays of insulin secretion. This work opens up new avenues for allosteric drug discovery by directly targeting modulation of metabolites, but it also identifies a behavior that could contribute to unexpected clinical outcomes if interaction of allosteric drugs with metabolites is not part of their preclinical assessment.

  9. Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

    Science.gov (United States)

    Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

    2017-12-04

    Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further

  10. Fumigation in Ayurveda: potential strategy for drug discovery and drug delivery.

    Science.gov (United States)

    Vishnuprasad, Chethala N; Pradeep, Nediyamparambu Sukumaran; Cho, Yong Woo; Gangadharan, Geethalayam Gopinathan; Han, Sung Soo

    2013-09-16

    Ayurveda has its unique perceptions and resultant methodologies for defining and treating human diseases. Fumigation therapy is one of the several treatment methods described in Ayurveda whereby fumes produced from defined drug formulations are inhaled by patients. This therapeutic procedure offers promising research opportunities from phytochemical and ethnopharmacological viewpoints, however, it remains under-noticed. Considering these facts, this review is primarily aimed at introducing said Ayurvedic fumigation therapy and discussing its scientific gaps and future challenges. A search of multiple bibliographical databases and traditional Ayurvedic text books was conducted and the articles analyzed under various key themes, e.g., Ayurvedic fumigation, fumigation therapy, medicinal fumigation, inhalation of drugs and aerosol therapy. Ayurveda recommends fumigation as a method of sterilization and therapeutic procedure for various human diseases including microbial infections and psychological disorders. However, it has not gained much attention as a prospective field with multiple research opportunities. It is necessary to have a more detailed and systematic investigation of the phytochemical and pharmacodynamic properties of Ayurvedic fumigation therapy in order to facilitate the identification of novel bioactive compounds and more effective drug administration methods. © 2013 Elsevier Ireland Ltd. All rights reserved.

  11. Small Molecules from Nature Targeting G-Protein Coupled Cannabinoid Receptors: Potential Leads for Drug Discovery and Development

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    Charu Sharma

    2015-01-01

    Full Text Available The cannabinoid molecules are derived from Cannabis sativa plant which acts on the cannabinoid receptors types 1 and 2 (CB1 and CB2 which have been explored as potential therapeutic targets for drug discovery and development. Currently, there are numerous cannabinoid based synthetic drugs used in clinical practice like the popular ones such as nabilone, dronabinol, and Δ9-tetrahydrocannabinol mediates its action through CB1/CB2 receptors. However, these synthetic based Cannabis derived compounds are known to exert adverse psychiatric effect and have also been exploited for drug abuse. This encourages us to find out an alternative and safe drug with the least psychiatric adverse effects. In recent years, many phytocannabinoids have been isolated from plants other than Cannabis. Several studies have shown that these phytocannabinoids show affinity, potency, selectivity, and efficacy towards cannabinoid receptors and inhibit endocannabinoid metabolizing enzymes, thus reducing hyperactivity of endocannabinoid systems. Also, these naturally derived molecules possess the least adverse effects opposed to the synthetically derived cannabinoids. Therefore, the plant based cannabinoid molecules proved to be promising and emerging therapeutic alternative. The present review provides an overview of therapeutic potential of ligands and plants modulating cannabinoid receptors that may be of interest to pharmaceutical industry in search of new and safer drug discovery and development for future therapeutics.

  12. Organ/body-on-a-chip based on microfluidic technology for drug discovery.

    Science.gov (United States)

    Kimura, Hiroshi; Sakai, Yasuyuki; Fujii, Teruo

    2018-02-01

    Although animal experiments are indispensable for preclinical screening in the drug discovery process, various issues such as ethical considerations and species differences remain. To solve these issues, cell-based assays using human-derived cells have been actively pursued. However, it remains difficult to accurately predict drug efficacy, toxicity, and organs interactions, because cultivated cells often do not retain their original organ functions and morphologies in conventional in vitro cell culture systems. In the μTAS research field, which is a part of biochemical engineering, the technologies of organ-on-a-chip, based on microfluidic devices built using microfabrication, have been widely studied recently as a novel in vitro organ model. Since it is possible to physically and chemically mimic the in vitro environment by using microfluidic device technology, maintenance of cellular function and morphology, and replication of organ interactions can be realized using organ-on-a-chip devices. So far, functions of various organs and tissues, such as the lung, liver, kidney, and gut have been reproduced as in vitro models. Furthermore, a body-on-a-chip, integrating multi organ functions on a microfluidic device, has also been proposed for prediction of organ interactions. We herein provide a background of microfluidic systems, organ-on-a-chip, Body-on-a-chip technologies, and their challenges in the future. Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

  13. Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics.

    Science.gov (United States)

    de Lange, Elizabeth C M; van den Brink, Willem; Yamamoto, Yumi; de Witte, Wilhelmus E A; Wong, Yin Cheong

    2017-12-01

    CNS drug development has been hampered by inadequate consideration of CNS pharmacokinetic (PK), pharmacodynamics (PD) and disease complexity (reductionist approach). Improvement is required via integrative model-based approaches. Areas covered: The authors summarize factors that have played a role in the high attrition rate of CNS compounds. Recent advances in CNS research and drug discovery are presented, especially with regard to assessment of relevant neuro-PK parameters. Suggestions for further improvements are also discussed. Expert opinion: Understanding time- and condition dependent interrelationships between neuro-PK and neuro-PD processes is key to predictions in different conditions. As a first screen, it is suggested to use in silico/in vitro derived molecular properties of candidate compounds and predict concentration-time profiles of compounds in multiple compartments of the human CNS, using time-course based physiology-based (PB) PK models. Then, for selected compounds, one can include in vitro drug-target binding kinetics to predict target occupancy (TO)-time profiles in humans. This will improve neuro-PD prediction. Furthermore, a pharmaco-omics approach is suggested, providing multilevel and paralleled data on systems processes from individuals in a systems-wide manner. Thus, clinical trials will be better informed, using fewer animals, while also, needing fewer individuals and samples per individual for proof of concept in humans.

  14. New Perspectives on How to Discover Drugs from Herbal Medicines: CAM's Outstanding Contribution to Modern Therapeutics.

    Science.gov (United States)

    Pan, Si-Yuan; Zhou, Shu-Feng; Gao, Si-Hua; Yu, Zhi-Ling; Zhang, Shuo-Feng; Tang, Min-Ke; Sun, Jian-Ning; Ma, Dik-Lung; Han, Yi-Fan; Fong, Wang-Fun; Ko, Kam-Ming

    2013-01-01

    With tens of thousands of plant species on earth, we are endowed with an enormous wealth of medicinal remedies from Mother Nature. Natural products and their derivatives represent more than 50% of all the drugs in modern therapeutics. Because of the low success rate and huge capital investment need, the research and development of conventional drugs are very costly and difficult. Over the past few decades, researchers have focused on drug discovery from herbal medicines or botanical sources, an important group of complementary and alternative medicine (CAM) therapy. With a long history of herbal usage for the clinical management of a variety of diseases in indigenous cultures, the success rate of developing a new drug from herbal medicinal preparations should, in theory, be higher than that from chemical synthesis. While the endeavor for drug discovery from herbal medicines is "experience driven," the search for a therapeutically useful synthetic drug, like "looking for a needle in a haystack," is a daunting task. In this paper, we first illustrated various approaches of drug discovery from herbal medicines. Typical examples of successful drug discovery from botanical sources were given. In addition, problems in drug discovery from herbal medicines were described and possible solutions were proposed. The prospect of drug discovery from herbal medicines in the postgenomic era was made with the provision of future directions in this area of drug development.

  15. Flexible End2End Workflow Automation of Hit-Discovery Research.

    Science.gov (United States)

    Holzmüller-Laue, Silke; Göde, Bernd; Thurow, Kerstin

    2014-08-01

    The article considers a new approach of more complex laboratory automation at the workflow layer. The authors purpose the automation of end2end workflows. The combination of all relevant subprocesses-whether automated or manually performed, independently, and in which organizational unit-results in end2end processes that include all result dependencies. The end2end approach focuses on not only the classical experiments in synthesis or screening, but also on auxiliary processes such as the production and storage of chemicals, cell culturing, and maintenance as well as preparatory activities and analyses of experiments. Furthermore, the connection of control flow and data flow in the same process model leads to reducing of effort of the data transfer between the involved systems, including the necessary data transformations. This end2end laboratory automation can be realized effectively with the modern methods of business process management (BPM). This approach is based on a new standardization of the process-modeling notation Business Process Model and Notation 2.0. In drug discovery, several scientific disciplines act together with manifold modern methods, technologies, and a wide range of automated instruments for the discovery and design of target-based drugs. The article discusses the novel BPM-based automation concept with an implemented example of a high-throughput screening of previously synthesized compound libraries. © 2014 Society for Laboratory Automation and Screening.

  16. The 4th Euro-Mediterranean Conference of Natural Products and Drug Discovery: Back to Mother Nature (BioNat-IV, Cairo/Sharm El-Sheikh, Egypt, March 3–7, 2015

    Directory of Open Access Journals (Sweden)

    Ashraf A. Khalil

    2016-04-01

    Full Text Available The 4th Euro-Mediterranean Conference of Natural Products and Drug Discovery: Back to Mother Nature (BioNat-IV was recently (from March 3rd through 7th, 2015 convened in Cairo and Sharm El-Sheikh along the Red Sea coast of Egypt. Overall, the meeting provided a platform for scientists from different nations to discuss emerging ideas that focused on cell signaling in cancer; the pathogenesis of autoimmune diseases; the identification and use of natural products as well as novel drug delivery approaches for the treatment of cancer, arthritis, diabetes, tuberculosis, fungal infection, etc.; and untapped or unconventional sources for natural products. This fourth in a row conference tried to bridge the gap not only between basic research and clinical applications, but also between developed nations and developing countries. With the continuing success of these past meetings, the fifth Euro-Mediterranean Conference of Natural Products and Drug Discovery (BioNat-V is slated to be in February 2017.

  17. Systems pharmacology-based drug discovery for marine resources: an example using sea cucumber (Holothurians).

    Science.gov (United States)

    Guo, Yingying; Ding, Yan; Xu, Feifei; Liu, Baoyue; Kou, Zinong; Xiao, Wei; Zhu, Jingbo

    2015-05-13

    Sea cucumber, a kind of marine animal, have long been utilized as tonic and traditional remedies in the Middle East and Asia because of its effectiveness against hypertension, asthma, rheumatism, cuts and burns, impotence, and constipation. In this study, an overall study performed on sea cucumber was used as an example to show drug discovery from marine resource by using systems pharmacology model. The value of marine natural resources has been extensively considered because these resources can be potentially used to treat and prevent human diseases. However, the discovery of drugs from oceans is difficult, because of complex environments in terms of composition and active mechanisms. Thus, a comprehensive systems approach which could discover active constituents and their targets from marine resource, understand the biological basis for their pharmacological properties is necessary. In this study, a feasible pharmacological model based on systems pharmacology was established to investigate marine medicine by incorporating active compound screening, target identification, and network and pathway analysis. As a result, 106 candidate components of sea cucumber and 26 potential targets were identified. Furthermore, the functions of sea cucumber in health improvement and disease treatment were elucidated in a holistic way based on the established compound-target and target-disease networks, and incorporated pathways. This study established a novel strategy that could be used to explore specific active mechanisms and discover new drugs from marine sources. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery.

    Science.gov (United States)

    Pérot, Stéphanie; Sperandio, Olivier; Miteva, Maria A; Camproux, Anne-Claude; Villoutreix, Bruno O

    2010-08-01

    Detection, comparison and analyses of binding pockets are pivotal to structure-based drug design endeavors, from hit identification, screening of exosites and de-orphanization of protein functions to the anticipation of specific and non-specific binding to off- and anti-targets. Here, we analyze protein-ligand complexes and discuss methods that assist binding site identification, prediction of druggability and binding site comparison. The full potential of pockets is yet to be harnessed, and we envision that better understanding of the pocket space will have far-reaching implications in the field of drug discovery, such as the design of pocket-specific compound libraries and scoring functions.

  19. A review of human pluripotent stem cell-derived cardiomyocytes for high-throughput drug discovery, cardiotoxicity screening, and publication standards.

    Science.gov (United States)

    Mordwinkin, Nicholas M; Burridge, Paul W; Wu, Joseph C

    2013-02-01

    Drug attrition rates have increased in past years, resulting in growing costs for the pharmaceutical industry and consumers. The reasons for this include the lack of in vitro models that correlate with clinical results and poor preclinical toxicity screening assays. The in vitro production of human cardiac progenitor cells and cardiomyocytes from human pluripotent stem cells provides an amenable source of cells for applications in drug discovery, disease modeling, regenerative medicine, and cardiotoxicity screening. In addition, the ability to derive human-induced pluripotent stem cells from somatic tissues, combined with current high-throughput screening and pharmacogenomics, may help realize the use of these cells to fulfill the potential of personalized medicine. In this review, we discuss the use of pluripotent stem cell-derived cardiomyocytes for drug discovery and cardiotoxicity screening, as well as current hurdles that must be overcome for wider clinical applications of this promising approach.

  20. The Biomedical Resource Ontology (BRO) to enable resource discovery in clinical and translational research.

    Science.gov (United States)

    Tenenbaum, Jessica D; Whetzel, Patricia L; Anderson, Kent; Borromeo, Charles D; Dinov, Ivo D; Gabriel, Davera; Kirschner, Beth; Mirel, Barbara; Morris, Tim; Noy, Natasha; Nyulas, Csongor; Rubenson, David; Saxman, Paul R; Singh, Harpreet; Whelan, Nancy; Wright, Zach; Athey, Brian D; Becich, Michael J; Ginsburg, Geoffrey S; Musen, Mark A; Smith, Kevin A; Tarantal, Alice F; Rubin, Daniel L; Lyster, Peter

    2011-02-01

    The biomedical research community relies on a diverse set of resources, both within their own institutions and at other research centers. In addition, an increasing number of shared electronic resources have been developed. Without effective means to locate and query these resources, it is challenging, if not impossible, for investigators to be aware of the myriad resources available, or to effectively perform resource discovery when the need arises. In this paper, we describe the development and use of the Biomedical Resource Ontology (BRO) to enable semantic annotation and discovery of biomedical resources. We also describe the Resource Discovery System (RDS) which is a federated, inter-institutional pilot project that uses the BRO to facilitate resource discovery on the Internet. Through the RDS framework and its associated Biositemaps infrastructure, the BRO facilitates semantic search and discovery of biomedical resources, breaking down barriers and streamlining scientific research that will improve human health. Copyright © 2010 Elsevier Inc. All rights reserved.

  1. New Perspectives on Chinese Herbal Medicine (Zhong-Yao) Research and Development

    Science.gov (United States)

    Pan, Si-Yuan; Chen, Si-Bao; Dong, Hong-Guang; Yu, Zhi-Ling; Dong, Ji-Cui; Long, Zhi-Xian; Fong, Wang-Fun; Han, Yi-Fan; Ko, Kam-Ming

    2011-01-01

    Synthetic chemical drugs, while being efficacious in the clinical management of many diseases, are often associated with undesirable side effects in patients. It is now clear that the need of therapeutic intervention in many clinical conditions cannot be satisfactorily met by synthetic chemical drugs. Since the research and development of new chemical drugs remain time-consuming, capital-intensive and risky, much effort has been put in the search for alternative routes for drug discovery in China. This narrative review illustrates various approaches to the research and drug discovery in Chinese herbal medicine. Although this article focuses on Chinese traditional drugs, it is also conducive to the development of other traditional remedies and innovative drug discovery. PMID:21785622

  2. New Perspectives on Chinese Herbal Medicine (Zhong-Yao Research and Development

    Directory of Open Access Journals (Sweden)

    Si-Yuan Pan

    2011-01-01

    Full Text Available Synthetic chemical drugs, while being efficacious in the clinical management of many diseases, are often associated with undesirable side effects in patients. It is now clear that the need of therapeutic intervention in many clinical conditions cannot be satisfactorily met by synthetic chemical drugs. Since the research and development of new chemical drugs remain time-consuming, capital-intensive and risky, much effort has been put in the search for alternative routes for drug discovery in China. This narrative review illustrates various approaches to the research and drug discovery in Chinese herbal medicine. Although this article focuses on Chinese traditional drugs, it is also conducive to the development of other traditional remedies and innovative drug discovery.

  3. MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development.

    Science.gov (United States)

    Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

    2015-01-01

    Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/.

  4. Biomarkers: in medicine, drug discovery, and environmental health

    National Research Council Canada - National Science Library

    Vaidya, Vishal S; Bonventre, Joseph V

    2010-01-01

    ... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

  5. MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

    Science.gov (United States)

    Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology.

  6. Cross-pollination of research findings, although uncommon, may accelerate discovery of human disease genes

    Directory of Open Access Journals (Sweden)

    Duda Marlena

    2012-11-01

    Full Text Available Abstract Background Technological leaps in genome sequencing have resulted in a surge in discovery of human disease genes. These discoveries have led to increased clarity on the molecular pathology of disease and have also demonstrated considerable overlap in the genetic roots of human diseases. In light of this large genetic overlap, we tested whether cross-disease research approaches lead to faster, more impactful discoveries. Methods We leveraged several gene-disease association databases to calculate a Mutual Citation Score (MCS for 10,853 pairs of genetically related diseases to measure the frequency of cross-citation between research fields. To assess the importance of cooperative research, we computed an Individual Disease Cooperation Score (ICS and the average publication rate for each disease. Results For all disease pairs with one gene in common, we found that the degree of genetic overlap was a poor predictor of cooperation (r2=0.3198 and that the vast majority of disease pairs (89.56% never cited previous discoveries of the same gene in a different disease, irrespective of the level of genetic similarity between the diseases. A fraction (0.25% of the pairs demonstrated cross-citation in greater than 5% of their published genetic discoveries and 0.037% cross-referenced discoveries more than 10% of the time. We found strong positive correlations between ICS and publication rate (r2=0.7931, and an even stronger correlation between the publication rate and the number of cross-referenced diseases (r2=0.8585. These results suggested that cross-disease research may have the potential to yield novel discoveries at a faster pace than singular disease research. Conclusions Our findings suggest that the frequency of cross-disease study is low despite the high level of genetic similarity among many human diseases, and that collaborative methods may accelerate and increase the impact of new genetic discoveries. Until we have a better

  7. Academic-Pharma drug discovery alliances: seeking ways to eliminate the valley of death.

    Science.gov (United States)

    Hammonds, Tim

    2015-01-01

    Industrial pharmaceutical companies (Pharma) share a common goal with academic scientists (Academia) in that they wish to create an environment in which patients are treated for diseases with ever more effective therapies. As disease biology has proven to be ever more complex and money and new drugs are becoming more elusive, Pharma and Academia are reaching toward each other with ever greater collaborative intent. There are a growing number of collaboration models that allow scientists to work together and profit from the creation of new drugs. Here I give a personal view of how we came to where we are, present an overview of a number of these models and look to the future in terms of running successful discovery alliances.

  8. An evolutionary perspective on drug discovery in the plant genus Euphorbia L. (Euphorbiaceae)

    DEFF Research Database (Denmark)

    Ernst, Madeleine

    herbivory and physical stresses or to attract pollinators. Consequently, specializedmetabolites, as well as plants used in traditional medicine, are not randomly distributed across phylogenetictrees. Evolutionary approaches to plant-based drug discovery suggest that this informationcan be used to guide...... healthcarethreats, urge for systematic and time-efficient approaches in finding new drug candidates. Manydrugs are derived from plant specialized metabolites, chemical compounds, which are synthesizedby the plants in response to evolutionary adaptation to environmental and ecological factors, for example,to combat...... evolution and diversification. Also, Euphorbia species producean often chemically highly diverse latex exhibiting an exceptional number of biological activities withpharmaceutical interest. In this PhD project, the genus Euphorbia was chosen as a model group forstudying evolutionary approaches to plant...

  9. In silico studies in drug research against neurodegenerative diseases.

    Science.gov (United States)

    Makhouri, Farahnaz Rezaei; Ghasemi, Jahan B

    2017-08-22

    Neurodegenerative diseases such as Alzheimer's disease (AD), progressive neurodegenerative forms of Huntington's disease, Parkinson's disease (PD), amyotrophic lateral sclerosis, spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective dysfunction and degeneration of neurons and axons in the central nervous system (CNS). Computer-aided or in silico design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays. In the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches. Neurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  10. Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power?

    Science.gov (United States)

    Zuberi, Aamir; Lutz, Cathleen

    2016-01-01

    systems, are synergistic and serve to make the mouse a better model for biomedical research, enhancing the potential for preclinical drug discovery and personalized medicine. PMID:28053071

  11. Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power?

    Science.gov (United States)

    Zuberi, Aamir; Lutz, Cathleen

    2016-12-01

    , are synergistic and serve to make the mouse a better model for biomedical research, enhancing the potential for preclinical drug discovery and personalized medicine. © The Author 2016. Published by Oxford University Press.

  12. Structure-based drug discovery for combating influenza virus by targeting the PA-PB1 interaction.

    Science.gov (United States)

    Watanabe, Ken; Ishikawa, Takeshi; Otaki, Hiroki; Mizuta, Satoshi; Hamada, Tsuyoshi; Nakagaki, Takehiro; Ishibashi, Daisuke; Urata, Shuzo; Yasuda, Jiro; Tanaka, Yoshimasa; Nishida, Noriyuki

    2017-08-25

    Influenza virus infections are serious public health concerns throughout the world. The development of compounds with novel mechanisms of action is urgently required due to the emergence of viruses with resistance to the currently-approved anti-influenza viral drugs. We performed in silico screening using a structure-based drug discovery algorithm called Nagasaki University Docking Engine (NUDE), which is optimised for a GPU-based supercomputer (DEstination for Gpu Intensive MAchine; DEGIMA), by targeting influenza viral PA protein. The compounds selected by NUDE were tested for anti-influenza virus activity using a cell-based assay. The most potent compound, designated as PA-49, is a medium-sized quinolinone derivative bearing a tetrazole moiety, and it inhibited the replication of influenza virus A/WSN/33 at a half maximal inhibitory concentration of 0.47 μM. PA-49 has the ability to bind PA and its anti-influenza activity was promising against various influenza strains, including a clinical isolate of A(H1N1)pdm09 and type B viruses. The docking simulation suggested that PA-49 interrupts the PA-PB1 interface where important amino acids are mostly conserved in the virus strains tested, suggesting the strain independent utility. Because our NUDE/DEGIMA system is rapid and efficient, it may help effective drug discovery against the influenza virus and other emerging viruses.

  13. Novel opportunities for computational biology and sociology in drug discovery☆

    Science.gov (United States)

    Yao, Lixia; Evans, James A.; Rzhetsky, Andrey

    2013-01-01

    Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy–industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies. PMID:20349528

  14. Drug Repurposing Is a New Opportunity for Developing Drugs against Neuropsychiatric Disorders

    Directory of Open Access Journals (Sweden)

    Hyeong-Min Lee

    2016-01-01

    Full Text Available Better the drugs you know than the drugs you do not know. Drug repurposing is a promising, fast, and cost effective method that can overcome traditional de novo drug discovery and development challenges of targeting neuropsychiatric and other disorders. Drug discovery and development targeting neuropsychiatric disorders are complicated because of the limitations in understanding pathophysiological phenomena. In addition, traditional de novo drug discovery and development are risky, expensive, and time-consuming processes. One alternative approach, drug repurposing, has emerged taking advantage of off-target effects of the existing drugs. In order to identify new opportunities for the existing drugs, it is essential for us to understand the mechanisms of action of drugs, both biologically and pharmacologically. By doing this, drug repurposing would be a more effective method to develop drugs against neuropsychiatric and other disorders. Here, we review the difficulties in drug discovery and development in neuropsychiatric disorders and the extent and perspectives of drug repurposing.

  15. Assessing the structural conservation of protein pockets to study functional and allosteric sites: implications for drug discovery

    Directory of Open Access Journals (Sweden)

    Daura Xavier

    2010-03-01

    Full Text Available Abstract Background With the classical, active-site oriented drug-development approach reaching its limits, protein ligand-binding sites in general and allosteric sites in particular are increasingly attracting the interest of medicinal chemists in the search for new types of targets and strategies to drug development. Given that allostery represents one of the most common and powerful means to regulate protein function, the traditional drug discovery approach of targeting active sites can be extended by targeting allosteric or regulatory protein pockets that may allow the discovery of not only novel drug-like inhibitors, but activators as well. The wealth of available protein structural data can be exploited to further increase our understanding of allosterism, which in turn may have therapeutic applications. A first step in this direction is to identify and characterize putative effector sites that may be present in already available structural data. Results We performed a large-scale study of protein cavities as potential allosteric and functional sites, by integrating publicly available information on protein sequences, structures and active sites for more than a thousand protein families. By identifying common pockets across different structures of the same protein family we developed a method to measure the pocket's structural conservation. The method was first parameterized using known active sites. We characterized the predicted pockets in terms of sequence and structural conservation, backbone flexibility and electrostatic potential. Although these different measures do not tend to correlate, their combination is useful in selecting functional and regulatory sites, as a detailed analysis of a handful of protein families shows. We finally estimated the numbers of potential allosteric or regulatory pockets that may be present in the data set, finding that pockets with putative functional and effector characteristics are widespread across

  16. Using ChEMBL web services for building applications and data processing workflows relevant to drug discovery.

    Science.gov (United States)

    Nowotka, Michał M; Gaulton, Anna; Mendez, David; Bento, A Patricia; Hersey, Anne; Leach, Andrew

    2017-08-01

    ChEMBL is a manually curated database of bioactivity data on small drug-like molecules, used by drug discovery scientists. Among many access methods, a REST API provides programmatic access, allowing the remote retrieval of ChEMBL data and its integration into other applications. This approach allows scientists to move from a world where they go to the ChEMBL web site to search for relevant data, to one where ChEMBL data can be simply integrated into their everyday tools and work environment. Areas covered: This review highlights some of the audiences who may benefit from using the ChEMBL API, and the goals they can address, through the description of several use cases. The examples cover a team communication tool (Slack), a data analytics platform (KNIME), batch job management software (Luigi) and Rich Internet Applications. Expert opinion: The advent of web technologies, cloud computing and micro services oriented architectures have made REST APIs an essential ingredient of modern software development models. The widespread availability of tools consuming RESTful resources have made them useful for many groups of users. The ChEMBL API is a valuable resource of drug discovery bioactivity data for professional chemists, chemistry students, data scientists, scientific and web developers.

  17. New Perspectives on How to Discover Drugs from Herbal Medicines: CAM's Outstanding Contribution to Modern Therapeutics

    Directory of Open Access Journals (Sweden)

    Si-Yuan Pan

    2013-01-01

    Full Text Available With tens of thousands of plant species on earth, we are endowed with an enormous wealth of medicinal remedies from Mother Nature. Natural products and their derivatives represent more than 50% of all the drugs in modern therapeutics. Because of the low success rate and huge capital investment need, the research and development of conventional drugs are very costly and difficult. Over the past few decades, researchers have focused on drug discovery from herbal medicines or botanical sources, an important group of complementary and alternative medicine (CAM therapy. With a long history of herbal usage for the clinical management of a variety of diseases in indigenous cultures, the success rate of developing a new drug from herbal medicinal preparations should, in theory, be higher than that from chemical synthesis. While the endeavor for drug discovery from herbal medicines is “experience driven,” the search for a therapeutically useful synthetic drug, like “looking for a needle in a haystack,” is a daunting task. In this paper, we first illustrated various approaches of drug discovery from herbal medicines. Typical examples of successful drug discovery from botanical sources were given. In addition, problems in drug discovery from herbal medicines were described and possible solutions were proposed. The prospect of drug discovery from herbal medicines in the postgenomic era was made with the provision of future directions in this area of drug development.

  18. New Perspectives on How to Discover Drugs from Herbal Medicines: CAM's Outstanding Contribution to Modern Therapeutics

    Science.gov (United States)

    Pan, Si-Yuan; Zhou, Shu-Feng; Gao, Si-Hua; Yu, Zhi-Ling; Zhang, Shuo-Feng; Tang, Min-Ke; Sun, Jian-Ning; Han, Yi-Fan; Fong, Wang-Fun; Ko, Kam-Ming

    2013-01-01

    With tens of thousands of plant species on earth, we are endowed with an enormous wealth of medicinal remedies from Mother Nature. Natural products and their derivatives represent more than 50% of all the drugs in modern therapeutics. Because of the low success rate and huge capital investment need, the research and development of conventional drugs are very costly and difficult. Over the past few decades, researchers have focused on drug discovery from herbal medicines or botanical sources, an important group of complementary and alternative medicine (CAM) therapy. With a long history of herbal usage for the clinical management of a variety of diseases in indigenous cultures, the success rate of developing a new drug from herbal medicinal preparations should, in theory, be higher than that from chemical synthesis. While the endeavor for drug discovery from herbal medicines is “experience driven,” the search for a therapeutically useful synthetic drug, like “looking for a needle in a haystack,” is a daunting task. In this paper, we first illustrated various approaches of drug discovery from herbal medicines. Typical examples of successful drug discovery from botanical sources were given. In addition, problems in drug discovery from herbal medicines were described and possible solutions were proposed. The prospect of drug discovery from herbal medicines in the postgenomic era was made with the provision of future directions in this area of drug development. PMID:23634172

  19. Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System.

    Science.gov (United States)

    El-Kattan, Ayman F; Varma, Manthena V; Steyn, Stefan J; Scott, Dennis O; Maurer, Tristan S; Bergman, Arthur

    2016-12-01

    To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions. A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability. Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters. ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.

  20. Antiviral Drug Research Proposal Activity

    Directory of Open Access Journals (Sweden)

    Lisa Injaian

    2011-03-01

    Full Text Available The development of antiviral drugs provides an excellent example of how basic and clinical research must be used together in order to achieve the final goal of treating disease. A Research Oriented Learning Activity was designed to help students to better understand how basic and clinical research can be combined toward a common goal. Through this project students gained a better understanding of the process of scientific research and increased their information literacy in the field of virology. The students worked as teams to research the many aspects involved in the antiviral drug design process, with each student becoming an "expert" in one aspect of the project. The Antiviral Drug Research Proposal (ADRP culminated with students presenting their proposals to their peers and local virologists in a poster session. Assessment data showed increased student awareness and knowledge of the research process and the steps involved in the development of antiviral drugs as a result of this activity.

  1. Biomarkers as drug development tools: discovery, validation, qualification and use.

    Science.gov (United States)

    Kraus, Virginia B

    2018-06-01

    The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

  2. The AEROPATH project targeting Pseudomonas aeruginosa: crystallographic studies for assessment of potential targets in early-stage drug discovery

    International Nuclear Information System (INIS)

    Moynie, Lucille; Schnell, Robert; McMahon, Stephen A.; Sandalova, Tatyana; Boulkerou, Wassila Abdelli; Schmidberger, Jason W.; Alphey, Magnus; Cukier, Cyprian; Duthie, Fraser; Kopec, Jolanta; Liu, Huanting; Jacewicz, Agata; Hunter, William N.; Naismith, James H.; Schneider, Gunter

    2012-01-01

    A focused strategy has been directed towards the structural characterization of selected proteins from the bacterial pathogen P. aeruginosa. The objective is to exploit the resulting structural data, in combination with ligand-binding studies, and to assess the potential of these proteins for early-stage antimicrobial drug discovery. Bacterial infections are increasingly difficult to treat owing to the spread of antibiotic resistance. A major concern is Gram-negative bacteria, for which the discovery of new antimicrobial drugs has been particularly scarce. In an effort to accelerate early steps in drug discovery, the EU-funded AEROPATH project aims to identify novel targets in the opportunistic pathogen Pseudomonas aeruginosa by applying a multidisciplinary approach encompassing target validation, structural characterization, assay development and hit identification from small-molecule libraries. Here, the strategies used for target selection are described and progress in protein production and structure analysis is reported. Of the 102 selected targets, 84 could be produced in soluble form and the de novo structures of 39 proteins have been determined. The crystal structures of eight of these targets, ranging from hypothetical unknown proteins to metabolic enzymes from different functional classes (PA1645, PA1648, PA2169, PA3770, PA4098, PA4485, PA4992 and PA5259), are reported here. The structural information is expected to provide a firm basis for the improvement of hit compounds identified from fragment-based and high-throughput screening campaigns

  3. Candidiasis and the impact of flow cytometry on antifungal drug discovery.

    Science.gov (United States)

    Ku, Tsun Sheng N; Bernardo, Stella; Walraven, Carla J; Lee, Samuel A

    2017-11-01

    Invasive candidiasis continues to be associated with significant morbidity and mortality as well as substantial health care costs nationally and globally. One of the contributing factors is the development of resistance to antifungal agents that are already in clinical use. Moreover, there are known treatment limitations with all of the available antifungal agents. Since traditional techniques in novel drug discovery are time consuming, high-throughput screening using flow cytometry presents as a potential tool to identify new antifungal agents that would be useful in the management of these patients. Areas covered: In this review, the authors discuss the use of automated high-throughput screening assays based upon flow cytometry to identify potential antifungals from a library comprised of a large number of bioactive compounds. They also review studies that employed the use of this research methodology that has identified compounds with antifungal activity. Expert opinion: High-throughput screening using flow cytometry has substantially decreased the processing time necessary for screening thousands of compounds, and has helped enhance our understanding of fungal pathogenesis. Indeed, the authors see this technology as a powerful tool to help scientists identify new antifungal agents that can be added to the clinician's arsenal in their fight against invasive candidiasis.

  4. G protein-coupled receptor transmembrane binding pockets and their applications in GPCR research and drug discovery: a survey.

    Science.gov (United States)

    Kratochwil, Nicole A; Gatti-McArthur, Silvia; Hoener, Marius C; Lindemann, Lothar; Christ, Andreas D; Green, Luke G; Guba, Wolfgang; Martin, Rainer E; Malherbe, Pari; Porter, Richard H P; Slack, Jay P; Winnig, Marcel; Dehmlow, Henrietta; Grether, Uwe; Hertel, Cornelia; Narquizian, Robert; Panousis, Constantinos G; Kolczewski, Sabine; Steward, Lucinda

    2011-01-01

    G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Hence, an automated method was developed that allows a fast analysis and comparison of these generic ligand binding pockets across the entire GPCR family by providing the relevant information for all GPCRs in the same format. This methodology compiles amino acids lining the TM binding pocket including parts of the ECL2 loop in a so-called 1D ligand binding pocket vector and translates these 1D vectors in a second step into 3D receptor pharmacophore models. It aims to support various aspects of GPCR drug discovery in the pharmaceutical industry. Applications of pharmacophore similarity analysis of these 1D LPVs include definition of receptor subfamilies, prediction of species differences within subfamilies in regard to in vitro pharmacology and identification of nearest neighbors for GPCRs of interest to generate starting points for GPCR lead identification programs. These aspects of GPCR research are exemplified in the field of melanopsins, trace amine-associated receptors and somatostatin receptor subtype 5. In addition, it is demonstrated how 3D pharmacophore models of the LPVs can support the prediction of amino acids involved in ligand recognition, the understanding of mutational data in a 3D context and the elucidation of binding modes for GPCR ligands and their evaluation. Furthermore, guidance through 3D receptor pharmacophore modeling for the synthesis of subtype-specific GPCR ligands will be reported. Illustrative examples are taken from the GPCR family class C, metabotropic glutamate receptors 1 and 5 and sweet taste receptors, and from the GPCR class A, e.g. nicotinic acid and 5-hydroxytryptamine 5A receptor. © 2011 Bentham Science Publishers

  5. The application of mass-spectrometry-based protein biomarker discovery to theragnostics

    OpenAIRE

    Street, Jonathan M; Dear, James W

    2010-01-01

    Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed ‘theragnostics’). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

  6. A practical drug discovery project at the undergraduate level.

    Science.gov (United States)

    Fray, M Jonathan; Macdonald, Simon J F; Baldwin, Ian R; Barton, Nick; Brown, Jack; Campbell, Ian B; Churcher, Ian; Coe, Diane M; Cooper, Anthony W J; Craven, Andrew P; Fisher, Gail; Inglis, Graham G A; Kelly, Henry A; Liddle, John; Maxwell, Aoife C; Patel, Vipulkumar K; Swanson, Stephen; Wellaway, Natalie

    2013-12-01

    In this article, we describe a practical drug discovery project for third-year undergraduates. No previous knowledge of medicinal chemistry is assumed. Initial lecture workshops cover the basic principles; then students, in teams, seek to improve the profile of a weakly potent, insoluble phosphatidylinositide 3-kinase delta (PI3Kδ) inhibitor (1) through compound array design, molecular modelling, screening data analysis and the synthesis of target compounds in the laboratory. The project benefits from significant industrial support, including lectures, student mentoring and consumables. The aim is to make the learning experience as close as possible to real-life industrial situations. In total, 48 target compounds were prepared, the best of which (5b, 5j, 6b and 6ap) improved the potency and aqueous solubility of the lead compound (1) by 100-1000 fold and ≥tenfold, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Knowledge Discovery and Data Mining in Iran's Climatic Researches

    Science.gov (United States)

    Karimi, Mostafa

    2013-04-01

    Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for

  8. Discovery – Cisplatin and The Treatment of Testicular and Other Cancers

    Science.gov (United States)

    Prior to the discovery of cisplatin in 1965, men with testicular cancer had few medical options. Now, thanks to NCI research, cisplatin and similar chemotherapy drugs are known for curing testicular and other forms of cancer.

  9. LEGO-inspired drug design: Discovery of novel fungal Plasma membrane H+-ATPase (Pma1) inhibitors from small molecule libraries: An introduction of HFSA-SBS_DOS-RD strategy in drug discovery

    DEFF Research Database (Denmark)

    Tung, Truong Thanh; Dao, Trong Tuan; Palmgren, Michael B.

    to extracellular, this enzyme generates a transmembrane electrochem. gradient, as a consequence, fungi can uptake nutrients by secondary transport systems. Until now, only low resoln. of protein structure has been reported, and notably there a no report of co-crystal structure of Pma1 with inhibitors. Therefore......-oriented synthesis (SBS_DOS) and rational design (RD), so called HFSA-SBS_DOS-RD strategy in drug discovery and development process. Using HFSA-SBS_DOS-RD, our group successfully designed, synthesized, and performed SAR studies of novel compds. potent Pma1 inhibitors. An expeditious, high yield and scalable...... microwave-assisted synthesis was developed and applied for synthesis of library compds. To our delight, ours compd. libraries were able to inhibit Pma1 activity and growth inhibitory activity of C. albican and S. cerevisiae revealed the most promising example for future development of antifungal drugs...

  10. High-Throughput Screening of Ototoxic and Otoprotective Pharmacological Drugs

    Science.gov (United States)

    Kalinec, Federico

    2005-01-01

    Drug ototoxicity research has relied traditionally on animal models for the discovery and development of therapeutic interventions. More than 50 years of research, however, has delivered few--if any--successful clinical strategies for preventing or ameliorating the ototoxic effects of common pharmacological drugs such as aminoglycoside…

  11. Enabling Open Research Data Discovery through a Recommender System

    Science.gov (United States)

    Devaraju, Anusuriya; Jayasinghe, Gaya; Klump, Jens; Hogan, Dominic

    2017-04-01

    Government agencies, universities, research and nonprofit organizations are increasingly publishing their datasets to promote transparency, induce new research and generate economic value through the development of new products or services. The datasets may be downloaded from various data portals (data repositories) which are general or domain-specific. The Registry of Research Data Repository (re3data.org) lists more than 2500 such data repositories from around the globe. Data portals allow keyword search and faceted navigation to facilitate discovery of research datasets. However, the volume and variety of datasets have made finding relevant datasets more difficult. Common dataset search mechanisms may be time consuming, may produce irrelevant results and are primarily suitable for users who are familiar with the general structure and contents of the respective database. Therefore, we need new approaches to support research data discovery. Recommender systems offer new possibilities for users to find datasets that are relevant to their research interests. This study presents a recommender system developed for the CSIRO Data Access Portal (DAP, http://data.csiro.au). The datasets hosted on the portal are diverse, published by researchers from 13 business units in the organisation. The goal of the study is not to replace the current search mechanisms on the data portal, but rather to extend the data discovery through an exploratory search, in this case by building a recommender system. We adopted a hybrid recommendation approach, comprising content-based filtering and item-item collaborative filtering. The content-based filtering computes similarities between datasets based on metadata such as title, keywords, descriptions, fields of research, location, contributors, etc. The collaborative filtering utilizes user search behaviour and download patterns derived from the server logs to determine similar datasets. Similarities above are then combined with different

  12. The roots of modern oncology: from discovery of new antitumor anthracyclines to their clinical use.

    Science.gov (United States)

    Cassinelli, Giuseppe

    2016-06-02

    In May 1960, the Farmitalia CEO Dr. Bertini and the director of the Istituto Nazionale dei Tumori of Milan Prof. Bucalossi (talent scout and city's Mayor) signed a research agreement for the discovery and development up to clinical trials of new natural antitumor agents. This agreement can be considered as a pioneering and fruitful example of a translational discovery program with relevant transatlantic connections. Owing to an eclectic Streptomyces, found near Castel del Monte (Apulia), and to the skilled and motivated participants of both institutions, a new natural antitumor drug, daunomycin, was ready for clinical trials within 3 years. Patent interference by the Farmitalia French partner was overcome by the good quality of the Italian drug and by the cooperation between Prof. Di Marco, director of the Istituto Ricerche Farmitalia Research Laboratories for Microbiology and Chemotherapy, and Prof. Karnofsky, head of the Sloan-Kettering Cancer Institute of New York, leading to the first transatlantic clinical trials. The search for daunomycin's sister anthracyclines led to the discovery and development of adriamycin, one of the best drugs born in Milan. This was the second act prologue of the history of Italian antitumor discovery and clinical oncology, which started in July 1969 when Prof. Di Marco sent Prof. Bonadonna the first vials of adriamycin (doxorubicin) to be tested in clinical trials. This article reviews the Milan scene in the 1960s, a city admired and noted for the outstanding scientific achievements of its private and public institutions in drugs and industrial product discovery.

  13. Emerging role of bioinformatics tools and software in evolution of clinical research

    Directory of Open Access Journals (Sweden)

    Supreet Kaur Gill

    2016-01-01

    Full Text Available Clinical research is making toiling efforts for promotion and wellbeing of the health status of the people. There is a rapid increase in number and severity of diseases like cancer, hepatitis, HIV etc, resulting in high morbidity and mortality. Clinical research involves drug discovery and development whereas clinical trials are performed to establish safety and efficacy of drugs. Drug discovery is a long process starting with the target identification, validation and lead optimization. This is followed by the preclinical trials, intensive clinical trials and eventually post marketing vigilance for drug safety. Softwares and the bioinformatics tools play a great role not only in the drug discovery but also in drug development. It involves the use of informatics in the development of new knowledge pertaining to health and disease, data management during clinical trials and to use clinical data for secondary research. In addition, new technology likes molecular docking, molecular dynamics simulation, proteomics and quantitative structure activity relationship in clinical research results in faster and easier drug discovery process. During the preclinical trials, the software is used for randomization to remove bias and to plan study design. In clinical trials software like electronic data capture, Remote data capture and electronic case report form (eCRF is used to store the data. eClinical, Oracle clinical are software used for clinical data management and for statistical analysis of the data. After the drug is marketed the safety of a drug could be monitored by drug safety software like Oracle Argus or ARISg. Therefore, softwares are used from the very early stages of drug designing, to drug development, clinical trials and during pharmacovigilance. This review describes different aspects related to application of computers and bioinformatics in drug designing, discovery and development, formulation designing and clinical research.

  14. Progressing from programmatic to discovery research: a case example with the overjustification effect.

    Science.gov (United States)

    Roane, Henry S; Fisher, Wayne W; McDonough, Erin M

    2003-01-01

    Scientific research progresses along planned (programmatic research) and unplanned (discovery research) paths. In the current investigation, we attempted to conduct a single-case evaluation of the overjustification effect (i.e., programmatic research). Results of the initial analysis were contrary to the overjustification hypothesis in that removal of the reward contingency produced an increase in responding. Based on this unexpected finding, we conducted subsequent analyses to further evaluate the mechanisms underlying these results (i.e., discovery research). Results of the additional analyses suggested that the reward contingency functioned as punishment (because the participant preferred the task to the rewards) and that withdrawal of the contingency produced punishment contrast.

  15. Drug Repurposing from an Academic Perspective.

    Science.gov (United States)

    Oprea, Tudor I; Bauman, Julie E; Bologa, Cristian G; Buranda, Tione; Chigaev, Alexandre; Edwards, Bruce S; Jarvik, Jonathan W; Gresham, Hattie D; Haynes, Mark K; Hjelle, Brian; Hromas, Robert; Hudson, Laurie; Mackenzie, Debra A; Muller, Carolyn Y; Reed, John C; Simons, Peter C; Smagley, Yelena; Strouse, Juan; Surviladze, Zurab; Thompson, Todd; Ursu, Oleg; Waller, Anna; Wandinger-Ness, Angela; Winter, Stuart S; Wu, Yang; Young, Susan M; Larson, Richard S; Willman, Cheryl; Sklar, Larry A

    2011-01-01

    Academia and small business research units are poised to play an increasing role in drug discovery, with drug repurposing as one of the major areas of activity. Here we summarize project status for a number of drugs or classes of drugs: raltegravir, cyclobenzaprine, benzbromarone, mometasone furoate, astemizole, R-naproxen, ketorolac, tolfenamic acid, phenothiazines, methylergonovine maleate and beta-adrenergic receptor drugs, respectively. Based on this multi-year, multi-project experience we discuss strengths and weaknesses of academic-based drug repurposing research. Translational, target and disease foci are strategic advantages fostered by close proximity and frequent interactions between basic and clinical scientists, which often result in discovering new modes of action for approved drugs. On the other hand, lack of integration with pharmaceutical sciences and toxicology, lack of appropriate intellectual coverage and issues related to dosing and safety may lead to significant drawbacks. The development of a more streamlined regulatory process world-wide, and the development of pre-competitive knowledge transfer systems such as a global healthcare database focused on regulatory and scientific information for drugs world-wide, are among the ideas proposed to improve the process of academic drug discovery and repurposing, and to overcome the "valley of death" by bridging basic to clinical sciences.

  16. The pivotal role of multimodality reporter sensors in drug discovery: from cell based assays to real time molecular imaging.

    Science.gov (United States)

    Ray, Pritha

    2011-04-01

    Development and marketing of new drugs require stringent validation that are expensive and time consuming. Non-invasive multimodality molecular imaging using reporter genes holds great potential to expedite these processes at reduced cost. New generations of smarter molecular imaging strategies such as Split reporter, Bioluminescence resonance energy transfer, Multimodality fusion reporter technologies will further assist to streamline and shorten the drug discovery and developmental process. This review illustrates the importance and potential of molecular imaging using multimodality reporter genes in drug development at preclinical phases.

  17. Receptor localization of steroid hormones and drugs: discoveries through the use of thaw-mount and dry-mount autoradiography

    Directory of Open Access Journals (Sweden)

    Stumpf W.E.

    1998-01-01

    Full Text Available The history of receptor autoradiography, its development and applications, testify to the utility of this histochemical technique for localizing radiolabeled hormones and drugs at cellular and subcellular sites of action in intact tissues. Localization of diffusible compounds has been a challenge that was met through the introduction of the "thaw-mount" and "dry-mount" autoradiographic techniques thirty years ago. With this cellular receptor autoradiography, used alone or combined with other histochemical techniques, sites of specific binding and deposition in vivo and in vitro have been characterized. Numerous discoveries, some reviewed in this article, provided information that led to new concepts and opened new areas of research. As an example, in recent years more than fifty target tissues for vitamin D have been specified, challenging the conventional view about the main biological role of vitamin D. The functions of most of these vitamin D target tissues are unrelated to the regulation of systemic calcium homeostasis, but pertain to the (seasonal regulation of endo- and exocrine secretion, cell proliferation, reproduction, neural, immune and cardiovascular responses, and adaptation to stress. Receptor autoradiography with cellular resolution has become an indispensable tool in drug research and development, since information can be obtained that is difficult or impossible to gain otherwise

  18. The University of Kansas High-Throughput Screening Laboratory. Part II: enabling collaborative drug-discovery partnerships through cutting-edge screening technology.

    Science.gov (United States)

    McDonald, Peter R; Roy, Anuradha; Chaguturu, Rathnam

    2011-07-01

    The University of Kansas High-Throughput Screening (KU HTS) core is a state-of-the-art drug-discovery facility with an entrepreneurial open-service policy, which provides centralized resources supporting public- and private-sector research initiatives. The KU HTS core was established in 2002 at the University of Kansas with support from an NIH grant and the state of Kansas. It collaborates with investigators from national and international academic, nonprofit and pharmaceutical organizations in executing HTS-ready assay development and screening of chemical libraries for target validation, probe selection, hit identification and lead optimization. This is part two of a contribution from the KU HTS laboratory.

  19. New Zealand’s Drug Development Industry

    Directory of Open Access Journals (Sweden)

    Christopher Carswell

    2013-09-01

    Full Text Available The pharmaceutical industry’s profitability depends on identifying and successfully developing new drug candidates while trying to contain the increasing costs of drug development. It is actively searching for new sources of innovative compounds and for mechanisms to reduce the enormous costs of developing new drug candidates. There is an opportunity for academia to further develop as a source of drug discovery. The rising levels of industry outsourcing also provide prospects for organisations that can reduce the costs of drug development. We explored the potential returns to New Zealand (NZ from its drug discovery expertise by assuming a drug development candidate is out-licensed without clinical data and has anticipated peak global sales of $350 million. We also estimated the revenue from NZ’s clinical research industry based on a standard per participant payment to study sites and the number of industry-sponsored clinical trials approved each year. Our analyses found that NZ’s clinical research industry has generated increasing foreign revenue and appropriate policy support could ensure that this continues to grow. In addition the probability-based revenue from the out-licensing of a drug development candidate could be important for NZ if provided with appropriate policy and financial support.

  20. In Silico Systems Pharmacology to Assess Drug's Therapeutic and Toxic Effects

    DEFF Research Database (Denmark)

    Orozco, Alejandro Aguayo; Audouze, Karine; Brunak, Soren

    2016-01-01

    For many years, the "one target, one drug" paradigm has been the driving force behind developments in pharmaceutical research. With the recent advances in molecular biology and genomics technologies, the focus is shifting toward "drug-holistic" systems based approaches (i.e. systems pharmacology......). The integration of large and diverse amount of data from chemistry and biology coupled with the development and the application of network-based approaches to cope with these data is the next paradigm of drug discovery. Systems pharmacology offers a novel way of approaching drug discovery by developing models...

  1. Therapeutic Potential of Plants as Anti-Microbials for Drug Discovery

    Directory of Open Access Journals (Sweden)

    Ramar Perumal Samy

    2010-01-01

    Full Text Available The uses of traditional medicinal plants for primary health care have steadily increased worldwide in recent years. Scientists are in search of new phytochemicals that could be developed as useful anti-microbials for treatment of infectious diseases. Currently, out of 80% of pharmaceuticals derived from plants, very few are now being used as anti-microbials. Plants are rich in a wide variety of secondary metabolites that have found anti-microbial properties. This review highlights the current status of traditional medicine, its contribution to modern medicine, recent trends in the evaluation of anti-microbials with a special emphasis upon some tribal medicine, in vitro and in vivo experimental design for screening, and therapeutic efficacy in safety and human clinical trails for commercial outlet. Many of these commercially available compounds are crude preparations administered without performing human clinical trials. Recent methods are useful to standardize the extraction for scientific investigation of new phytochemicals and anti-microbials of traditionally used plants. It is concluded that once the local ethnomedical preparations of traditional sources are scientifically evaluated before dispensing they should replace existing drugs commonly used for the therapeutic treatment of infection. This method should be put into practice for future investigations in the field of ethnopharmacology, phytochemistry, ethnobotany and other biological fields for drug discovery.

  2. Is the GAIN Act a turning point in new antibiotic discovery?

    Science.gov (United States)

    Brown, Eric D

    2013-03-01

    The United States GAIN (Generating Antibiotic Incentives Now) Act is a call to action for new antibiotic discovery and development that arises from a ground swell of concern over declining activity in this therapeutic area in the pharmaceutical sector. The GAIN Act aims to provide economic incentives for antibiotic drug discovery in the form of market exclusivity and accelerated drug approval processes. The legislation comes on the heels of nearly two decades of failure using the tools of modern drug discovery to find new antibiotic drugs. The lessons of failure are examined herein as are the prospects for a renewed effort in antibiotic drug discovery and development stimulated by new investments in both the public and private sector.

  3. Towards a 21st-century roadmap for biomedical research and drug discovery: consensus report and recommendations.

    Science.gov (United States)

    Langley, Gillian R; Adcock, Ian M; Busquet, François; Crofton, Kevin M; Csernok, Elena; Giese, Christoph; Heinonen, Tuula; Herrmann, Kathrin; Hofmann-Apitius, Martin; Landesmann, Brigitte; Marshall, Lindsay J; McIvor, Emily; Muotri, Alysson R; Noor, Fozia; Schutte, Katrin; Seidle, Troy; van de Stolpe, Anja; Van Esch, Hilde; Willett, Catherine; Woszczek, Grzegorz

    2017-02-01

    Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and non-governmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Plant natural products research in tuberculosis drug discovery and ...

    African Journals Online (AJOL)

    SAM

    2014-06-04

    Jun 4, 2014 ... Department of Medicinal Chemistry and Quality Control (MCQC), National Institute for Pharmaceutical Research and. Development ..... Anticancer. Cannabis sativa L. ... National Cancer Research Institute (NCI) at Frederick,.

  5. Dual-acting of Hybrid Compounds - A New Dawn in the Discovery of Multi-target Drugs: Lead Generation Approaches.

    Science.gov (United States)

    Abdolmaleki, Azizeh; Ghasemi, Jahan B

    2017-01-01

    Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  6. Marine Microorganism-Invertebrate Assemblages: Perspectives to Solve the “Supply Problem” in the Initial Steps of Drug Discovery

    NARCIS (Netherlands)

    Leal, M.C.; Sheridan, C.; Osinga, R.; Dionisio, G.; Rocha, R.J.M.; Silva, B.; Rosa, R.; Calado, R.

    2014-01-01

    The chemical diversity associated with marine natural products (MNP) is unanimously acknowledged as the “blue gold” in the urgent quest for new drugs. Consequently, a significant increase in the discovery of MNP published in the literature has been observed in the past decades, particularly from

  7. Hit and lead criteria in drug discovery for infectious diseases of the developing world.

    Science.gov (United States)

    Katsuno, Kei; Burrows, Jeremy N; Duncan, Ken; Hooft van Huijsduijnen, Rob; Kaneko, Takushi; Kita, Kiyoshi; Mowbray, Charles E; Schmatz, Dennis; Warner, Peter; Slingsby, B T

    2015-11-01

    Reducing the burden of infectious diseases that affect people in the developing world requires sustained collaborative drug discovery efforts. The quality of the chemical starting points for such projects is a key factor in improving the likelihood of clinical success, and so it is important to set clear go/no-go criteria for the progression of hit and lead compounds. With this in mind, the Japanese Global Health Innovative Technology (GHIT) Fund convened with experts from the Medicines for Malaria Venture, the Drugs for Neglected Diseases initiative and the TB Alliance, together with representatives from the Bill &Melinda Gates Foundation, to set disease-specific criteria for hits and leads for malaria, tuberculosis, visceral leishmaniasis and Chagas disease. Here, we present the agreed criteria and discuss the underlying rationale.

  8. A Review of Human Pluripotent Stem Cell-Derived Cardiomyocytes for High-Throughput Drug Discovery, Cardiotoxicity Screening and Publication Standards

    OpenAIRE

    Mordwinkin, Nicholas M.; Burridge, Paul W.; Wu, Joseph C.

    2012-01-01

    Drug attrition rates have increased in past years, resulting in growing costs for the pharmaceutical industry and consumers. The reasons for this include the lack of in vitro models that correlate with clinical results, and poor preclinical toxicity screening assays. The in vitro production of human cardiac progenitor cells and cardiomyocytes from human pluripotent stem cells provides an amenable source of cells for applications in drug discovery, disease modeling, regenerative medicine, and ...

  9. Drug discovery strategies in the field of tumor energy metabolism: Limitations by metabolic flexibility and metabolic resistance to chemotherapy.

    Science.gov (United States)

    Amoedo, N D; Obre, E; Rossignol, R

    2017-08-01

    metabolism and to follow the efficiency of a treatment at a preclinical or clinical stage. Relevant descriptors of tumor metabolism are now required to better stratify patients for the development of personalized metabolic medicine. In this review, we discuss the current limitations in basic research and drug discovery in the field of cancer metabolism to foster the need for more clinically relevant target identification and validation. We discuss the design of adapted drug screening assays and compound efficacy evaluation methods for the discovery of innovative anti-cancer therapeutic approaches at the level of tumor energetics. This article is part of a Special Issue entitled Mitochondria in Cancer, edited by Giuseppe Gasparre, Rodrigue Rossignol and Pierre Sonveaux. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls

    Directory of Open Access Journals (Sweden)

    Hezekiel Mathambo Kumalo

    2015-01-01

    Full Text Available he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i covalent interactions in biomolecular systems; (ii the mathematical framework of covalent molecular docking; (iii implementation of covalent docking protocol in drug design workflows; (iv applications covalent docking: case studies and (v shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.

  11. Mechanistic systems modeling to guide drug discovery and development.

    Science.gov (United States)

    Schmidt, Brian J; Papin, Jason A; Musante, Cynthia J

    2013-02-01

    A crucial question that must be addressed in the drug development process is whether the proposed therapeutic target will yield the desired effect in the clinical population. Pharmaceutical and biotechnology companies place a large investment on research and development, long before confirmatory data are available from human trials. Basic science has greatly expanded the computable knowledge of disease processes, both through the generation of large omics data sets and a compendium of studies assessing cellular and systemic responses to physiologic and pathophysiologic stimuli. Given inherent uncertainties in drug development, mechanistic systems models can better inform target selection and the decision process for advancing compounds through preclinical and clinical research. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Brazil: An emerging partner in drug R&D.

    Science.gov (United States)

    Rodrigues, Debora G

    2009-08-01

    With the need for innovation in drug discovery and development and changes to patent laws that are enabling greater IP protection, many pharmaceutical companies are pursuing international cooperation agreements with foreign companies as part of a global development strategy to enhance product pipelines. Brazil, the largest pharmaceutical market in Latin America, has improved its infrastructure, scientific and technological capabilities and has created a sustainable strategy to promote drug discovery research activities. Positive economic growth, a stable political structure, expanding patient populations an increasing governmental, private and foreign investments are creating a new landscape for drug R&D in the country. As Brazilian-based pharmaceutical companies become further established, new opportunities for partnerships and collaborative alliances are becoming available for the drug discovery process, as well as for co-manufacturing and co-marketing efforts. This feature review provides an overview of the Brazilian pharmaceutical market and discusses current opportunities, emerging trends and challenges for this expanding market.

  13. Drug Enforcement Administration

    Science.gov (United States)

    ... de informacin confidencial --> DEA NEWS The Drug Enforcement Administration and Discovery Education name grand winner of Operation ... JUN 15 (Washington) The United States Drug Enforcement Administration, DEA Educational Foundation and Discovery Education awarded Porter ...

  14. Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

    International Nuclear Information System (INIS)

    Morton, M.J.; Armstrong, D.; Abi Gerges, N.; Bridgland-Taylor, M.; Pollard, C.E.; Bowes, J.; Valentin, J.-P.

    2014-01-01

    Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility

  15. Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

    Energy Technology Data Exchange (ETDEWEB)

    Morton, M.J., E-mail: michael.morton@astrazeneca.com [Discovery Sciences, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Armstrong, D.; Abi Gerges, N. [Drug Safety and Metabolism, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Bridgland-Taylor, M. [Discovery Sciences, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Pollard, C.E.; Bowes, J.; Valentin, J.-P. [Drug Safety and Metabolism, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom)

    2014-09-01

    Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility.

  16. A rapid alternative to X-ray crystallography for chiral determination: case studies of vibrational circular dichroism (VCD) to advance drug discovery projects.

    Science.gov (United States)

    Wesolowski, Steven S; Pivonka, Don E

    2013-07-15

    The absolute stereochemistry of chiral drugs is usually established via X-ray crystallography. However, vibrational circular dichroism (VCD) spectroscopy coupled with quantum mechanics simulations offers a rapid alternative to crystallography and is readily applied to both crystalline and non-crystalline samples. VCD is an effective complement to X-ray analysis of drug candidates, and it can be used as a high-throughput means of assessing absolute stereochemistry at all phases of the discovery process (hundreds of assignments per year). The practical implementation (or fee-for-service outsourcing) of VCD and selected case studies are illustrated with an emphasis on providing utility and impact to pharmaceutical discovery programs. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

    Science.gov (United States)

    Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J.M.; London, Gábor; Nussinov, Ruth

    2013-01-01

    Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The “central hit strategy” selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The “network influence strategy” works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach. PMID:23384594

  18. Signals from the Fourth Dimension Regulate Drug Relapse.

    Science.gov (United States)

    Mulholland, Patrick J; Chandler, L Judson; Kalivas, Peter W

    2016-07-01

    Despite the enormous societal burden of alcohol and drug addiction and abundant research describing drug-induced maladaptive synaptic plasticity, there are few effective strategies for treating substance use disorders. Recent awareness that synaptic plasticity involves astroglia and the extracellular matrix is revealing new possibilities for understanding and treating addiction. We first review constitutive corticostriatal adaptations that are elicited by and shared between all abused drugs from the perspective of tetrapartite synapses, and integrate recent discoveries regarding cell type-specificity in striatal neurons. Next, we describe recent discoveries that drug-seeking is associated with transient synaptic plasticity that requires all four synaptic elements and is shared across drug classes. Finally, we prognosticate how considering tetrapartite synapses can provide new treatment strategies for addiction. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Conformational transition paths harbor structures useful for aiding drug discovery and understanding enzymatic mechanisms in protein kinases.

    Science.gov (United States)

    Wong, Chung F

    2016-01-01

    This short article examines the usefulness of fast simulations of conformational transition paths in elucidating enzymatic mechanisms and guiding drug discovery for protein kinases. It applies the transition path method in the MOIL software package to simulate the paths of conformational transitions between six pairs of structures from the Protein Data Bank. The structures along the transition paths were found to resemble experimental structures that mimic transient structures believed to form during enzymatic catalysis or conformational transitions, or structures that have drug candidates bound. These findings suggest that such simulations could provide quick initial insights into the enzymatic mechanisms or pathways of conformational transitions of proteins kinases, or could provide structures useful for aiding structure-based drug design. © 2015 The Protein Society.

  20. Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

    Science.gov (United States)

    Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

    2016-05-27

    Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and

  1. Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

    LENUS (Irish Health Repository)

    Toomey, David

    2009-01-01

    BACKGROUND: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins\\/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and\\/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. METHODOLOGY\\/PRINCIPAL FINDINGS: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. CONCLUSIONS\\/SIGNIFICANCE: Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under \\'change-of-application\\' patents.

  2. Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

    Directory of Open Access Journals (Sweden)

    David Toomey

    Full Text Available BACKGROUND: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. METHODOLOGY/PRINCIPAL FINDINGS: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i homologous to previously crystallized proteins or (ii targets of known drugs, but are (iii not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. CONCLUSIONS/SIGNIFICANCE: Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under 'change-of-application' patents.

  3. Microbial P450 Enzymes in Bioremediation and Drug Discovery: Emerging Potentials and Challenges.

    Science.gov (United States)

    Bhattacharya, Sukanta S; Yadav, Jagjit S

    2018-01-01

    Cytochrome P450 enzymes are a structurally conserved but functionally diverse group of heme-containing mixed function oxidases found across both prokaryotic and eukaryotic forms of the microbial world. Microbial P450s are known to perform diverse functions ranging from the synthesis of cell wall components to xenobiotic/drug metabolism to biodegradation of environmental chemicals. Conventionally, many microbial systems have been reported to mimic mammalian P450-like activation of drugs and were proposed as the in-vitro models of mammalian drug metabolism. Recent reports suggest that native or engineered forms of specific microbial P450s from these and other microbial systems could be employed for desired specific biotransformation reactions toward natural and synthetic (drug) compounds underscoring their emerging potential in drug improvement and discovery. On the other hand, microorganisms particularly fungi and actinomycetes have been shown to possess catabolic P450s with unusual potential to degrade toxic environmental chemicals including persistent organic pollutants (POPs). Wood-rotting basidiomycete fungi in particular have revealed the presence of exceptionally large P450 repertoire (P450ome) in their genomes, majority of which are however orphan (with no known function). Our pre- and post-genomic studies have led to functional characterization of several fungal P450s inducible in response to exposure to several environmental toxicants and demonstration of their potential in bioremediation of these chemicals. This review is an attempt to summarize the postgenomic unveiling of this versatile enzyme superfamily in microbial systems and investigation of their potential to synthesize new drugs and degrade persistent pollutants, among other biotechnological applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  4. Secondary Metabolites from Higher Fungi: Discovery, Bioactivity, and Bioproduction

    Science.gov (United States)

    Zhong, Jian-Jiang; Xiao, Jian-Hui

    Medicinal higher fungi such as Cordyceps sinensis and Ganoderma lucidum have been used as an alternative medicine remedy to promote health and longevity for people in China and other regions of the world since ancient times. Nowadays there is an increasing public interest in the secondary metabolites of those higher fungi for discovering new drugs or lead compounds. Current research in drug discovery from medicinal higher fungi involves a multifaceted approach combining mycological, biochemical, pharmacological, metabolic, biosynthetic and molecular techniques. In recent years, many new secondary metabolites from higher fungi have been isolated and are more likely to provide lead compounds for new drug discovery, which may include chemopreventive agents possessing the bioactivity of immunomodulatory, anticancer, etc. However, numerous challenges of secondary metabolites from higher fungi are encountered including bioseparation, identification, biosynthetic metabolism, and screening model issues, etc. Commercial production of secondary metabolites from medicinal mushrooms is still limited mainly due to less information about secondary metabolism and its regulation. Strategies for enhancing secondary metabolite production by medicinal mushroom fermentation include two-stage cultivation combining liquid fermentation and static culture, two-stage dissolved oxygen control, etc. Purification of bioactive secondary metabolites, such as ganoderic acids from G. lucidum, is also very important to pharmacological study and future pharmaceutical application. This review outlines typical examples of the discovery, bioactivity, and bioproduction of secondary metabolites of higher fungi origin.

  5. Advances in phage display technology for drug discovery.

    Science.gov (United States)

    Omidfar, Kobra; Daneshpour, Maryam

    2015-06-01

    Over the past decade, several library-based methods have been developed to discover ligands with strong binding affinities for their targets. These methods mimic the natural evolution for screening and identifying ligand-target interactions with specific functional properties. Phage display technology is a well-established method that has been applied to many technological challenges including novel drug discovery. This review describes the recent advances in the use of phage display technology for discovering novel bioactive compounds. Furthermore, it discusses the application of this technology to produce proteins and peptides as well as minimize the use of antibodies, such as antigen-binding fragment, single-chain fragment variable or single-domain antibody fragments like VHHs. Advances in screening, manufacturing and humanization technologies demonstrate that phage display derived products can play a significant role in the diagnosis and treatment of disease. The effects of this technology are inevitable in the development pipeline for bringing therapeutics into the market, and this number is expected to rise significantly in the future as new advances continue to take place in display methods. Furthermore, a widespread application of this methodology is predicted in different medical technological areas, including biosensing, monitoring, molecular imaging, gene therapy, vaccine development and nanotechnology.

  6. Chemical Genomics and Emerging DNA Technologies in the Identification of Drug Mechanisms and Drug Targets

    DEFF Research Database (Denmark)

    Olsen, Louise Cathrine Braun; Færgeman, Nils J.

    2012-01-01

    and validate therapeutic targets and to discover drug candidates for rapidly and effectively generating new interventions for human diseases. The recent emergence of genomic technologies and their application on genetically tractable model organisms like Drosophila melanogaster,Caenorhabditis elegans...... critical roles in the genomic age of biological research and drug discovery. In the present review we discuss how simple biological model organisms can be used as screening platforms in combination with emerging genomic technologies to advance the identification of potential drugs and their molecular...

  7. Generation of Polar Semi-Saturated Bicyclic Pyrazoles for Fragment-Based Drug Discovery Campaigns.

    Science.gov (United States)

    Luise, Nicola; Wyatt, Paul

    2018-05-07

    Synthesising polar semi-saturated bicyclic heterocycles can lead to better starting points for fragment-based drug discovery (FBDD) programs. This communication highlights the application of diverse chemistry to construct bicyclic systems from a common intermediate, where pyrazole, a privileged heteroaromatic able to bind effectively to biological targets, is fused to diverse saturated counterparts. The generated fragments can be further developed either after confirmation of their binding pose or early in the process, as their synthetic intermediates. Essential quality control (QC) for selection of small molecules to add to a fragment library is discussed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Trypanosomatids topoisomerase re-visited. New structural findings and role in drug discovery

    Directory of Open Access Journals (Sweden)

    Rafael Balaña-Fouce

    2014-12-01

    , their involvement both in the physiology and virulence of these parasites, as well as their use as promising targets for drug discovery.

  9. Towards an in vitro model of Plasmodium hypnozoites suitable for drug discovery.

    Science.gov (United States)

    Dembele, Laurent; Gego, Audrey; Zeeman, Anne-Marie; Franetich, Jean-François; Silvie, Olivier; Rametti, Armelle; Le Grand, Roger; Dereuddre-Bosquet, Nathalie; Sauerwein, Robert; van Gemert, Geert-Jan; Vaillant, Jean-Christophe; Thomas, Alan W; Snounou, Georges; Kocken, Clemens H M; Mazier, Dominique

    2011-03-31

    Amongst the Plasmodium species in humans, only P. vivax and P. ovale produce latent hepatic stages called hypnozoites, which are responsible for malaria episodes long after a mosquito bite. Relapses contribute to increased morbidity, and complicate malaria elimination programs. A single drug effective against hypnozoites, primaquine, is available, but its deployment is curtailed by its haemolytic potential in glucose-6-phosphate dehydrogenase deficient persons. Novel compounds are thus urgently needed to replace primaquine. Discovery of compounds active against hypnozoites is restricted to the in vivo P. cynomolgi-rhesus monkey model. Slow growing hepatic parasites reminiscent of hypnozoites had been noted in cultured P. vivax-infected hepatoma cells, but similar forms are also observed in vitro by other species including P. falciparum that do not produce hypnozoites. P. falciparum or P. cynomolgi sporozoites were used to infect human or Macaca fascicularis primary hepatocytes, respectively. The susceptibility of the slow and normally growing hepatic forms obtained in vitro to three antimalarial drugs, one active against hepatic forms including hypnozoites and two only against the growing forms, was measured. The non-dividing slow growing P. cynomolgi hepatic forms, observed in vitro in primary hepatocytes from the natural host Macaca fascicularis, can be distinguished from similar forms seen in P. falciparum-infected human primary hepatocytes by the differential action of selected anti-malarial drugs. Whereas atovaquone and pyrimethamine are active on all the dividing hepatic forms observed, the P. cynomolgi slow growing forms are highly resistant to treatment by these drugs, but remain susceptible to primaquine. Resistance of the non-dividing P. cynomolgi forms to atovaquone and pyrimethamine, which do not prevent relapses, strongly suggests that these slow growing forms are hypnozoites. This represents a first step towards the development of a practical medium

  10. Towards an in vitro model of Plasmodium hypnozoites suitable for drug discovery.

    Directory of Open Access Journals (Sweden)

    Laurent Dembele

    2011-03-01

    Full Text Available Amongst the Plasmodium species in humans, only P. vivax and P. ovale produce latent hepatic stages called hypnozoites, which are responsible for malaria episodes long after a mosquito bite. Relapses contribute to increased morbidity, and complicate malaria elimination programs. A single drug effective against hypnozoites, primaquine, is available, but its deployment is curtailed by its haemolytic potential in glucose-6-phosphate dehydrogenase deficient persons. Novel compounds are thus urgently needed to replace primaquine. Discovery of compounds active against hypnozoites is restricted to the in vivo P. cynomolgi-rhesus monkey model. Slow growing hepatic parasites reminiscent of hypnozoites had been noted in cultured P. vivax-infected hepatoma cells, but similar forms are also observed in vitro by other species including P. falciparum that do not produce hypnozoites.P. falciparum or P. cynomolgi sporozoites were used to infect human or Macaca fascicularis primary hepatocytes, respectively. The susceptibility of the slow and normally growing hepatic forms obtained in vitro to three antimalarial drugs, one active against hepatic forms including hypnozoites and two only against the growing forms, was measured.The non-dividing slow growing P. cynomolgi hepatic forms, observed in vitro in primary hepatocytes from the natural host Macaca fascicularis, can be distinguished from similar forms seen in P. falciparum-infected human primary hepatocytes by the differential action of selected anti-malarial drugs. Whereas atovaquone and pyrimethamine are active on all the dividing hepatic forms observed, the P. cynomolgi slow growing forms are highly resistant to treatment by these drugs, but remain susceptible to primaquine.Resistance of the non-dividing P. cynomolgi forms to atovaquone and pyrimethamine, which do not prevent relapses, strongly suggests that these slow growing forms are hypnozoites. This represents a first step towards the development of a

  11. Drug repurposing from an academic perspective

    DEFF Research Database (Denmark)

    Oprea, Tudor; Bauman, Julie E.; Bologa, Cristian G.

    2011-01-01

    Academia and small business research units are poised to play an increasing role in drug discovery, with drug repurposing as one of the major areas of activity. Here we summarize project status for several drugs or classes of drugs: raltegravir, cyclobenzaprine, benzbromarone, mometasone furoate...... intellectual coverage and issues related to dosing and safety may lead to significant drawbacks. The development of a more streamlined regulatory process worldwide, and the development of precompetitive knowledge transfer systems such as a global healthcare database focused on regulatory and scientific...

  12. A Metadata based Knowledge Discovery Methodology for Seeding Translational Research.

    Science.gov (United States)

    Kothari, Cartik R; Payne, Philip R O

    2015-01-01

    In this paper, we present a semantic, metadata based knowledge discovery methodology for identifying teams of researchers from diverse backgrounds who can collaborate on interdisciplinary research projects: projects in areas that have been identified as high-impact areas at The Ohio State University. This methodology involves the semantic annotation of keywords and the postulation of semantic metrics to improve the efficiency of the path exploration algorithm as well as to rank the results. Results indicate that our methodology can discover groups of experts from diverse areas who can collaborate on translational research projects.

  13. Analyzing user-generated online content for drug discovery: development and use of MedCrawler.

    Science.gov (United States)

    Helfenstein, Andreas; Tammela, Päivi

    2017-04-15

    Ethnopharmacology, or the scientific validation of traditional medicine, is a respected starting point in drug discovery. Home remedies and traditional use of plants are still widespread, also in Western societies. Instead of perusing ancient pharmacopeias, we developed MedCrawler, which we used to analyze blog posts for mentions of home remedies and their applications. This method is free and accessible from the office computer. We developed MedCrawler, a data mining tool for analyzing user-generated blog posts aiming to find modern 'traditional' medicine or home remedies. It searches user-generated blog posts and analyzes them for correlations between medically relevant terms. We also present examples and show that this method is capable of delivering both scientifically validated uses as well as not so well documented applications, which might serve as a starting point for follow-up research. Source code is available on GitHub at {{ https://github.com/a-hel/medcrawler }}. paivi.tammela@helsinki.fi. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  14. Rationality in discovery : a study of logic, cognition, computation and neuropharmacology

    NARCIS (Netherlands)

    Bosch, Alexander Petrus Maria van den

    2001-01-01

    Part I Introduction The specific problem adressed in this thesis is: what is the rational use of theory and experiment in the process of scientific discovery, in theory and in the practice of drug research for Parkinson’s disease? The thesis aims to answer the following specific questions: what is:

  15. Public-Private Partnerships in Lead Discovery: Overview and Case Studies.

    Science.gov (United States)

    Gottwald, Matthias; Becker, Andreas; Bahr, Inke; Mueller-Fahrnow, Anke

    2016-09-01

    The pharmaceutical industry is faced with significant challenges in its efforts to discover new drugs that address unmet medical needs. Safety concerns and lack of efficacy are the two main technical reasons for attrition. Improved early research tools including predictive in silico, in vitro, and in vivo models, as well as a deeper understanding of the disease biology, therefore have the potential to improve success rates. The combination of internal activities with external collaborations in line with the interests and needs of all partners is a successful approach to foster innovation and to meet the challenges. Collaboration can take place in different ways, depending on the requirements of the participants. In this review, the value of public-private partnership approaches will be discussed, using examples from the Innovative Medicines Initiative (IMI). These examples describe consortia approaches to develop tools and processes for improving target identification and validation, as well as lead identification and optimization. The project "Kinetics for Drug Discovery" (K4DD), focusing on the adoption of drug-target binding kinetics analysis in the drug discovery decision-making process, is described in more detail. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Common to both academia and industry: the challenge of discovery. An interview with Perry Molinoff.

    Science.gov (United States)

    Molinoff, P B

    2001-06-01

    Perry Molinoff recognizes the distinctions between basic and applied science, between academic and industrial research, and between the preclinical and clinical realities of drug development. But he generally discusses these categories in fluid, practical terms, having throughout his career crossed the lines of distinction that have sometimes been rather heavily drawn among pharmacologists. As a third-year medical student at Harvard, he decided "to take a year off" to conduct laboratory research. After receiving his MD and pursuing further clinical and postdoctoral work, he enjoyed an academic career that included fourteen years as the A.N. Richards Professor and Chair of Pharmacology at the University of Pennsylvania School of Medicine. He has just completed six years as Vice President of Neuroscience and Genitourinary Drug Discovery for Bristol-Myers Squibb and will soon return to teaching, in the Departments of Psychiatry and Pharmacology at Yale University. Referring to himself as either pharmacologist or neuroscientist, depending on context, he has made fundamental discoveries in receptor biology, has overseen the discovery and development of drugs and their subsequent clinical trials, and has mentored a host of pharmacologists and neuroscientists who themselves have established careers in industry and academia. The pursuit of discovery as its own reward emerges as a theme that has marked his professional life (and is perhaps reflected also in the images displayed in his office of the Himalayan mountains, photographed by Molinoff himself from the Everest base camp last year).

  17. Biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy: a novel strategy in drug development

    Directory of Open Access Journals (Sweden)

    Jan eStenvang

    2013-12-01

    Full Text Available Cancer is a leading cause of mortality worldwide and matters are only set to worsen as its incidence continues to rise. Traditional approaches to combat cancer include improved prevention, early diagnosis, optimized surgery, development of novel drugs and honing regimens of existing anti-cancer drugs. Although discovery and development of novel and effective anti-cancer drugs is a major research area, it is well known that oncology drug development is a lengthy process, extremely costly and with high attrition rates. Furthermore, those drugs that do make it through the drug development mill are often quite expensive, laden with severe side-effects and, unfortunately, to date, have only demonstrated minimal increases in overall survival. Therefore, a strong interest has emerged to identify approved non-cancer drugs that possess anti-cancer activity, thus shortcutting the development process. This research strategy is commonly known as drug repurposing or drug repositioning and provides a faster path to the clinics. We have developed and implemented a modification of the standard drug repurposing strategy that we review here; rather than investigating target-promiscuous non-cancer drugs for possible anti-cancer activity, we focus on the discovery of novel cancer indications for already approved chemotherapeutic anti-cancer drugs. Clinical implementation of this strategy is normally commenced at clinical phase II trials and includes pre-treated patients. As the response rates to any non-standard chemotherapeutic drug will be relatively low in such a patient cohort it is a pre-requisite that such testing is based on predictive biomarkers. This review describes our strategy of biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy, taking the repurposing of topoisomerase I inhibitors and topoisomerase I as a potential predictive biomarker as case in point.

  18. 75 FR 45130 - Guidance for Industry and Researchers on the Radioactive Drug Research Committee: Human Research...

    Science.gov (United States)

    2010-08-02

    ... and Research, Food and Drug Administration, 10903 New Hampshire Ave., Bldg. 51, rm. 2201, Silver... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2009-D-0125] Guidance for Industry and Researchers on the Radioactive Drug Research Committee: Human Research Without an...

  19. Malaria in South America: a drug discovery perspective.

    Science.gov (United States)

    Cruz, Luiza R; Spangenberg, Thomas; Lacerda, Marcus V G; Wells, Timothy N C

    2013-05-24

    The challenge of controlling and eventually eradicating malaria means that new tools are urgently needed. South America's role in this fight spans both ends of the research and development spectrum: both as a continent capable of discovering and developing new medicines, and also as a continent with significant numbers of malaria patients. This article reviews the contribution of groups in the South American continent to the research and development of new medicines over the last decade. Therefore, the current situation of research targeting malaria control and eradication is discussed, including endemicity, geographical distribution, treatment, drug-resistance and diagnosis. This sets the scene for a review of efforts within South America to discover and optimize compounds with anti-malarial activity.

  20. Lab-on-a-chip platform for high throughput drug discovery with DNA-encoded chemical libraries

    Science.gov (United States)

    Grünzner, S.; Reddavide, F. V.; Steinfelder, C.; Cui, M.; Busek, M.; Klotzbach, U.; Zhang, Y.; Sonntag, F.

    2017-02-01

    The fast development of DNA-encoded chemical libraries (DECL) in the past 10 years has received great attention from pharmaceutical industries. It applies the selection approach for small molecular drug discovery. Because of the limited choices of DNA-compatible chemical reactions, most DNA-encoded chemical libraries have a narrow structural diversity and low synthetic yield. There is also a poor correlation between the ranking of compounds resulted from analyzing the sequencing data and the affinity measured through biochemical assays. By combining DECL with dynamical chemical library, the resulting DNA-encoded dynamic library (EDCCL) explores the thermodynamic equilibrium of reversible reactions as well as the advantages of DNA encoded compounds for manipulation/detection, thus leads to enhanced signal-to-noise ratio of the selection process and higher library quality. However, the library dynamics are caused by the weak interactions between the DNA strands, which also result in relatively low affinity of the bidentate interaction, as compared to a stable DNA duplex. To take advantage of both stably assembled dual-pharmacophore libraries and EDCCLs, we extended the concept of EDCCLs to heat-induced EDCCLs (hi-EDCCLs), in which the heat-induced recombination process of stable DNA duplexes and affinity capture are carried out separately. To replace the extremely laborious and repetitive manual process, a fully automated device will facilitate the use of DECL in drug discovery. Herein we describe a novel lab-on-a-chip platform for high throughput drug discovery with hi-EDCCL. A microfluidic system with integrated actuation was designed which is able to provide a continuous sample circulation by reducing the volume to a minimum. It consists of a cooled and a heated chamber for constant circulation. The system is capable to generate stable temperatures above 75 °C in the heated chamber to melt the double strands of the DNA and less than 15 °C in the cooled chamber

  1. A polychromatic turbidity microplate assay to distinguish discovery stage drug molecules with beneficial precipitation properties.

    Science.gov (United States)

    Morrison, John; Nophsker, Michelle; Elzinga, Paul; Donoso, Maria; Park, Hyunsoo; Haskell, Roy

    2017-10-05

    A material sparing microplate screening assay was developed to evaluate and compare the precipitation of discovery stage drug molecules as a function of time, concentration and media composition. Polychromatic turbidity time course profiles were collected for cinnarizine, probucol, dipyridamole as well as BMS-932481, and compared with turbidity profiles of monodisperse particle size standards. Precipitation for select sample conditions were further characterized at several time points by size, morphology, amount and form via laser diffraction, microscopy, size based particle counting and X-ray diffraction respectively. Wavelength dependent turbidity was found indicative of nanoprecipitate, while wavelength independent turbidity was consistent with larger microprecipitate formation. A transition from wavelength dependent to wavelength independent turbidity occurred for nanoparticle to microparticle growth, and a decrease in wavelength independent turbidity correlated with continued growth in size of microparticles. Other sudden changes in turbidity signal over time such as rapid fluctuation, a decrease in slope or a sharp inversion were correlated with very large or aggregated macro-precipitates exceeding 100μm in diameter, a change in the rate of precipitate formation or an amorphous to crystalline form conversion respectively. The assay provides an effective method to efficiently monitor and screen the precipitation fates of drug molecules, even during the early stages of discovery with limited amounts of available material. This capability highlights molecules with beneficial precipitation properties that are able to generate and maintain solubility enabling amorphous or nanoparticle precipitates. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. [New drug development by innovative drug administration--"change" in pharmaceutical field].

    Science.gov (United States)

    Nagai, T

    1997-11-01

    New drug development can be made by providing products of higher "selectivity for the drug" for medical treatment. There are two ways for the approach to get higher "selectivity of drug": 1) discovery of new compounds with high selectivity of drug; 2) innovation of new drug administration, that is new formulation and/or method with high selectivity of drug by integration and harmonization of various hard/soft technologies. An extensive increase of biological information and advancement of surrounding science and technology may modify the situation as the latter overcomes the former in the 21 century. As the science and technology in the 21 century is said to be formed on "3H", that is, 1. hybrid; 2. hi-quality; 3. husbandry, the new drug development by innovative drug administration is exactly based on the science and technology of 3H. Its characteristic points are interdisciplinary/interfusion, international, of philosophy/ethics, and systems of hard/hard/heart. From these points of view, not only the advance of unit technology but also a revolution in thinking way should be "must" subjects. To organize this type of research well, a total research activity such as ROR (research on research) might take an important and efficient role. Here the key words are the "Optimization technology" and "Change in Pharmaceutical Fields." As some examples of new drug innovation, our trials on several topical mucosal adhesive dosage forms and parenteral administration of peptide drugs such as insulin and erythropoietin will be described.

  3. Addiction research centres and the nurturing of creativity. The Centre for Alcohol and Drug Research: social science alcohol and drug research in Denmark.

    Science.gov (United States)

    Pedersen, Mads U; Elmeland, Karen; Frank, Vibeke A

    2011-12-01

    The purpose of this paper is to introduce the social science alcohol and drug research undertaken by the Centre for Alcohol and Drug Research (CRF) and at the same time offer an insight into the development in Danish alcohol and drug research throughout the past 15-20 years. A review of articles, books and reports published by researcher from CRF from the mid-1990s until today and an analysis of the policy-making in the Danish substance use and misuse area. CRF is a result of the discussions surrounding social, health and allocation policy questions since the mid-1980s. Among other things, these discussions led to the formal establishment of the Centre in 1991 under the Aarhus University, the Faculty of Social Science. Since 2001 the Centre has received a permanent basic allocation, which has made it possible to appoint tenured senior researchers; to work under a more long-term research strategy; to function as a milieu for educating PhD students; and to diversify from commissioned research tasks to initiating projects involving more fundamental research. Research at the Centre is today pivoted around four core areas: consumption, policy, prevention and treatment. The emergence, continuation, financing and character of the research taking place at CRF can be linked closely to the specific Danish drug and alcohol discourse and to the division of the responsibility for alcohol and drug research into separate Ministries. © 2010 The Authors, Addiction © 2010 Society for the Study of Addiction.

  4. How do researchers categorize drugs, and how do drug users categorize them?

    Science.gov (United States)

    Lee, Juliet P; Antin, Tamar M J

    2012-01-01

    This paper considers drug classifications and terms widely used in US survey research, and compares these to classifications and terms used by drug users. We begin with a critical review of drug classification systems, including those oriented to public policy and health services as well as survey research. We then consider the results of a pile sort exercise we conducted with 76 respondents within a mixed method study of Southeast Asian American adolescent and young adult drug users in urban Northern California, USA. We included the pile sort to clarify how respondents handled specific terms which we understood to be related to Ecstasy and methamphetamines. Results of the pile sort were analyzed using graphic layout algorithms as well as content analysis of pile labels. Similar to the national surveys, our respondents consistently differentiated Ecstasy terms from methamphetamine terms. We found high agreement between some specific local terms ( thizz , crystal ) and popular drug terms, while other terms thought to be mainstream ( crank , speed ) were reported as unknown by many respondents. In labeling piles, respondents created taxonomies based on consumption method (in particular, pill ) as well as the social contexts of use. We conclude by proposing that divergences between drug terms utilized in survey research and those used by drug users may reflect two opposing tendencies: the tendency of survey researchers to utilize standardized language that constructs persons and experiences as relatively homogeneous, varying only within measurable degrees, and the tendency of drug users to utilize specialized language (argot) that reflects their understandings of their experiences as hybrid and diverse. The findings problematize the validity of drug terms and categories used in survey research.

  5. Predictors of timing of pregnancy discovery.

    Science.gov (United States)

    McCarthy, Molly; Upadhyay, Ushma; Biggs, M Antonia; Anthony, Renaisa; Holl, Jennifer; Roberts, Sarah Cm

    2018-04-01

    Earlier pregnancy discovery is important in the context of prenatal and abortion care. We evaluated characteristics associated with later pregnancy discovery among women seeking abortion care. Data come from a survey of women seeking abortion care at four family planning facilities in Utah. The participants completed a survey during the state-mandated abortion information visit they are required to complete prior to having an abortion. The outcome in this study was pregnancy discovery before versus after 6 weeks since respondents' last menstrual period (LMP). We used logistic regression to estimate the relationship between sociodemographic and health-related independent variables of interest and pregnancy discovery before versus after 6 weeks. Among the 458 women in the sample, 28% discovered their pregnancy later than 6 weeks since LMP. Most (n=366, 80%) knew the exact date of their LMP and a significant minority estimated it (n=92, 20%). Those who estimated the date of their LMP had higher odds of later pregnancy discovery than those who knew the exact date (adjusted odds ratio (aOR)=1.81[1.07-3.07]). Those who used illicit drugs weekly, daily, or almost daily had higher odds of later pregnancy discovery (aOR=6.33[2.44, 16.40]). Women who did not track their menstrual periods and those who frequently used drugs had higher odds of discovering their pregnancies later. Women who estimated the date of their LMP and who frequently used drugs may benefit from strategies to help them recognize their pregnancies earlier and link them to care when they discover their pregnancies later. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and Collaboration

    Science.gov (United States)

    Seul, M.; Brazil, L.; Castronova, A. M.

    2017-12-01

    CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and CollaborationEnabling research surrounding interdisciplinary topics often requires a combination of finding, managing, and analyzing large data sets and models from multiple sources. This challenge has led the National Science Foundation to make strategic investments in developing community data tools and cyberinfrastructure that focus on water data, as it is central need for many of these research topics. CUAHSI (The Consortium of Universities for the Advancement of Hydrologic Science, Inc.) is a non-profit organization funded by the National Science Foundation to aid students, researchers, and educators in using and managing data and models to support research and education in the water sciences. This presentation will focus on open-source CUAHSI-supported tools that enable enhanced data discovery online using advanced searching capabilities and computational analysis run in virtual environments pre-designed for educators and scientists so they can focus their efforts on data analysis rather than IT set-up.

  7. Three-dimensional compound comparison methods and their application in drug discovery.

    Science.gov (United States)

    Shin, Woong-Hee; Zhu, Xiaolei; Bures, Mark Gregory; Kihara, Daisuke

    2015-07-16

    Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS) methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D). Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.

  8. Accelerating target discovery using pre-competitive open science-patients need faster innovation more than anyone else.

    Science.gov (United States)

    Low, Eric; Bountra, Chas; Lee, Wen Hwa

    2016-01-01

    We are experiencing a new era enabled by unencumbered access to high quality data through the emergence of open science initiatives in the historically challenging area of early stage drug discovery. At the same time, many patient-centric organisations are taking matters into their own hands by participating in, enabling and funding research. Here we present the rationale behind the innovative partnership between the Structural Genomics Consortium (SGC)-an open, pre-competitive pre-clinical research consortium and the research-focused patient organisation Myeloma UK to create a new, comprehensive platform to accelerate the discovery and development of new treatments for multiple myeloma.

  9. Penicillin’s Discovery and Antibiotic Resistance: Lessons for the Future?

    Science.gov (United States)

    
Lobanovska, Mariya; Pilla, Giulia

    2017-01-01

    Undoubtedly, the discovery of penicillin is one of the greatest milestones in modern medicine. 2016 marks the 75th anniversary of the first systemic administration of penicillin in humans, and is therefore an occasion to reflect upon the extraordinary impact that penicillin has had on the lives of millions of people since. This perspective presents a historical account of the discovery of the wonder drug, describes the biological nature of penicillin, and considers lessons that can be learned from the golden era of antibiotic research, which took place between the 1940s and 1960s. Looking back at the history of penicillin might help us to relive this journey to find new treatments and antimicrobial agents. This is particularly relevant today as the emergence of multiple drug resistant bacteria poses a global threat, and joint efforts are needed to combat the rise and spread of resistance. PMID:28356901

  10. Wnt Drug Discovery: Weaving Through the Screens, Patents and Clinical Trials

    Directory of Open Access Journals (Sweden)

    Benjamin Lu

    2016-09-01

    Full Text Available The Wnt signaling pathway is intricately involved in many aspects of development and is the root cause of an increasing number of diseases. For example, colorectal cancer is the second leading cause of death in the industrialized world and aberration of Wnt signaling within the colonic stem cell is the cause of more than 90% of these cancers. Despite our advances in successfully targeting other pathways, such as Human Epidermal Growth Factor Receptor 2 (HER2, there are no clinically relevant therapies available for Wnt-related diseases. Here, we investigated where research activities are focused with respect to Wnt signaling modulators by searching the United States Patent and Trade Office (USPTO for patents and patent applications related to Wnt modulators and compared this to clinical trials focusing on Wnt modulation. We found that while the transition of intellectual property surrounding the Wnt ligand-receptor interface to clinical trials is robust, this is not true for specific inhibitors of β-catenin, which is constitutively active in many cancers. Considering the ubiquitous use of the synthetic T-cell Factor/Lymphoid Enhancer Factor (TCF/Lef reporter system and its success in identifying novel modulators in vitro, we speculate that this model of drug discovery does not capture the complexity of in vivo Wnt signaling that may be required if we are to successfully target the Wnt pathway in the clinic. Notwithstanding, increasingly more complex models are being developed, which may not be high throughput, but more pragmatic in our pursuit to control Wnt signaling.

  11. Drug nanocrystals for the formulation of poorly soluble drugs and its application as a potential drug delivery system

    International Nuclear Information System (INIS)

    Gao Lei; Zhang Dianrui; Chen Minghui

    2008-01-01

    Formulation of poorly soluble drugs is a general intractable problem in pharmaceutical field, especially those compounds poorly soluble in both aqueous and organic media. It is difficult to resolve this problem using conventional formulation approaches, so many drugs are abandoned early in discovery. Nanocrystals, a new carrier-free colloidal drug delivery system with a particle size ranging from 100 to 1000 nm, is thought as a viable drug delivery strategy to develop the poorly soluble drugs, because of their simplicity in preparation and general applicability. In this article, the product techniques of the nanocrystals were reviewed and compared, the special features of drug nanocrystals were discussed. The researches on the application of the drug nanocrystals to various administration routes were described in detail. In addition, as introduced later, the nanocrystals could be easily scaled up, which was the prerequisite to the development of a delivery system as a market product

  12. Text mining-based in silico drug discovery in oral mucositis caused by high-dose cancer therapy.

    Science.gov (United States)

    Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C

    2018-08-01

    Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.

  13. Blood-brain barrier in vitro models as tools in drug discovery: assessment of the transport ranking of antihistaminic drugs.

    Science.gov (United States)

    Neuhaus, W; Mandikova, J; Pawlowitsch, R; Linz, B; Bennani-Baiti, B; Lauer, R; Lachmann, B; Noe, C R

    2012-05-01

    In the course of our validation program testing blood-brain barrier (BBB) in vitro models for their usability as tools in drug discovery it was evaluated whether an established Transwell model based on porcine cell line PBMEC/C1-2 was able to differentiate between the transport properties of first and second generation antihistaminic drugs. First generation antihistamines can permeate the BBB and act in the central nervous system (CNS), whereas entry to the CNS of second generation antihistamines is restricted by efflux pumps such as P-glycoprotein (P-gP) located in brain endothelial cells. P-gP functionality of PBMEC/C1-2 cells grown on Transwell filter inserts was proven by transport studies with P-gP substrate rhodamine 123 and P-gP blocker verapamil. Subsequent drug transport studies with the first generation antihistamines promethazine, diphenhydramine and pheniramine and the second generation antihistamines astemizole, ceterizine, fexofenadine and loratadine were accomplished in single substance as well as in group studies. Results were normalised to diazepam, an internal standard for the transcellular transport route. Moreover, effects after addition of P-gP inhibitor verapamil were investigated. First generation antihistamine pheniramine permeated as fastest followed by diphenhydramine, diazepam, promethazine and second generation antihistaminic drugs ceterizine, fexofenadine, astemizole and loratadine reflecting the BBB in vivo permeability ranking well. Verapamil increased the transport rates of all second generation antihistamines, which suggested involvement of P-gP during their permeation across the BBB model. The ranking after addition of verapamil was significantly changed, only fexofenadine and ceterizine penetrated slower than internal standard diazepam in the presence of verapamil. In summary, permeability data showed that the BBB model based on porcine cell line PBMEC/C1-2 was able to reflect the BBB in vivo situation for the transport of

  14. Drug promotion practices: A review.

    Science.gov (United States)

    Jacob, Nilan T

    2018-01-18

    Over the years, the pharmaceutical industry has been at the forefront of research and innovation in drug discovery and development. The process of drug discovery extending from preclinical studies to multicentric clinical trials and postmarketing phase is a costly affair running into billions of dollars. On the flip side, not all investigational molecules clear the trial phases and get approved, which puts pressure on the manufacturers to maximize the profit from approved drugs. It is in this key area that the practice of drug promotion plays its role. The World Health Organization defines drug promotion as "all informational and persuasive activities by manufacturers and distributors, the effect of which is to influence the prescription, supply, purchase or use of medicinal drugs". With its humble intent of creating awareness among healthcare professionals and updating their knowledge on recent advances in treatment options, drug promotion has been an important tool, but gradually it has evolved to embrace aggressive marketing strategies and sometimes unethical business and scientific practices where the need for profit-making eclipses commitment to patient care and scientific exploration. In this review, we discuss the evolution of drug promotion practices, the various types, its merits and demerits, the influence of drug promotion on physician prescribing behaviour, the role of regulatory bodies, unethical promotional practices and finally summarize with future directions. © 2018 The British Pharmacological Society.

  15. Novel approaches to develop community-built biological network models for potential drug discovery.

    Science.gov (United States)

    Talikka, Marja; Bukharov, Natalia; Hayes, William S; Hofmann-Apitius, Martin; Alexopoulos, Leonidas; Peitsch, Manuel C; Hoeng, Julia

    2017-08-01

    Hundreds of thousands of data points are now routinely generated in clinical trials by molecular profiling and NGS technologies. A true translation of this data into knowledge is not possible without analysis and interpretation in a well-defined biology context. Currently, there are many public and commercial pathway tools and network models that can facilitate such analysis. At the same time, insights and knowledge that can be gained is highly dependent on the underlying biological content of these resources. Crowdsourcing can be employed to guarantee the accuracy and transparency of the biological content underlining the tools used to interpret rich molecular data. Areas covered: In this review, the authors describe crowdsourcing in drug discovery. The focal point is the efforts that have successfully used the crowdsourcing approach to verify and augment pathway tools and biological network models. Technologies that enable the building of biological networks with the community are also described. Expert opinion: A crowd of experts can be leveraged for the entire development process of biological network models, from ontologies to the evaluation of their mechanistic completeness. The ultimate goal is to facilitate biomarker discovery and personalized medicine by mechanistically explaining patients' differences with respect to disease prevention, diagnosis, and therapy outcome.

  16. The Elements of Antifungal Drug Discovery

    DEFF Research Database (Denmark)

    Kjellerup, Lasse

    In this PhD thesis I will explore the development of antifungal drugs. Fungal infections are estimated to cause the death of 1.5 million patients each year. There is currently a need for new antifungal drugs as the existing drugs are hampered by lack of broad-spectrum antifungal activity, resista...

  17. Drugability of extracellular targets: discovery of small molecule drugs targeting allosteric, functional, and subunit-selective sites on GPCRs and ion channels.

    Science.gov (United States)

    Grigoriadis, Dimitri E; Hoare, Samuel R J; Lechner, Sandra M; Slee, Deborah H; Williams, John A

    2009-01-01

    Beginning with the discovery of the structure of deoxyribose nucleic acid in 1953, by James Watson and Francis Crick, the sequencing of the entire human genome some 50 years later, has begun to quantify the classes and types of proteins that may have relevance to human disease with the promise of rapidly identifying compounds that can modulate these proteins so as to have a beneficial and therapeutic outcome. This so called 'drugable space' involves a variety of membrane-bound proteins including the superfamily of G-protein-coupled receptors (GPCRs), ion channels, and transporters among others. The recent number of novel therapeutics targeting membrane-bound extracellular proteins that have reached the market in the past 20 years however pales in magnitude when compared, during the same timeframe, to the advancements made in the technologies available to aid in the discovery of these novel therapeutics. This review will consider select examples of extracellular drugable targets and focus on the GPCRs and ion channels highlighting the corticotropin releasing factor (CRF) type 1 and gamma-aminobutyric acid receptors, and the Ca(V)2.2 voltage-gated ion channel. These examples will elaborate current technological advancements in drug discovery and provide a prospective framework for future drug development.

  18. Design Principles for Fragment Libraries: Maximizing the Value of Learnings from Pharma Fragment-Based Drug Discovery (FBDD) Programs for Use in Academia.

    Science.gov (United States)

    Keserű, György M; Erlanson, Daniel A; Ferenczy, György G; Hann, Michael M; Murray, Christopher W; Pickett, Stephen D

    2016-09-22

    Fragment-based drug discovery (FBDD) is well suited for discovering both drug leads and chemical probes of protein function; it can cover broad swaths of chemical space and allows the use of creative chemistry. FBDD is widely implemented for lead discovery in industry but is sometimes used less systematically in academia. Design principles and implementation approaches for fragment libraries are continually evolving, and the lack of up-to-date guidance may prevent more effective application of FBDD in academia. This Perspective explores many of the theoretical, practical, and strategic considerations that occur within FBDD programs, including the optimal size, complexity, physicochemical profile, and shape profile of fragments in FBDD libraries, as well as compound storage, evaluation, and screening technologies. This compilation of industry experience in FBDD will hopefully be useful for those pursuing FBDD in academia.

  19. Zika antiviral chemotherapy: identification of drugs and promising starting points for drug discovery from an FDA-approved library [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Bruno S. Pascoalino

    2016-10-01

    Full Text Available Background The recent epidemics of Zika virus (ZIKV implicated it as the cause of serious and potentially lethal congenital conditions such microcephaly and other central nervous system defects, as well as the development of the Guillain-Barré syndrome in otherwise healthy patients. Recent findings showed that anti-Dengue antibodies are capable of amplifying ZIKV infection by a mechanism similar to antibody-dependent enhancement, increasing the severity of the disease. This scenario becomes potentially catastrophic when the global burden of Dengue and the advent of the newly approved anti-Dengue vaccines in the near future are taken into account. Thus, antiviral chemotherapy should be pursued as a priority strategy to control the spread of the virus and prevent the complications associated with Zika. Methods Here we describe a fast and reliable cell-based, high-content screening assay for discovery of anti-ZIKV compounds. This methodology has been used to screen the National Institute of Health Clinical Collection compound library, a small collection of FDA-approved drugs. Results and conclusion From 725 FDA-approved compounds triaged, 29 (4% were found to have anti-Zika virus activity, of which 22 had confirmed (76% of confirmation by dose-response curves. Five candidates presented selective activity against ZIKV infection and replication in a human cell line. These hits have abroad spectrum of chemotypes and therapeutic uses, offering valuable opportunities for selection of leads for antiviral drug discovery.

  20. NCI Program for Natural Product Discovery: A Publicly-Accessible Library of Natural Product Fractions for High-Throughput Screening.

    Science.gov (United States)

    Thornburg, Christopher C; Britt, John R; Evans, Jason R; Akee, Rhone K; Whitt, James A; Trinh, Spencer K; Harris, Matthew J; Thompson, Jerell R; Ewing, Teresa L; Shipley, Suzanne M; Grothaus, Paul G; Newman, David J; Schneider, Joel P; Grkovic, Tanja; O'Keefe, Barry R

    2018-06-13

    The US National Cancer Institute's (NCI) Natural Product Repository is one of the world's largest, most diverse collections of natural products containing over 230,000 unique extracts derived from plant, marine, and microbial organisms that have been collected from biodiverse regions throughout the world. Importantly, this national resource is available to the research community for the screening of extracts and the isolation of bioactive natural products. However, despite the success of natural products in drug discovery, compatibility issues that make extracts challenging for liquid handling systems, extended timelines that complicate natural product-based drug discovery efforts and the presence of pan-assay interfering compounds have reduced enthusiasm for the high-throughput screening (HTS) of crude natural product extract libraries in targeted assay systems. To address these limitations, the NCI Program for Natural Product Discovery (NPNPD), a newly launched, national program to advance natural product discovery technologies and facilitate the discovery of structurally defined, validated lead molecules ready for translation will create a prefractionated library from over 125,000 natural product extracts with the aim of producing a publicly-accessible, HTS-amenable library of >1,000,000 fractions. This library, representing perhaps the largest accumulation of natural-product based fractions in the world, will be made available free of charge in 384-well plates for screening against all disease states in an effort to reinvigorate natural product-based drug discovery.

  1. Collaborative translational research leading to multicenter clinical trials in Duchenne muscular dystrophy: the Cooperative International Neuromuscular Research Group (CINRG).

    Science.gov (United States)

    Escolar, Diana M; Henricson, Erik K; Pasquali, Livia; Gorni, Ksenija; Hoffman, Eric P

    2002-10-01

    Progress in the development of rationally based therapies for Duchenne muscular dystrophy has been accelerated by encouraging multidisciplinary, multi-institutional collaboration between basic science and clinical investigators in the Cooperative International Research Group. We combined existing research efforts in pathophysiology by a gene expression profiling laboratory with the efforts of animal facilities capable of conducting high-throughput drug screening and toxicity testing to identify safe and effective drug compounds that target different parts of the pathophysiologic cascade in a genome-wide drug discovery approach. Simultaneously, we developed a clinical trial coordinating center and an international network of collaborating physicians and clinics where those drugs could be tested in large-scale clinical trials. We hope that by bringing together investigators at these facilities and providing the infrastructure to support their research, we can rapidly move new bench discoveries through animal model screening and into therapeutic testing in humans in a safe, timely and cost-effective setting.

  2. Progressing from programmatic to discovery research: a case example with the overjustification effect.

    OpenAIRE

    Roane, Henry S; Fisher, Wayne W; McDonough, Erin M

    2003-01-01

    Scientific research progresses along planned (programmatic research) and unplanned (discovery research) paths. In the current investigation, we attempted to conduct a single-case evaluation of the overjustification effect (i.e., programmatic research). Results of the initial analysis were contrary to the overjustification hypothesis in that removal of the reward contingency produced an increase in responding. Based on this unexpected finding, we conducted subsequent analyses to further evalua...

  3. Center for Drug Evaluation and Research

    Data.gov (United States)

    Federal Laboratory Consortium — The Center for Drug Evaluation and Research(CDER) performs an essential public health task by making sure that safe and effective drugs are available to improve the...

  4. Three-Dimensional Compound Comparison Methods and Their Application in Drug Discovery

    Directory of Open Access Journals (Sweden)

    Woong-Hee Shin

    2015-07-01

    Full Text Available Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D, two-dimensional (2D, and three-dimensional (3D. Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.

  5. Towards a privacy preserving cohort discovery framework for clinical research networks.

    Science.gov (United States)

    Yuan, Jiawei; Malin, Bradley; Modave, François; Guo, Yi; Hogan, William R; Shenkman, Elizabeth; Bian, Jiang

    2017-02-01

    The last few years have witnessed an increasing number of clinical research networks (CRNs) focused on building large collections of data from electronic health records (EHRs), claims, and patient-reported outcomes (PROs). Many of these CRNs provide a service for the discovery of research cohorts with various health conditions, which is especially useful for rare diseases. Supporting patient privacy can enhance the scalability and efficiency of such processes; however, current practice mainly relies on policy, such as guidelines defined in the Health Insurance Portability and Accountability Act (HIPAA), which are insufficient for CRNs (e.g., HIPAA does not require encryption of data - which can mitigate insider threats). By combining policy with privacy enhancing technologies we can enhance the trustworthiness of CRNs. The goal of this research is to determine if searchable encryption can instill privacy in CRNs without sacrificing their usability. We developed a technique, implemented in working software to enable privacy-preserving cohort discovery (PPCD) services in large distributed CRNs based on elliptic curve cryptography (ECC). This technique also incorporates a block indexing strategy to improve the performance (in terms of computational running time) of PPCD. We evaluated the PPCD service with three real cohort definitions: (1) elderly cervical cancer patients who underwent radical hysterectomy, (2) oropharyngeal and tongue cancer patients who underwent robotic transoral surgery, and (3) female breast cancer patients who underwent mastectomy) with varied query complexity. These definitions were tested in an encrypted database of 7.1 million records derived from the publically available Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS). We assessed the performance of the PPCD service in terms of (1) accuracy in cohort discovery, (2) computational running time, and (3) privacy afforded to the underlying records during PPCD. The

  6. Numerate Intends to Join ATOM Consortium to Rapidly Accelerate Preclinical Drug Development | Frederick National Laboratory for Cancer Research

    Science.gov (United States)

    SAN FRANCISCO – Computational drug design company Numerate has signed a letter of intent to join an open consortium of scientists staffed from two U.S. national laboratories, industry, and academia working to transform drug discovery and developmen

  7. Symbiotic Microbes from Marine Invertebrates: Driving a New Era of Natural Product Drug Discovery

    Directory of Open Access Journals (Sweden)

    Alix Blockley

    2017-10-01

    Full Text Available Invertebrates account for more than 89% of all extant organisms in the marine environment, represented by over 174,600 species (recorded to date. Such diversity is mirrored in (or more likely increased by the microbial symbionts associated with this group and in the marine natural products (or MNPs that they produce. Since the early 1950s over 20,000 MNPs have been discovered, including compounds produced by symbiotic bacteria, and the chemical diversity of compounds produced from marine sources has led to them being referred to as "blue gold" in the search for new drugs. For example, 80% of novel antibiotics stemming from the marine environment have come from Actinomycetes, many of which can be found associated with marine sponges, and compounds with anti-tumorigenic and anti-diabetic potential have also been isolated from marine symbionts. In fact, it has been estimated that marine sources formed the basis of over 50% of FDA-approved drugs between 1981 and 2002. In this review, we explore the diversity of marine microbial symbionts by examining their use as the producers of novel pharmaceutical actives, together with a discussion of the opportunities and constraints offered by “blue gold” drug discovery.

  8. An update on the use of C. elegans for preclinical drug discovery: screening and identifying anti-infective drugs.

    Science.gov (United States)

    Kim, Wooseong; Hendricks, Gabriel Lambert; Lee, Kiho; Mylonakis, Eleftherios

    2017-06-01

    The emergence of antibiotic-resistant and -tolerant bacteria is a major threat to human health. Although efforts for drug discovery are ongoing, conventional bacteria-centered screening strategies have thus far failed to yield new classes of effective antibiotics. Therefore, new paradigms for discovering novel antibiotics are of critical importance. Caenorhabditis elegans, a model organism used for in vivo, offers a promising solution for identification of anti-infective compounds. Areas covered: This review examines the advantages of C. elegans-based high-throughput screening over conventional, bacteria-centered in vitro screens. It discusses major anti-infective compounds identified from large-scale C. elegans-based screens and presents the first clinically-approved drugs, then known bioactive compounds, and finally novel small molecules. Expert opinion: There are clear advantages of using a C. elegans-infection based screening method. A C. elegans-based screen produces an enriched pool of non-toxic, efficacious, potential anti-infectives, covering: conventional antimicrobial agents, immunomodulators, and anti-virulence agents. Although C. elegans-based screens do not denote the mode of action of hit compounds, this can be elucidated in secondary studies by comparing the results to target-based screens, or conducting subsequent target-based screens, including the genetic knock-down of host or bacterial genes.

  9. CRITICAL ASSESSMENT OF CONTRIBUTION FROM INDIAN PUBLICATIONS: THE ROLE OF IN SILICO DESIGNING METHODS LEADING TO DRUGS OR DRUG-LIKE COMPOUNDS USING TEXT BASED MINING AND ASSOCIATION

    Directory of Open Access Journals (Sweden)

    Pawan Kumar

    2017-09-01

    Full Text Available Over the several decades, India is constantly challenged by communicable and non-communicable diseases which are originated either by poor lifestyle or by environmental factors. The pools of diseases are constantly posing serious threats to mankind especially among the poverty-stricken families. Scientific communities across the globe are working continuously to design drug molecules to overcome the burden of these life threaten diseases. In last three decades, many computational algorithms and tools have been developed to identify potential drug targets and their inhibitors. It is believed that computational techniques have reduced the time and money required to develop an inhibitor into drug. However, applicability and deliverability of these in silico techniques in rational drug designing are not fully evaluated. In the present study, PubMed/Medline extracted data driven analysis has been performed to highlight the influence and progress of the theoretical methods in the field of drug discovery across India and compared with the world. Drug discovery related keyword dictionary has been built and utilized to select only drug discovery related PubMed abstract. A second keyword set (related to bioinformatics tools is used for normalized pointwise mutual information (PMI based association analysis. Observations show that drug discovery has been an interdisciplinary research and used many tools starting with QSAR, docking, pharmacophore, Molecular Simulations etc. The publications contributed from India (2% are similar as compared to the contribution in total world publications, suggesting large scope in future. Data coverage as represented since 1990-2015 in PubMed as indicated by number of publications associated with drug discovery is almost same in world and India (~75%. Emerging institutes/Universities are contributing since last 10 years as observed from Indian publication list. However, this method has many limitations as discussed.

  10. 21 CFR 361.1 - Radioactive drugs for certain research uses.

    Science.gov (United States)

    2010-04-01

    ... Research Committee. A Radioactive Drug Research Committee, composed and approved by the Food and Drug... CFR 20.61. Investigator Chairman, Radioactive Drug Research Committee At any time a proposal is... 21 Food and Drugs 5 2010-04-01 2010-04-01 false Radioactive drugs for certain research uses. 361.1...

  11. Mesua beccariana (Clusiaceae, A Source of Potential Anti-cancer Lead Compounds in Drug Discovery

    Directory of Open Access Journals (Sweden)

    Soek Sin Teh

    2012-09-01

    Full Text Available An investigation on biologically active secondary metabolites from the stem bark of Mesua beccariana was carried out. A new cyclodione, mesuadione (1, along with several known constituents which are beccamarin (2, 2,5-dihydroxy-1,3,4-trimethoxy anthraquinone (3, 4-methoxy-1,3,5-trihydroxyanthraquinone (4, betulinic acid (5 and stigmasterol (6 were obtained from this ongoing research. Structures of these compounds were elucidated by extensive spectroscopic methods, including 1D and 2D-NMR, GC-MS, IR and UV techniques. Preliminary tests of the in vitro cytotoxic activities of all the isolated metabolites against a panel of human cancer cell lines Raji (lymphoma, SNU-1 (gastric carcinoma, K562 (erythroleukemia cells, LS-174T (colorectal adenocarcinoma, HeLa (cervical cells, SK-MEL-28 (malignant melanoma cells, NCI-H23 (lung adenocarcinoma, IMR-32 (neuroblastoma and Hep-G2 (hepatocellular liver carcinoma were carried out using an MTT assay. Mesuadione (1, beccamarin (2, betulinic acid (5 and stigmasterol (6 displayed strong inhibition of Raji cell proliferation, while the proliferation rate of SK-MEL-28 and HeLa were strongly inhibited by stigmasterol (6 and beccamarin (2, indicating these secondary metabolites could be anti-cancer lead compounds in drug discovery.

  12. Machine Learning-based Virtual Screening and Its Applications to Alzheimer's Drug Discovery: A Review.

    Science.gov (United States)

    Carpenter, Kristy A; Huang, Xudong

    2018-06-07

    Virtual Screening (VS) has emerged as an important tool in the drug development process, as it conducts efficient in silico searches over millions of compounds, ultimately increasing yields of potential drug leads. As a subset of Artificial Intelligence (AI), Machine Learning (ML) is a powerful way of conducting VS for drug leads. ML for VS generally involves assembling a filtered training set of compounds, comprised of known actives and inactives. After training the model, it is validated and, if sufficiently accurate, used on previously unseen databases to screen for novel compounds with desired drug target binding activity. The study aims to review ML-based methods used for VS and applications to Alzheimer's disease (AD) drug discovery. To update the current knowledge on ML for VS, we review thorough backgrounds, explanations, and VS applications of the following ML techniques: Naïve Bayes (NB), k-Nearest Neighbors (kNN), Support Vector Machines (SVM), Random Forests (RF), and Artificial Neural Networks (ANN). All techniques have found success in VS, but the future of VS is likely to lean more heavily toward the use of neural networks - and more specifically, Convolutional Neural Networks (CNN), which are a subset of ANN that utilize convolution. We additionally conceptualize a work flow for conducting ML-based VS for potential therapeutics of for AD, a complex neurodegenerative disease with no known cure and prevention. This both serves as an example of how to apply the concepts introduced earlier in the review and as a potential workflow for future implementation. Different ML techniques are powerful tools for VS, and they have advantages and disadvantages albeit. ML-based VS can be applied to AD drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  13. Distributed Drug Discovery, Part 2: Global Rehearsal of Alkylating Agents for the Synthesis of Resin-Bound Unnatural Amino Acids and Virtual D3 Catalog Construction

    Science.gov (United States)

    2008-01-01

    Distributed Drug Discovery (D3) proposes solving large drug discovery problems by breaking them into smaller units for processing at multiple sites. A key component of the synthetic and computational stages of D3 is the global rehearsal of prospective reagents and their subsequent use in the creation of virtual catalogs of molecules accessible by simple, inexpensive combinatorial chemistry. The first section of this article documents the feasibility of the synthetic component of Distributed Drug Discovery. Twenty-four alkylating agents were rehearsed in the United States, Poland, Russia, and Spain, for their utility in the synthesis of resin-bound unnatural amino acids 1, key intermediates in many combinatorial chemistry procedures. This global reagent rehearsal, coupled to virtual library generation, increases the likelihood that any member of that virtual library can be made. It facilitates the realistic integration of worldwide virtual D3 catalog computational analysis with synthesis. The second part of this article describes the creation of the first virtual D3 catalog. It reports the enumeration of 24 416 acylated unnatural amino acids 5, assembled from lists of either rehearsed or well-precedented alkylating and acylating reagents, and describes how the resulting catalog can be freely accessed, searched, and downloaded by the scientific community. PMID:19105725

  14. Pharmacological screening technologies for venom peptide discovery.

    Science.gov (United States)

    Prashanth, Jutty Rajan; Hasaballah, Nojod; Vetter, Irina

    2017-12-01

    Venomous animals occupy one of the most successful evolutionary niches and occur on nearly every continent. They deliver venoms via biting and stinging apparatuses with the aim to rapidly incapacitate prey and deter predators. This has led to the evolution of venom components that act at a number of biological targets - including ion channels, G-protein coupled receptors, transporters and enzymes - with exquisite selectivity and potency, making venom-derived components attractive pharmacological tool compounds and drug leads. In recent years, plate-based pharmacological screening approaches have been introduced to accelerate venom-derived drug discovery. A range of assays are amenable to this purpose, including high-throughput electrophysiology, fluorescence-based functional and binding assays. However, despite these technological advances, the traditional activity-guided fractionation approach is time-consuming and resource-intensive. The combination of screening techniques suitable for miniaturization with sequence-based discovery approaches - supported by advanced proteomics, mass spectrometry, chromatography as well as synthesis and expression techniques - promises to further improve venom peptide discovery. Here, we discuss practical aspects of establishing a pipeline for venom peptide drug discovery with a particular emphasis on pharmacology and pharmacological screening approaches. This article is part of the Special Issue entitled 'Venom-derived Peptides as Pharmacological Tools.' Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Informatics-guided procurement of patient samples for biomarker discovery projects in cancer research.

    Science.gov (United States)

    Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H

    2009-02-01

    Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.

  16. Targeting molecular networks for drug research

    Directory of Open Access Journals (Sweden)

    José Pedro Pinto

    2014-06-01

    Full Text Available The study of molecular networks has recently moved into the limelight of biomedical research. While it has certainly provided us with plenty of new insights into cellular mechanisms, the challenge now is how to modify or even restructure these networks. This is especially true for human diseases, which can be regarded as manifestations of distorted states of molecular networks. Of the possible interventions for altering networks, the use of drugs is presently the most feasible. In this mini-review, we present and discuss some exemplary approaches of how analysis of molecular interaction networks can contribute to pharmacology (e.g., by identifying new drug targets or prediction of drug side effects, as well as listing pointers to relevant resources and software to guide future research. We also outline recent progress in the use of drugs for in vitro reprogramming of cells, which constitutes an example par excellence for altering molecular interaction networks with drugs.

  17. Pushing the accelerator - speeding up drug research with accelerator mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Garner, R.C. E-mail: colin.garner@cbams.co.uk; Leong, D

    2000-10-01

    Accelerator mass spectrometry (AMS) is the most sensitive analytical method yet developed for elemental isotope analysis and has a broad range of applications. The measurement of {sup 14}C is of most interest to biomedical researchers but few studies have been reported using AMS in drug discovery and development. For biomedical use, {sup 14}C is incorporated into organic molecules by either radiosynthesis or biosynthetically and the isotope is used as a surrogate for the distribution of the radiolabelled molecule either in animal or human studies. The majority of users of {sup 14}C quantitate the radioactivity using decay counting usually with a liquid scintillation counter (LSC). Our Centre over the past 12 months has been evaluating and validating the use of AMS as an alternative detection method. In vitro spiking studies of human plasma with {sup 14}C-Fluconazole, a prescription antifungal drug has demonstrated an excellent correlation between AMS and LSC (correlation coefficient 0.999). Human Phase I clinical studies have been conducted with radioactive doses ranging from 120 Bq (7000 dpm) to 11 kBq (300 nCi) to provide mass balance, plasma concentration and radioactive metabolite profiling data. Limits of detection of 0.00022 Bq {sup 14}C-labelled drug/ml plasma have been accurately quantitated in a plasma background of 0.0078 Bq/ml (0.013 dpm/ml in a plasma background of 0.47 dpm/ml or 2.72 pMC in a background of 90.19 pMC)

  18. Personalized Medicine: Pharmacogenomics and Drug Development

    Directory of Open Access Journals (Sweden)

    Somayeh Mirsadeghi

    2017-03-01

    Full Text Available Personalized medicine aims is to supply the proper drug to the proper patient within the right dose. Pharmacogenomics (PGx is to recognize genetic variants that may influence drug efficacy and toxicity. All things considered, the fields cover a wide area, including basic drug discovery researches, the genetic origin of pharmacokinetics and pharmacodynamics, novel drug improvement, patient genetic assessment and clinical patient administration. At last, the objective of Pharmacogenomics is to anticipate a patient’s genetic response to a particular drug as a way of presenting the best possible medical treatment. By predicting the drug response of an individual, it will be possible to increase the success of therapies and decrease the incidence of adverse side effect.

  19. Molecularly Imprinted Polymers: Novel Discovery for Drug Delivery.

    Science.gov (United States)

    Dhanashree, Surve; Priyanka, Mohite; Manisha, Karpe; Vilasrao, Kadam

    2016-01-01

    Molecularly imprinted polymers (MIP) are novel carriers synthesized by imprinting of a template over a polymer. This paper presents the recent application of MIP for diagnostic and therapeutic drug delivery. MIP owing to their 3D polymeric structures and due to bond formation with the template serves as a reservoir of active causing stimuli sensitive, enantioselective, targetted and/or controlled release. The review elaborates about key factors for optimization of MIP, controlled release by MIP for various administration routes various forms like patches, contact lenses, nanowires along with illustrations. To overcome the limitation of organic solvent usage causing increased cost, water compatible MIP and use of supercritical fluid technology for molecular imprinting were developed. Novel methods for developing water compatible MIP like pickering emulsion polymerization, co-precipitation method, cyclodextrin imprinting, surface grafting, controlled/living radical chain polymerization methods are described with illustration in this review. Various protein imprinting methods like bulk, epitope and surface imprinting are described along with illustrations. Further, application of MIP in microdevices as biomimetic sensing element for personalized therapy is elaborated. Although development and application of MIP in drug delivery is still at its infancy, constant efforts of researchers will lead to a novel intelligent drug delivery with commercial value. Efforts should be directed in developing solid oral dosage forms consisting of MIP for therapeutic protein and peptide delivery and targeted release of potent drugs addressing life threatening disease like cancer. Amalgamation of bio-engineering and pharmaceutical techniques can make these future prospects into reality.

  20. Early investigations of Ceres and the discovery of Pallas historical studies in asteroid research

    CERN Document Server

    Cunningham, Clifford

    2016-01-01

    An asteroid scholar, Cunningham in this book picks up where his Discovery of the First Asteroid, Ceres left off in telling the story of the impact created by the discovery of this new class of object in the early 1800s. The best and brightest minds of mathematics, science, and philosophy were fascinated by Ceres, and figures as diverse as Gauss, Herschel, Brougham, Kant, and Laplace all contributed something to the conversation. The first few chapters deal with the mathematical and philosophical aspects of the discovery, and the rivalry between Germany and France that so affected science and astronomy of that era. The jockeying for glory over the discovery of Ceres by both Piazzi and Bode is examined in detail, as is the reception given to Herschel’s use of the word 'asteroid.' Archival research that reveals the creator of the word 'asteroid' is presented in this book. Astronomy was a truly cosmopolitan field at the time, spanning across various disciplines, and the discovery of Pallas, a story completely t...