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.

WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures

Directory of Open Access Journals (Sweden)

Kenyon Colin

2009-05-01

Full Text Available Abstract Background Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Motivation Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR, and on a new promising one, glutathione-S-transferase. Methods In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. Results On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. Conclusion The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software

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.

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.

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

Bacterial contamination of computer touch screens.

Science.gov (United States)

Gerba, Charles P; Wuollet, Adam L; Raisanen, Peter; Lopez, Gerardo U

2016-03-01

The goal of this study was to determine the occurrence of opportunistic bacterial pathogens on the surfaces of computer touch screens used in hospitals and grocery stores. Opportunistic pathogenic bacteria were isolated on touch screens in hospitals; Clostridium difficile and vancomycin-resistant Enterococcus and in grocery stores; methicillin-resistant Staphylococcus aureus. Enteric bacteria were more common on grocery store touch screens than on hospital computer touch screens. Published by Elsevier Inc.

Incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery

Science.gov (United States)

Fischer, Marcus; Coleman, Ryan G.; Fraser, James S.; Shoichet, Brian K.

2014-07-01

Proteins fluctuate between alternative conformations, which presents a challenge for ligand discovery because such flexibility is difficult to treat computationally owing to problems with conformational sampling and energy weighting. Here we describe a flexible docking method that samples and weights protein conformations using experimentally derived conformations as a guide. The crystallographically refined occupancies of these conformations, which are observable in an apo receptor structure, define energy penalties for docking. In a large prospective library screen, we identified new ligands that target specific receptor conformations of a cavity in cytochrome c peroxidase, and we confirm both ligand pose and associated receptor conformation predictions by crystallography. The inclusion of receptor flexibility led to ligands with new chemotypes and physical properties. By exploiting experimental measures of loop and side-chain flexibility, this method can be extended to the discovery of new ligands for hundreds of targets in the Protein Data Bank for which similar experimental information is available.

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.

MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters

Directory of Open Access Journals (Sweden)

Abreu Rui MV

2010-10-01

Full Text Available Abstract Background Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. Implementation MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. Conclusion MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a

The Computer Revolution in Science: Steps towards the realization of computer-supported discovery environments

NARCIS (Netherlands)

de Jong, Hidde; Rip, Arie

1997-01-01

The tools that scientists use in their search processes together form so-called discovery environments. The promise of artificial intelligence and other branches of computer science is to radically transform conventional discovery environments by equipping scientists with a range of powerful

Computational discovery of picomolar Q(o) site inhibitors of cytochrome bc1 complex.

Science.gov (United States)

Hao, Ge-Fei; Wang, Fu; Li, Hui; Zhu, Xiao-Lei; Yang, Wen-Chao; Huang, Li-Shar; Wu, Jia-Wei; Berry, Edward A; Yang, Guang-Fu

2012-07-11

A critical challenge to the fragment-based drug discovery (FBDD) is its low-throughput nature due to the necessity of biophysical method-based fragment screening. Herein, a method of pharmacophore-linked fragment virtual screening (PFVS) was successfully developed. Its application yielded the first picomolar-range Q(o) site inhibitors of the cytochrome bc(1) complex, an important membrane protein for drug and fungicide discovery. Compared with the original hit compound 4 (K(i) = 881.80 nM, porcine bc(1)), the most potent compound 4f displayed 20 507-fold improved binding affinity (K(i) = 43.00 pM). Compound 4f was proved to be a noncompetitive inhibitor with respect to the substrate cytochrome c, but a competitive inhibitor with respect to the substrate ubiquinol. Additionally, we determined the crystal structure of compound 4e (K(i) = 83.00 pM) bound to the chicken bc(1) at 2.70 Å resolution, providing a molecular basis for understanding its ultrapotency. To our knowledge, this study is the first application of the FBDD method in the discovery of picomolar inhibitors of a membrane protein. This work demonstrates that the novel PFVS approach is a high-throughput drug discovery method, independent of biophysical screening techniques.

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.

Computational Discovery of Materials Using the Firefly Algorithm

Science.gov (United States)

Avendaño-Franco, Guillermo; Romero, Aldo

Our current ability to model physical phenomena accurately, the increase computational power and better algorithms are the driving forces behind the computational discovery and design of novel materials, allowing for virtual characterization before their realization in the laboratory. We present the implementation of a novel firefly algorithm, a population-based algorithm for global optimization for searching the structure/composition space. This novel computation-intensive approach naturally take advantage of concurrency, targeted exploration and still keeping enough diversity. We apply the new method in both periodic and non-periodic structures and we present the implementation challenges and solutions to improve efficiency. The implementation makes use of computational materials databases and network analysis to optimize the search and get insights about the geometric structure of local minima on the energy landscape. The method has been implemented in our software PyChemia, an open-source package for materials discovery. We acknowledge the support of DMREF-NSF 1434897 and the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research under Contract 54075-ND10.

Computational methods for a three-dimensional model of the petroleum-discovery process

Science.gov (United States)

Schuenemeyer, J.H.; Bawiec, W.J.; Drew, L.J.

1980-01-01

A discovery-process model devised by Drew, Schuenemeyer, and Root can be used to predict the amount of petroleum to be discovered in a basin from some future level of exploratory effort: the predictions are based on historical drilling and discovery data. Because marginal costs of discovery and production are a function of field size, the model can be used to make estimates of future discoveries within deposit size classes. The modeling approach is a geometric one in which the area searched is a function of the size and shape of the targets being sought. A high correlation is assumed between the surface-projection area of the fields and the volume of petroleum. To predict how much oil remains to be found, the area searched must be computed, and the basin size and discovery efficiency must be estimated. The basin is assumed to be explored randomly rather than by pattern drilling. The model may be used to compute independent estimates of future oil at different depth intervals for a play involving multiple producing horizons. We have written FORTRAN computer programs that are used with Drew, Schuenemeyer, and Root's model to merge the discovery and drilling information and perform the necessary computations to estimate undiscovered petroleum. These program may be modified easily for the estimation of remaining quantities of commodities other than petroleum. ?? 1980.

Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery.

Science.gov (United States)

Therrien, Eric; Englebienne, Pablo; Arrowsmith, Andrew G; Mendoza-Sanchez, Rodrigo; Corbeil, Christopher R; Weill, Nathanael; Campagna-Slater, Valérie; Moitessier, Nicolas

2012-01-23

As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

Pulsar discovery by global volunteer computing.

Science.gov (United States)

Knispel, B; Allen, B; Cordes, J M; Deneva, J S; Anderson, D; Aulbert, C; Bhat, N D R; Bock, O; Bogdanov, S; Brazier, A; Camilo, F; Champion, D J; Chatterjee, S; Crawford, F; Demorest, P B; Fehrmann, H; Freire, P C C; Gonzalez, M E; Hammer, D; Hessels, J W T; Jenet, F A; Kasian, L; Kaspi, V M; Kramer, M; Lazarus, P; van Leeuwen, J; Lorimer, D R; Lyne, A G; Machenschalk, B; McLaughlin, M A; Messenger, C; Nice, D J; Papa, M A; Pletsch, H J; Prix, R; Ransom, S M; Siemens, X; Stairs, I H; Stappers, B W; Stovall, K; Venkataraman, A

2010-09-10

Einstein@Home aggregates the computer power of hundreds of thousands of volunteers from 192 countries to mine large data sets. It has now found a 40.8-hertz isolated pulsar in radio survey data from the Arecibo Observatory taken in February 2007. Additional timing observations indicate that this pulsar is likely a disrupted recycled pulsar. PSR J2007+2722's pulse profile is remarkably wide with emission over almost the entire spin period; the pulsar likely has closely aligned magnetic and spin axes. The massive computing power provided by volunteers should enable many more such discoveries.

A New In Vivo Screening Paradigm to Accelerate Antimalarial Drug Discovery

Science.gov (United States)

Jiménez-Díaz, María Belén; Viera, Sara; Ibáñez, Javier; Mulet, Teresa; Magán-Marchal, Noemí; Garuti, Helen; Gómez, Vanessa; Cortés-Gil, Lorena; Martínez, Antonio; Ferrer, Santiago; Fraile, María Teresa; Calderón, Félix; Fernández, Esther; Shultz, Leonard D.; Leroy, Didier; Wilson, David M.; García-Bustos, José Francisco; Gamo, Francisco Javier; Angulo-Barturen, Iñigo

2013-01-01

The emergence of resistance to available antimalarials requires the urgent development of new medicines. The recent disclosure of several thousand compounds active in vitro against the erythrocyte stage of Plasmodium falciparum has been a major breakthrough, though converting these hits into new medicines challenges current strategies. A new in vivo screening concept was evaluated as a strategy to increase the speed and efficiency of drug discovery projects in malaria. The new in vivo screening concept was developed based on human disease parameters, i.e. parasitemia in the peripheral blood of patients on hospital admission and parasite reduction ratio (PRR), which were allometrically down-scaled into P. berghei-infected mice. Mice with an initial parasitemia (P0) of 1.5% were treated orally for two consecutive days and parasitemia measured 24 h after the second dose. The assay was optimized for detection of compounds able to stop parasite replication (PRR = 1) or induce parasite clearance (PRR >1) with statistical power >99% using only two mice per experimental group. In the P. berghei in vivo screening assay, the PRR of a set of eleven antimalarials with different mechanisms of action correlated with human-equivalent data. Subsequently, 590 compounds from the Tres Cantos Antimalarial Set with activity in vitro against P. falciparum were tested at 50 mg/kg (orally) in an assay format that allowed the evaluation of hundreds of compounds per month. The rate of compounds with detectable efficacy was 11.2% and about one third of active compounds showed in vivo efficacy comparable with the most potent antimalarials used clinically. High-throughput, high-content in vivo screening could rapidly select new compounds, dramatically speeding up the discovery of new antimalarial medicines. A global multilateral collaborative project aimed at screening the significant chemical diversity within the antimalarial in vitro hits described in the literature is a feasible task

A new in vivo screening paradigm to accelerate antimalarial drug discovery.

Directory of Open Access Journals (Sweden)

María Belén Jiménez-Díaz

Full Text Available The emergence of resistance to available antimalarials requires the urgent development of new medicines. The recent disclosure of several thousand compounds active in vitro against the erythrocyte stage of Plasmodium falciparum has been a major breakthrough, though converting these hits into new medicines challenges current strategies. A new in vivo screening concept was evaluated as a strategy to increase the speed and efficiency of drug discovery projects in malaria. The new in vivo screening concept was developed based on human disease parameters, i.e. parasitemia in the peripheral blood of patients on hospital admission and parasite reduction ratio (PRR, which were allometrically down-scaled into P. berghei-infected mice. Mice with an initial parasitemia (P0 of 1.5% were treated orally for two consecutive days and parasitemia measured 24 h after the second dose. The assay was optimized for detection of compounds able to stop parasite replication (PRR = 1 or induce parasite clearance (PRR >1 with statistical power >99% using only two mice per experimental group. In the P. berghei in vivo screening assay, the PRR of a set of eleven antimalarials with different mechanisms of action correlated with human-equivalent data. Subsequently, 590 compounds from the Tres Cantos Antimalarial Set with activity in vitro against P. falciparum were tested at 50 mg/kg (orally in an assay format that allowed the evaluation of hundreds of compounds per month. The rate of compounds with detectable efficacy was 11.2% and about one third of active compounds showed in vivo efficacy comparable with the most potent antimalarials used clinically. High-throughput, high-content in vivo screening could rapidly select new compounds, dramatically speeding up the discovery of new antimalarial medicines. A global multilateral collaborative project aimed at screening the significant chemical diversity within the antimalarial in vitro hits described in the literature is a

Computer screens and brain cancer

International Nuclear Information System (INIS)

Wood, A.W.

1995-01-01

Australia, both in the media and at the federal government level, over possible links between screen-based computer use and cancer, brain tumour in particular. The screen emissions assumed to be the sources of the putative hazard are the magnetic fields responsible for horizontal and vertical scanning of the display. Time-varying fluctuations in these magnetic fields induce electrical current flows in exposed tissues. This paper estimates that the induced current densities in the brain of the computer user are up to 1 mA/m 2 (due to the vertical flyback). Corresponding values for other electrical appliances or installations are in general much less than this. The epidemiological literature shows no obvious signs of a sudden increase in brain tumour incidence, but the widespread use of computers is a relatively recent phenomenon. The occupational use of other equipment based on cathode ray tubes (such as TV repair) has a much longer history and has been statistically linked to brain tumour in some studies. A number of factors make this an unreliable indicator of the risk from computer screens, however. 42 refs., 3 tabs., 2 figs

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.

Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

Directory of Open Access Journals (Sweden)

Yuri Pevzner

2014-05-01

Full Text Available Inherent biological viability and diversity of natural products make them a potentially rich source for new therapeutics. However, identification of bioactive compounds with desired therapeutic effects and identification of their protein targets is a laborious, expensive process. Extracts from organism samples may show desired activity in phenotypic assays but specific bioactive compounds must be isolated through further separation methods and protein targets must be identified by more specific phenotypic and in vitro experimental assays. Still, questions remain as to whether all relevant protein targets for a compound have been identified. The desire is to understand breadth of purposing for the compound to maximize its use and intellectual property, and to avoid further development of compounds with insurmountable adverse effects. Previously we developed a Virtual Target Screening system that computationally screens one or more compounds against a collection of virtual protein structures. By scoring each compound-protein interaction, we can compare against averaged scores of synthetic drug-like compounds to determine if a particular protein would be a potential target of a compound of interest. Here we provide examples of natural products screened through our system as we assess advantages and shortcomings of our current system in regards to natural product drug discovery.

Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

Directory of Open Access Journals (Sweden)

Yuri Pevzner

2015-08-01

Full Text Available Inherent biological viability and diversity of natural products make them a potentially rich source for new therapeutics. However, identification of bioactive compounds with desired therapeutic effects and identification of their protein targets is a laborious, expensive process. Extracts from organism samples may show desired activity in phenotypic assays but specific bioactive compounds must be isolated through further separation methods and protein targets must be identified by more specific phenotypic and in vitro experimental assays. Still, questions remain as to whether all relevant protein targets for a compound have been identified. The desire is to understand breadth of purposing for the compound to maximize its use and intellectual property, and to avoid further development of compounds with insurmountable adverse effects. Previously we developed a Virtual Target Screening system that computationally screens one or more compounds against a collection of virtual protein structures. By scoring each compound-protein interaction, we can compare against averaged scores of synthetic drug-like compounds to determine if a particular protein would be a potential target of a compound of interest. Here we provide examples of natural products screened through our system as we assess advantages and shortcomings of our current system in regards to natural product drug discovery.

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.

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

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.

Binding-site assessment by virtual fragment screening.

Directory of Open Access Journals (Sweden)

Niu Huang

2010-04-01

Full Text Available The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock approximately 11,000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors.

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...

Discovery of novel selenium derivatives as Pin1 inhibitors by high-throughput screening

International Nuclear Information System (INIS)

Subedi, Amit; Shimizu, Takeshi; Ryo, Akihide; Sanada, Emiko; Watanabe, Nobumoto; Osada, Hiroyuki

2016-01-01

Peptidyl prolyl cis/trans isomerization by Pin1 regulates various oncogenic signals during cancer progression, and its inhibition through multiple approaches has established Pin1 as a therapeutic target. However, lack of simplified screening systems has limited the discovery of potent Pin1 inhibitors. We utilized phosphorylation-dependent binding of Pin1 to its specific substrate to develop a screening system for Pin1 inhibitors. Using this system, we screened a chemical library, and identified a novel selenium derivative as Pin1 inhibitor. Based on structure-activity guided chemical synthesis, we developed more potent Pin1 inhibitors that inhibited cancer cell proliferation. -- Highlights: •Novel screening for Pin1 inhibitors based on Pin1 binding is developed. •A novel selenium compound is discovered as Pin1 inhibitor. •Activity guided chemical synthesis of selenium derivatives resulted potent Pin1 inhibitors.

Computational discovery of extremal microstructure families

Science.gov (United States)

Chen, Desai; Skouras, Mélina; Zhu, Bo; Matusik, Wojciech

2018-01-01

Modern fabrication techniques, such as additive manufacturing, can be used to create materials with complex custom internal structures. These engineered materials exhibit a much broader range of bulk properties than their base materials and are typically referred to as metamaterials or microstructures. Although metamaterials with extraordinary properties have many applications, designing them is very difficult and is generally done by hand. We propose a computational approach to discover families of microstructures with extremal macroscale properties automatically. Using efficient simulation and sampling techniques, we compute the space of mechanical properties covered by physically realizable microstructures. Our system then clusters microstructures with common topologies into families. Parameterized templates are eventually extracted from families to generate new microstructure designs. We demonstrate these capabilities on the computational design of mechanical metamaterials and present five auxetic microstructure families with extremal elastic material properties. Our study opens the way for the completely automated discovery of extremal microstructures across multiple domains of physics, including applications reliant on thermal, electrical, and magnetic properties. PMID:29376124

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.

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.

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

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.

Recent development of computational resources for new antibiotics discovery

DEFF Research Database (Denmark)

Kim, Hyun Uk; Blin, Kai; Lee, Sang Yup

2017-01-01

Understanding a complex working mechanism of biosynthetic gene clusters (BGCs) encoding secondary metabolites is a key to discovery of new antibiotics. Computational resources continue to be developed in order to better process increasing volumes of genome and chemistry data, and thereby better...

The Discovery of Aurora Kinase Inhibitor by Multi-Docking-Based Virtual Screening

Directory of Open Access Journals (Sweden)

Jun-Tae Kim

2014-11-01

Full Text Available We report the discovery of aurora kinase inhibitor using the fragment-based virtual screening by multi-docking strategy. Among a number of fragments collected from eMololecules, we found four fragment molecules showing potent activity (>50% at 100 μM against aurora kinase. Based on the explored fragment scaffold, we selected two compounds in our synthesized library and validated the biological activity against Aurora kinase.

Discovery of novel-scaffold monoamine transporter ligands via in silico screening with the S1 pocket of the serotonin transporter.

Science.gov (United States)

Nolan, Tammy L; Geffert, Laura M; Kolber, Benedict J; Madura, Jeffry D; Surratt, Christopher K

2014-09-17

Discovery of new inhibitors of the plasmalemmal monoamine transporters (MATs) continues to provide pharmacotherapeutic options for depression, addiction, attention deficit disorders, psychosis, narcolepsy, and Parkinson's disease. The windfall of high-resolution MAT structural information afforded by X-ray crystallography has enabled the construction of credible computational models. Elucidation of lead compounds, creation of compound structure-activity series, and pharmacologic testing are staggering expenses that could be reduced by using a MAT computational model for virtual screening (VS) of structural libraries containing millions of compounds. Here, VS of the PubChem small molecule structural database using the S1 (primary substrate) ligand pocket of a serotonin transporter homology model yielded 19 prominent "hit" compounds. In vitro pharmacology of these VS hits revealed four structurally unique MAT substrate uptake inhibitors with high nanomolar affinity at one or more of the three MATs. In vivo characterization of three of these hits revealed significant activity in a mouse model of acute depression at doses that did not elicit untoward locomotor effects. This constitutes the first report of MAT inhibitor discovery using exclusively the primary substrate pocket as a VS tool. Novel-scaffold MAT inhibitors offer hope of new medications that lack the many classic adverse effects of existing antidepressant drugs.

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.

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.

OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

Science.gov (United States)

Strayer, Michael

2005-01-01

Good morning. Welcome to SciDAC 2005 and San Francisco. SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of twentieth century methodologies, computational science may be said to be transformational. There are a number of examples to this point. First are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment. A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal. SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science. As we look to the immediate future, FY2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations

Computer-aided discovery of antimicrobial agents as potential enoyl ...

African Journals Online (AJOL)

Computer-aided discovery of antimicrobial agents as potential enoyl acyl carrier protein reductase inhibitors. ... Conclusion: Overall, the newly discovered hits can act as a good starting point in the future for the development of safe and potent antibacterial agents. Keywords: Enoyl acyl carrier protein reductase, saFabI, ...

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.

Computer-Aided Drug Design in Epigenetics

Science.gov (United States)

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-03-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

Computer-Aided Drug Design in Epigenetics

Science.gov (United States)

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-01-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field. PMID:29594101

Discovery Mondays: 'The Grid: a universal computer'

CERN Multimedia

2006-01-01

How can one store and analyse the 15 million billion pieces of data that the LHC will produce each year with a computer that isn't the size of a sky-scraper? The IT experts have found the answer: the Grid, which will harness the power of tens of thousands of computers in the world by putting them together on one network and making them work like a single computer achieving a power that has not yet been matched. The Grid, inspired from the Web, already exists - in fact, several of them exist in the field of science. The European EGEE project, led by CERN, contributes not only to the study of particle physics but to medical research as well, notably in the study of malaria and avian flu. The next Discovery Monday invites you to explore this futuristic computing technology. The 'Grid Masters' of CERN have prepared lively animations to help you understand how the Grid works. Children can practice saving the planet on the Grid video game. You will also discover other applications such as UNOSAT, a United Nations...

Cardiac Arrhythmia: In vivo screening in the zebrafish to overcome complexity in drug discovery.

Science.gov (United States)

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

Computational methods for 2D materials: discovery, property characterization, and application design.

Science.gov (United States)

Paul, J T; Singh, A K; Dong, Z; Zhuang, H; Revard, B C; Rijal, B; Ashton, M; Linscheid, A; Blonsky, M; Gluhovic, D; Guo, J; Hennig, R G

2017-11-29

The discovery of two-dimensional (2D) materials comes at a time when computational methods are mature and can predict novel 2D materials, characterize their properties, and guide the design of 2D materials for applications. This article reviews the recent progress in computational approaches for 2D materials research. We discuss the computational techniques and provide an overview of the ongoing research in the field. We begin with an overview of known 2D materials, common computational methods, and available cyber infrastructures. We then move onto the discovery of novel 2D materials, discussing the stability criteria for 2D materials, computational methods for structure prediction, and interactions of monolayers with electrochemical and gaseous environments. Next, we describe the computational characterization of the 2D materials' electronic, optical, magnetic, and superconducting properties and the response of the properties under applied mechanical strain and electrical fields. From there, we move on to discuss the structure and properties of defects in 2D materials, and describe methods for 2D materials device simulations. We conclude by providing an outlook on the needs and challenges for future developments in the field of computational research for 2D materials.

Bioinformatics and biomarker discovery "Omic" data analysis for personalized medicine

CERN Document Server

Azuaje, Francisco

2010-01-01

This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided w

Computer-Aided Drug Design in Epigenetics

Directory of Open Access Journals (Sweden)

Wenchao Lu

2018-03-01

Full Text Available Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

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.

A reliable computational workflow for the selection of optimal screening libraries.

Science.gov (United States)

Gilad, Yocheved; Nadassy, Katalin; Senderowitz, Hanoch

2015-01-01

The experimental screening of compound collections is a common starting point in many drug discovery projects. Successes of such screening campaigns critically depend on the quality of the screened library. Many libraries are currently available from different vendors yet the selection of the optimal screening library for a specific project is challenging. We have devised a novel workflow for the rational selection of project-specific screening libraries. The workflow accepts as input a set of virtual candidate libraries and applies the following steps to each library: (1) data curation; (2) assessment of ADME/T profile; (3) assessment of the number of promiscuous binders/frequent HTS hitters; (4) assessment of internal diversity; (5) assessment of similarity to known active compound(s) (optional); (6) assessment of similarity to in-house or otherwise accessible compound collections (optional). For ADME/T profiling, Lipinski's and Veber's rule-based filters were implemented and a new blood brain barrier permeation model was developed and validated (85 and 74 % success rate for training set and test set, respectively). Diversity and similarity descriptors which demonstrated best performances in terms of their ability to select either diverse or focused sets of compounds from three databases (Drug Bank, CMC and CHEMBL) were identified and used for diversity and similarity assessments. The workflow was used to analyze nine common screening libraries available from six vendors. The results of this analysis are reported for each library providing an assessment of its quality. Furthermore, a consensus approach was developed to combine the results of these analyses into a single score for selecting the optimal library under different scenarios. We have devised and tested a new workflow for the rational selection of screening libraries under different scenarios. The current workflow was implemented using the Pipeline Pilot software yet due to the usage of generic

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.

Benefits of computer screen-based simulation in learning cardiac arrest procedures.

Science.gov (United States)

Bonnetain, Elodie; Boucheix, Jean-Michel; Hamet, Maël; Freysz, Marc

2010-07-01

What is the best way to train medical students early so that they acquire basic skills in cardiopulmonary resuscitation as effectively as possible? Studies have shown the benefits of high-fidelity patient simulators, but have also demonstrated their limits. New computer screen-based multimedia simulators have fewer constraints than high-fidelity patient simulators. In this area, as yet, there has been no research on the effectiveness of transfer of learning from a computer screen-based simulator to more realistic situations such as those encountered with high-fidelity patient simulators. We tested the benefits of learning cardiac arrest procedures using a multimedia computer screen-based simulator in 28 Year 2 medical students. Just before the end of the traditional resuscitation course, we compared two groups. An experiment group (EG) was first asked to learn to perform the appropriate procedures in a cardiac arrest scenario (CA1) in the computer screen-based learning environment and was then tested on a high-fidelity patient simulator in another cardiac arrest simulation (CA2). While the EG was learning to perform CA1 procedures in the computer screen-based learning environment, a control group (CG) actively continued to learn cardiac arrest procedures using practical exercises in a traditional class environment. Both groups were given the same amount of practice, exercises and trials. The CG was then also tested on the high-fidelity patient simulator for CA2, after which it was asked to perform CA1 using the computer screen-based simulator. Performances with both simulators were scored on a precise 23-point scale. On the test on a high-fidelity patient simulator, the EG trained with a multimedia computer screen-based simulator performed significantly better than the CG trained with traditional exercises and practice (16.21 versus 11.13 of 23 possible points, respectively; p<0.001). Computer screen-based simulation appears to be effective in preparing learners to

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.

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.

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.

Lung cancer screening beyond low-dose computed tomography: the role of novel biomarkers.

Science.gov (United States)

Hasan, Naveed; Kumar, Rohit; Kavuru, Mani S

2014-10-01

Lung cancer is the most common and lethal malignancy in the world. The landmark National lung screening trial (NLST) showed a 20% relative reduction in mortality in high-risk individuals with screening low-dose computed tomography. However, the poor specificity and low prevalence of lung cancer in the NLST provide major limitations to its widespread use. Furthermore, a lung nodule on CT scan requires a nuanced and individualized approach towards management. In this regard, advances in high through-put technology (molecular diagnostics, multi-gene chips, proteomics, and bronchoscopic techniques) have led to discovery of lung cancer biomarkers that have shown potential to complement the current screening standards. Early detection of lung cancer can be achieved by analysis of biomarkers from tissue samples within the respiratory tract such as sputum, saliva, nasal/bronchial airway epithelial cells and exhaled breath condensate or through peripheral biofluids such as blood, serum and urine. Autofluorescence bronchoscopy has been employed in research setting to identify pre-invasive lesions not identified on CT scan. Although these modalities are not yet commercially available in clinic setting, they will be available in the near future and clinicians who care for patients with lung cancer should be aware. In this review, we present up-to-date state of biomarker development, discuss their clinical relevance and predict their future role in lung cancer management.

Virtual screening of compound libraries.

Science.gov (United States)

Cerqueira, Nuno M F S A; Sousa, Sérgio F; Fernandes, Pedro A; Ramos, Maria João

2009-01-01

During the last decade, Virtual Screening (VS) has definitively established itself as an important part of the drug discovery and development process. VS involves the selection of likely drug candidates from large libraries of chemical structures by using computational methodologies, but the generic definition of VS encompasses many different methodologies. This chapter provides an introduction to the field by reviewing a variety of important aspects, including the different types of virtual screening methods, and the several steps required for a successful virtual screening campaign within a state-of-the-art approach, from target selection to postfilter application. This analysis is further complemented with a small collection important VS success stories.

Computer Screen Use Detection Using Smart Eyeglasses

Directory of Open Access Journals (Sweden)

Florian Wahl

2017-05-01

Full Text Available Screen use can influence the circadian phase and cause eye strain. Smart eyeglasses with an integrated color light sensor can detect screen use. We present a screen use detection approach based on a light sensor embedded into the bridge of smart eyeglasses. By calculating the light intensity at the user’s eyes for different screens and content types, we found only computer screens to have a significant impact on the circadian phase. Our screen use detection is based on ratios between color channels and used a linear support vector machine to detect screen use. We validated our detection approach in three studies. A test bench was built to detect screen use under different ambient light sources and intensities in a controlled environment. In a lab study, we evaluated recognition performance for different ambient light intensities. By using participant-independent models, we achieved an ROC AUC above 0.9 for ambient light intensities below 200 lx. In a study of typical ADLs, screen use was detected with an average ROC AUC of 0.83 assuming screen use for 30% of the time.

Search of computers for discovery of electronic evidence

Directory of Open Access Journals (Sweden)

Pisarić Milana M.

2015-01-01

Full Text Available In order to address the specific nature of criminal activities committed using computer networks and systems, the efforts of states to adapt or complement the existing criminal law with purposeful provisions is understandable. To create an appropriate legal framework for supressing cybercrime, except the rules of substantive criminal law predict certain behavior as criminal offenses against the confidentiality, integrity and availability of computer data, computer systems and networks, it is essential that the provisions of the criminal procedure law contain adequate powers of competent authorities for detecting sources of illegal activities, or the collection of data on the committed criminal offense and offender, which can be used as evidence in criminal proceedings, taking into account the specificities of cyber crime and the environment within which the illegal activity is undertaken. Accordingly, the provisions of the criminal procedural law should be designed to be able to overcome certain challenges in discovering and proving high technology crime, and the provisions governing search of computer for discovery of electronic evidence is of special importance.

Virtual Screening as a Technique for PPAR Modulator Discovery

Directory of Open Access Journals (Sweden)

Stephanie N. Lewis

2010-01-01

agonists have therapeutic applications as insulin sensitizers in type 2 diabetes or as anti-inflammatories. VS is a cost- and time-effective means for identifying small molecules that have therapeutic potential. Our long-term goal is to devise computational approaches for testing the PPARγ-binding activity of extensive naturally occurring compound libraries prior to testing agonist activity using ligand-binding and reporter assays. This review summarizes the high potential for obtaining further fundamental understanding of PPARγ biology and development of novel therapies for treating chronic inflammatory diseases through evolution and implementation of computational screening processes for immunotherapeutics in conjunction with experimental methods for calibration and validation of results.

Discoveries and application of prostate-specific antigen, and some proposals to optimize prostate cancer screening

Directory of Open Access Journals (Sweden)

Tokudome S

2016-05-01

Full Text Available Shinkan Tokudome,1 Ryosuke Ando,2 Yoshiro Koda,3 1Department of Nutritional Epidemiology, National Institute of Health and Nutrition, Shinjuku-ku, Tokyo, 2Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, 3Department of Forensic Medicine and Human Genetics, Kurume University School of Medicine, Kurume, Japan Abstract: The discoveries and application of prostate-specific antigen (PSA have been much appreciated because PSA-based screening has saved millions of lives of prostate cancer (PCa patients. Historically speaking, Flocks et al first identified antigenic properties in prostate tissue in 1960. Then, Barnes et al detected immunologic characteristics in prostatic fluid in 1963. Hara et al characterized γ-semino-protein in semen in 1966, and it has been proven to be identical to PSA. Subsequently, Ablin et al independently reported the presence of precipitation antigens in the prostate in 1970. Wang et al purified the PSA in 1979, and Kuriyama et al first applied an enzyme-linked immunosorbent assay for PSA in 1980. However, the positive predictive value with a cutoff figure of 4.0 ng/mL appeared substantially low (~30%. There are overdiagnoses and overtreatments for latent/low-risk PCa. Controversies exist in the PCa mortality-reducing effects of PSA screening between the European Randomized Study of Screening for Prostate Cancer (ERSPC and the US Prostate, Lung, Colorectal, and Ovarian (PLCO Cancer Screening Trial. For optimizing PCa screening, PSA-related items may require the following: 1 adjustment of the cutoff values according to age, as well as setting limits to age and screening intervals; 2 improving test performance using doubling time, density, and ratio of free: total PSA; and 3 fostering active surveillance for low-risk PCa with monitoring by PSA value. Other items needing consideration may include the following: 1 examinations of cell proliferation and cell cycle markers

Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

Science.gov (United States)

Hulshof, Casper D.; de Jong, Ton

2006-01-01

Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

Depression screening using the Patient Health Questionnaire-9 administered on a touch screen computer.

Science.gov (United States)

Fann, Jesse R; Berry, Donna L; Wolpin, Seth; Austin-Seymour, Mary; Bush, Nigel; Halpenny, Barbara; Lober, William B; McCorkle, Ruth

2009-01-01

To (1) evaluate the feasibility of touch screen depression screening in cancer patients using the Patient Health Questionnaire-9 (PHQ-9), (2) evaluate the construct validity of the PHQ-9 using the touch screen modality, and (3) examine the prevalence and severity of depression using this screening modality. The PHQ-9 was placed in a web-based survey within a study of the clinical impact of computerized symptom and quality of life screening. Patients in medical oncology, radiation oncology, and hematopoietic stem cell transplantation (HSCT) clinics used the program on a touch screen computer in waiting rooms prior to therapy (T1) and during therapy (T2). Responses of depressed mood or anhedonia (PHQ-2 cardinal depression symptoms) triggered additional items. PHQ-9 scores were provided to the oncology team in real time. Among 342 patients enrolled, 33 (9.6%) at T1 and 69 (20.2%) at T2 triggered the full PHQ-9 by endorsing at least one cardinal symptom. Feasibility was high, with at least 97% completing the PHQ-2 and at least 96% completing the PHQ-9 when triggered and a mean completion time of about 2 min. The PHQ-9 had good construct validity. Medical oncology patients had the highest percent of positive screens (12.9%) at T1, while HSCT patients had the highest percent (30.5%) at T2. Using this method, 21 (6.1%) at T1 and 54 (15.8%) at T2 of the total sample had moderate to severe depression. The PHQ-9 administered on a touch screen computer is feasible and provides valid depression data in a diverse cancer population. (c) 2008 John Wiley & Sons, Ltd.

Difficulties encountered managing nodules detected during a computed tomography lung cancer screening program.

Science.gov (United States)

Veronesi, Giulia; Bellomi, Massimo; Scanagatta, Paolo; Preda, Lorenzo; Rampinelli, Cristiano; Guarize, Juliana; Pelosi, Giuseppe; Maisonneuve, Patrick; Leo, Francesco; Solli, Piergiorgio; Masullo, Michele; Spaggiari, Lorenzo

2008-09-01

The main challenge of screening a healthy population with low-dose computed tomography is to balance the excessive use of diagnostic procedures with the risk of delayed cancer detection. We evaluated the pitfalls, difficulties, and sources of mistakes in the management of lung nodules detected in volunteers in the Cosmos single-center screening trial. A total of 5201 asymptomatic high-risk volunteers underwent screening with multidetector low-dose computed tomography. Nodules detected at baseline or new nodules at annual screening received repeat low-dose computed tomography at 1 year if less than 5 mm, repeat low-dose computed tomography 3 to 6 months later if between 5 and 8 mm, and fluorodeoxyglucose positron emission tomography if more than 8 mm. Growing nodules at the annual screening received low-dose computed tomography at 6 months and computed tomography-positron emission tomography or surgical biopsy according to doubling time, type, and size. During the first year of screening, 106 patients underwent lung biopsy and 91 lung cancers were identified (70% were stage I). Diagnosis was delayed (false-negative) in 6 patients (stage IIB in 1 patient, stage IIIA in 3 patients, and stage IV in 2 patients), including 2 small cell cancers and 1 central lesion. Surgical biopsy revealed benign disease (false-positives) in 15 cases (14%). Positron emission tomography sensitivity was 88% for prevalent cancers and 70% for cancers diagnosed after first annual screening. No needle biopsy procedures were performed in this cohort of patients. Low-dose computed tomography screening is effective for the early detection of lung cancers, but nodule management remains a challenge. Computed tomography-positron emission tomography is useful at baseline, but its sensitivity decreases significantly the subsequent year. Multidisciplinary management and experience are crucial for minimizing misdiagnoses.

Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

Directory of Open Access Journals (Sweden)

Federica Villanova

Full Text Available Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid flow cytometry platform (CFP and a unique lyoplate-based flow cytometry platform (LFP in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10 and activation markers (Foxp3 and CD25. Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

Science.gov (United States)

Villanova, Federica; Di Meglio, Paola; Inokuma, Margaret; Aghaeepour, Nima; Perucha, Esperanza; Mollon, Jennifer; Nomura, Laurel; Hernandez-Fuentes, Maria; Cope, Andrew; Prevost, A Toby; Heck, Susanne; Maino, Vernon; Lord, Graham; Brinkman, Ryan R; Nestle, Frank O

2013-01-01

Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid) flow cytometry platform (CFP) and a unique lyoplate-based flow cytometry platform (LFP) in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10) and activation markers (Foxp3 and CD25). Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

Computed tomographic characteristics of interval and post screen carcinomas in lung cancer screening

International Nuclear Information System (INIS)

Scholten, Ernst T.; Horeweg, Nanda; Koning, Harry J. de; Vliegenthart, Rozemarijn; Oudkerk, Matthijs; Mali, Willem P.T.M.; Jong, Pim A. de

2015-01-01

To analyse computed tomography (CT) findings of interval and post-screen carcinomas in lung cancer screening. Consecutive interval and post-screen carcinomas from the Dutch-Belgium lung cancer screening trial were included. The prior screening and the diagnostic chest CT were reviewed by two experienced radiologists in consensus with knowledge of the tumour location on the diagnostic CT. Sixty-one participants (53 men) were diagnosed with an interval or post-screen carcinoma. Twenty-two (36 %) were in retrospect visible on the prior screening CT. Detection error occurred in 20 cancers and interpretation error in two cancers. Errors involved intrabronchial tumour (n = 5), bulla with wall thickening (n = 5), lymphadenopathy (n = 3), pleural effusion (n = 1) and intraparenchymal solid nodules (n = 8). These were missed because of a broad pleural attachment (n = 4), extensive reticulation surrounding a nodule (n = 1) and extensive scarring (n = 1). No definite explanation other than human error was found in two cases. None of the interval or post-screen carcinomas involved a subsolid nodule. Interval or post-screen carcinomas that were visible in retrospect were mostly due to detection errors of solid nodules, bulla wall thickening or endobronchial lesions. Interval or post-screen carcinomas without explanation other than human errors are rare. (orig.)

Computed tomographic characteristics of interval and post screen carcinomas in lung cancer screening

Energy Technology Data Exchange (ETDEWEB)

Scholten, Ernst T. [University Medical Centre, Department of Radiology, Utrecht (Netherlands); Kennemer Gasthuis, Department of Radiology, Haarlem (Netherlands); Horeweg, Nanda [Erasmus University Medical Centre, Department of Public Health, Rotterdam (Netherlands); Erasmus University Medical Centre, Department of Pulmonary Medicine, Rotterdam (Netherlands); Koning, Harry J. de [Erasmus University Medical Centre, Department of Public Health, Rotterdam (Netherlands); Vliegenthart, Rozemarijn [University of Groningen, University Medical Centre Groningen, Department of Radiology, Groningen (Netherlands); University of Groningen, University Medical Centre Groningen, Center for Medical Imaging-North East Netherlands, Groningen (Netherlands); Oudkerk, Matthijs [University of Groningen, University Medical Centre Groningen, Center for Medical Imaging-North East Netherlands, Groningen (Netherlands); Mali, Willem P.T.M.; Jong, Pim A. de [University Medical Centre, Department of Radiology, Utrecht (Netherlands)

2015-01-15

To analyse computed tomography (CT) findings of interval and post-screen carcinomas in lung cancer screening. Consecutive interval and post-screen carcinomas from the Dutch-Belgium lung cancer screening trial were included. The prior screening and the diagnostic chest CT were reviewed by two experienced radiologists in consensus with knowledge of the tumour location on the diagnostic CT. Sixty-one participants (53 men) were diagnosed with an interval or post-screen carcinoma. Twenty-two (36 %) were in retrospect visible on the prior screening CT. Detection error occurred in 20 cancers and interpretation error in two cancers. Errors involved intrabronchial tumour (n = 5), bulla with wall thickening (n = 5), lymphadenopathy (n = 3), pleural effusion (n = 1) and intraparenchymal solid nodules (n = 8). These were missed because of a broad pleural attachment (n = 4), extensive reticulation surrounding a nodule (n = 1) and extensive scarring (n = 1). No definite explanation other than human error was found in two cases. None of the interval or post-screen carcinomas involved a subsolid nodule. Interval or post-screen carcinomas that were visible in retrospect were mostly due to detection errors of solid nodules, bulla wall thickening or endobronchial lesions. Interval or post-screen carcinomas without explanation other than human errors are rare. (orig.)

How to benchmark methods for structure-based virtual screening of large compound libraries.

Science.gov (United States)

Christofferson, Andrew J; Huang, Niu

2012-01-01

Structure-based virtual screening is a useful computational technique for ligand discovery. To systematically evaluate different docking approaches, it is important to have a consistent benchmarking protocol that is both relevant and unbiased. Here, we describe the designing of a benchmarking data set for docking screen assessment, a standard docking screening process, and the analysis and presentation of the enrichment of annotated ligands among a background decoy database.

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.

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.

Molecular-Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors.

Science.gov (United States)

Martinez-Rosell, Gerard; Harvey, Matt J; De Fabritiis, Gianni

2018-03-26

Fragment-based drug discovery (FBDD) has become a mainstream approach in drug design because it allows the reduction of the chemical space and screening libraries while identifying fragments with high protein-ligand efficiency interactions that can later be grown into drug-like leads. In this work, we leverage high-throughput molecular dynamics (MD) simulations to screen a library of 129 fragments for a total of 5.85 ms against the CXCL12 monomer, a chemokine involved in inflammation and diseases such as cancer. Our in silico binding assay was able to recover binding poses, affinities, and kinetics for the selected library and was able to predict 8 mM-affinity fragments with ligand efficiencies higher than 0.3. All of the fragment hits present a similar chemical structure, with a hydrophobic core and a positively charged group, and bind to either sY7 or H1S68 pockets, where they share pharmacophoric properties with experimentally resolved natural binders. This work presents a large-scale screening assay using an exclusive combination of thousands of short MD adaptive simulations analyzed with a Markov state model (MSM) framework.

A fully automated primary screening system for the discovery of therapeutic antibodies directly from B cells.

Science.gov (United States)

Tickle, Simon; Howells, Louise; O'Dowd, Victoria; Starkie, Dale; Whale, Kevin; Saunders, Mark; Lee, David; Lightwood, Daniel

2015-04-01

For a therapeutic antibody to succeed, it must meet a range of potency, stability, and specificity criteria. Many of these characteristics are conferred by the amino acid sequence of the heavy and light chain variable regions and, for this reason, can be screened for during antibody selection. However, it is important to consider that antibodies satisfying all these criteria may be of low frequency in an immunized animal; for this reason, it is essential to have a mechanism that allows for efficient sampling of the immune repertoire. UCB's core antibody discovery platform combines high-throughput B cell culture screening and the identification and isolation of single, antigen-specific IgG-secreting B cells through a proprietary technique called the "fluorescent foci" method. Using state-of-the-art automation to facilitate primary screening, extremely efficient interrogation of the natural antibody repertoire is made possible; more than 1 billion immune B cells can now be screened to provide a useful starting point from which to identify the rare therapeutic antibody. This article will describe the design, construction, and commissioning of a bespoke automated screening platform and two examples of how it was used to screen for antibodies against two targets. © 2014 Society for Laboratory Automation and Screening.

Discovery of replicating circular RNAs by RNA-seq and computational algorithms.

Directory of Open Access Journals (Sweden)

Zhixiang Zhang

2014-12-01

Full Text Available Replicating circular RNAs are independent plant pathogens known as viroids, or act to modulate the pathogenesis of plant and animal viruses as their satellite RNAs. The rate of discovery of these subviral pathogens was low over the past 40 years because the classical approaches are technical demanding and time-consuming. We previously described an approach for homology-independent discovery of replicating circular RNAs by analysing the total small RNA populations from samples of diseased tissues with a computational program known as progressive filtering of overlapping small RNAs (PFOR. However, PFOR written in PERL language is extremely slow and is unable to discover those subviral pathogens that do not trigger in vivo accumulation of extensively overlapping small RNAs. Moreover, PFOR is yet to identify a new viroid capable of initiating independent infection. Here we report the development of PFOR2 that adopted parallel programming in the C++ language and was 3 to 8 times faster than PFOR. A new computational program was further developed and incorporated into PFOR2 to allow the identification of circular RNAs by deep sequencing of long RNAs instead of small RNAs. PFOR2 analysis of the small RNA libraries from grapevine and apple plants led to the discovery of Grapevine latent viroid (GLVd and Apple hammerhead viroid-like RNA (AHVd-like RNA, respectively. GLVd was proposed as a new species in the genus Apscaviroid, because it contained the typical structural elements found in this group of viroids and initiated independent infection in grapevine seedlings. AHVd-like RNA encoded a biologically active hammerhead ribozyme in both polarities, and was not specifically associated with any of the viruses found in apple plants. We propose that these computational algorithms have the potential to discover novel circular RNAs in plants, invertebrates and vertebrates regardless of whether they replicate and/or induce the in vivo accumulation of small

Virtual Screening Approaches towards the Discovery of Toll-Like Receptor Modulators

Directory of Open Access Journals (Sweden)

Lucía Pérez-Regidor

2016-09-01

Full Text Available This review aims to summarize the latest efforts performed in the search for novel chemical entities such as Toll-like receptor (TLR modulators by means of virtual screening techniques. This is an emergent research field with only very recent (and successful contributions. Identification of drug-like molecules with potential therapeutic applications for the treatment of a variety of TLR-regulated diseases has attracted considerable interest due to the clinical potential. Additionally, the virtual screening databases and computational tools employed have been overviewed in a descriptive way, widening the scope for researchers interested in the field.

UCLA's Molecular Screening Shared Resource: enhancing small molecule discovery with functional genomics and new technology.

Science.gov (United States)

Damoiseaux, Robert

2014-05-01

The Molecular Screening Shared Resource (MSSR) offers a comprehensive range of leading-edge high throughput screening (HTS) services including drug discovery, chemical and functional genomics, and novel methods for nano and environmental toxicology. The MSSR is an open access environment with investigators from UCLA as well as from the entire globe. Industrial clients are equally welcome as are non-profit entities. The MSSR is a fee-for-service entity and does not retain intellectual property. In conjunction with the Center for Environmental Implications of Nanotechnology, the MSSR is unique in its dedicated and ongoing efforts towards high throughput toxicity testing of nanomaterials. In addition, the MSSR engages in technology development eliminating bottlenecks from the HTS workflow and enabling novel assays and readouts currently not available.

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

Blueprint for antimicrobial hit discovery targeting metabolic networks.

Science.gov (United States)

Shen, Y; Liu, J; Estiu, G; Isin, B; Ahn, Y-Y; Lee, D-S; Barabási, A-L; Kapatral, V; Wiest, O; Oltvai, Z N

2010-01-19

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy.

Performance of machine learning methods for ligand-based virtual screening.

Science.gov (United States)

Plewczynski, Dariusz; Spieser, Stéphane A H; Koch, Uwe

2009-05-01

Computational screening of compound databases has become increasingly popular in pharmaceutical research. This review focuses on the evaluation of ligand-based virtual screening using active compounds as templates in the context of drug discovery. Ligand-based screening techniques are based on comparative molecular similarity analysis of compounds with known and unknown activity. We provide an overview of publications that have evaluated different machine learning methods, such as support vector machines, decision trees, ensemble methods such as boosting, bagging and random forests, clustering methods, neuronal networks, naïve Bayesian, data fusion methods and others.

Arecibo PALFA survey and Einstein@Home: binary pulsar discovery by volunteer computing

NARCIS (Netherlands)

Knispel, B.; Lazarus, P.; Allen, B.; Anderson, D.; Aulbert, C.; Bhat, N.D.R.; Bock, O.; Bogdanov, S.; Brazier, A.; Camilo, F.; Chatterjee, S.; Cordes, J.M.; Crawford, F.; Deneva, J.S.; Desvignes, G.; Fehrmann, H.; Freire, P.C.C.; Hammer, D.; Hessels, J.W.T.; Jenet, F.A.; Kaspi, V.M.; Kramer, M.; van Leeuwen, J.; Lorimer, D.R.; Lyne, A.G.; Machenschalk, B.; McLaughlin, M.A.; Messenger, C.; Nice, D.J.; Papa, M.A.; Pletsch, H.J.; Prix, R.; Ransom, S.M.; Siemens, X.; Stairs, I.H.; Stappers, B.W.; Stovall, K.; Venkataraman, A.

2011-01-01

We report the discovery of the 20.7 ms binary pulsar J1952+2630, made using the distributed computing project Einstein@Home in Pulsar ALFA survey observations with the Arecibo telescope. Follow-up observations with the Arecibo telescope confirm the binary nature of the system. We obtain a circular

Television viewing, computer use and total screen time in Canadian youth.

Science.gov (United States)

Mark, Amy E; Boyce, William F; Janssen, Ian

2006-11-01

Research has linked excessive television viewing and computer use in children and adolescents to a variety of health and social problems. Current recommendations are that screen time in children and adolescents should be limited to no more than 2 h per day. To determine the percentage of Canadian youth meeting the screen time guideline recommendations. The representative study sample consisted of 6942 Canadian youth in grades 6 to 10 who participated in the 2001/2002 World Health Organization Health Behaviour in School-Aged Children survey. Only 41% of girls and 34% of boys in grades 6 to 10 watched 2 h or less of television per day. Once the time of leisure computer use was included and total daily screen time was examined, only 18% of girls and 14% of boys met the guidelines. The prevalence of those meeting the screen time guidelines was higher in girls than boys. Fewer than 20% of Canadian youth in grades 6 to 10 met the total screen time guidelines, suggesting that increased public health interventions are needed to reduce the number of leisure time hours that Canadian youth spend watching television and using the computer.

Established and Emerging Trends in Computational Drug Discovery in the Structural Genomics Era

DEFF Research Database (Denmark)

Taboureau, Olivier; Baell, Jonathan B.; Fernández-Recio, Juan

2012-01-01

Bioinformatics and chemoinformatics approaches contribute to hit discovery, hit-to-lead optimization, safety profiling, and target identification and enhance our overall understanding of the health and disease states. A vast repertoire of computational methods has been reported and increasingly...

Advantages of crystallographic fragment screening: functional and mechanistic insights from a powerful platform for efficient drug discovery.

Science.gov (United States)

Patel, Disha; Bauman, Joseph D; Arnold, Eddy

2014-01-01

X-ray crystallography has been an under-appreciated screening tool for fragment-based drug discovery due to the perception of low throughput and technical difficulty. Investigators in industry and academia have overcome these challenges by taking advantage of key factors that contribute to a successful crystallographic screening campaign. Efficient cocktail design and soaking methodologies have evolved to maximize throughput while minimizing false positives/negatives. In addition, technical improvements at synchrotron beamlines have dramatically increased data collection rates thus enabling screening on a timescale comparable to other techniques. The combination of available resources and efficient experimental design has resulted in many successful crystallographic screening campaigns. The three-dimensional crystal structure of the bound fragment complexed to its target, a direct result of the screening effort, enables structure-based drug design while revealing insights regarding protein dynamics and function not readily obtained through other experimental approaches. Furthermore, this "chemical interrogation" of the target protein crystals can lead to the identification of useful reagents for improving diffraction resolution or compound solubility. Copyright © 2014. Published by Elsevier Ltd.

Advantages of Crystallographic Fragment Screening: Functional and Mechanistic Insights from a Powerful Platform for Efficient Drug Discovery

Science.gov (United States)

Patel, Disha; Bauman, Joseph D.; Arnold, Eddy

2015-01-01

X-ray crystallography has been an under-appreciated screening tool for fragment-based drug discovery due to the perception of low throughput and technical difficulty. Investigators in industry and academia have overcome these challenges by taking advantage of key factors that contribute to a successful crystallographic screening campaign. Efficient cocktail design and soaking methodologies have evolved to maximize throughput while minimizing false positives/negatives. In addition, technical improvements at synchrotron beamlines have dramatically increased data collection rates thus enabling screening on a timescale comparable to other techniques. The combination of available resources and efficient experimental design has resulted in many successful crystallographic screening campaigns. The three-dimensional crystal structure of the bound fragment complexed to its target, a direct result of the screening effort, enables structure-based drug design while revealing insights regarding protein dynamics and function not readily obtained through other experimental approaches. Furthermore, this “chemical interrogation” of the target protein crystals can lead to the identification of useful reagents for improving diffraction resolution or compound solubility. PMID:25117499

De Novo Discovery of Structured ncRNA Motifs in Genomic Sequences

DEFF Research Database (Denmark)

Ruzzo, Walter L; Gorodkin, Jan

2014-01-01

De novo discovery of "motifs" capturing the commonalities among related noncoding ncRNA structured RNAs is among the most difficult problems in computational biology. This chapter outlines the challenges presented by this problem, together with some approaches towards solving them, with an emphas...... on an approach based on the CMfinder CMfinder program as a case study. Applications to genomic screens for novel de novo structured ncRNA ncRNA s, including structured RNA elements in untranslated portions of protein-coding genes, are presented.......De novo discovery of "motifs" capturing the commonalities among related noncoding ncRNA structured RNAs is among the most difficult problems in computational biology. This chapter outlines the challenges presented by this problem, together with some approaches towards solving them, with an emphasis...

[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.

Visual ergonomic aspects of glare on computer displays: glossy screens and angular dependence

Science.gov (United States)

Brunnström, Kjell; Andrén, Börje; Konstantinides, Zacharias; Nordström, Lukas

2007-02-01

Recently flat panel computer displays and notebook computer are designed with a so called glare panel i.e. highly glossy screens, have emerged on the market. The shiny look of the display appeals to the costumers, also there are arguments that the contrast, colour saturation etc improves by using a glare panel. LCD displays suffer often from angular dependent picture quality. This has been even more pronounced by the introduction of Prism Light Guide plates into displays for notebook computers. The TCO label is the leading labelling system for computer displays. Currently about 50% of all computer displays on the market are certified according to the TCO requirements. The requirements are periodically updated to keep up with the technical development and the latest research in e.g. visual ergonomics. The gloss level of the screen and the angular dependence has recently been investigated by conducting user studies. A study of the effect of highly glossy screens compared to matt screens has been performed. The results show a slight advantage for the glossy screen when no disturbing reflexes are present, however the difference was not statistically significant. When disturbing reflexes are present the advantage is changed into a larger disadvantage and this difference is statistically significant. Another study of angular dependence has also been performed. The results indicates a linear relationship between the picture quality and the centre luminance of the screen.

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.

Individual Stochastic Screening for the Development of Computer Graphics

Directory of Open Access Journals (Sweden)

Maja Turčić¹*

2012-12-01

Full Text Available With the emergence of new tools and media, art and design have developed into digital computer-generated works. This article presents a sequence of creating art graphics because their original authors have not published the procedures. The goal is to discover the mathematics of an image and the programming libretto with the purpose of organizing a structural base of computer graphics. We will elaborate the procedures used to produce graphics known throughout the history of art, but that are nowadays also found in design and security graphics. The results are closely related graphics obtained by changing parameters that initiate them. The aim is to control the graphics, i.e. to use controlled stochastic to achieve desired solutions. Since the artists from the past have never published the procedures of screening methods, their ideas have remained “only” the works of art. In this article we will present the development of the algorithm that, more or less successfully, simulates those screening solutions. It has been proven that mathematically defined graphical elements serve as screening elements. New technological and mathematical solutions are introduced in the reproduction with individual screening elements to be used in printing.

Computing elastic anisotropy to discover gum-metal-like structural alloys

Science.gov (United States)

Winter, I. S.; de Jong, M.; Asta, M.; Chrzan, D. C.

2017-08-01

The computer aided discovery of structural alloys is a burgeoning but still challenging area of research. A primary challenge in the field is to identify computable screening parameters that embody key structural alloy properties. Here, an elastic anisotropy parameter that captures a material's susceptibility to solute solution strengthening is identified. The parameter has many applications in the discovery and optimization of structural materials. As a first example, the parameter is used to identify alloys that might display the super elasticity, super strength, and high ductility of the class of TiNb alloys known as gum metals. In addition, it is noted that the parameter can be used to screen candidate alloys for shape memory response, and potentially aid in the optimization of the mechanical properties of high-entropy alloys.

Discovery of Selective Nanobodies against α-elapitoxin Dpp2c from Black Mamba through Phage Display Screening

DEFF Research Database (Denmark)

Milbo, Christina; Laustsen, Andreas Hougaard; Lohse, Brian

Feared for its highly neurotoxic venom and rapid attack technique, the Black mamba (Dendroaspis polylepis) is Africa’s largest venomous snake. The clinical manifestations of a bitefrom D. polylepis include flaccid paralysis leading to respiratory failure and death due to postsynaptic blockade of ......-neurotoxins. Here, we report the discovery of selective nanobodies targeting α-elapitoxin Dpp2c from D. polylepis through phage display screening....

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.

An Algorithm for Computing Screened Coulomb Scattering in Geant4

OpenAIRE

Mendenhall, Marcus H.; Weller, Robert A.

2004-01-01

An algorithm has been developed for the Geant4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in precise tracking of both the projectile and the recoil target nucleus. The algorithm permits the user to plug in an arbitrary screening function, such as Lens-Jensen screening, which is good for backscattering calculations, or Ziegler-Biersack-Littmark screenin...

SCREENING CHEMICALS FOR ESTROGEN RECEPTOR BIOACTIVITY USING A COMPUTATIONAL MODEL

Science.gov (United States)

The U.S. Environmental Protection Agency (EPA) is considering the use high-throughput and computational methods for regulatory applications in the Endocrine Disruptor Screening Program (EDSP). To use these new tools for regulatory decision making, computational methods must be a...

A computational design approach for virtual screening of peptide interactions across K+ channel families

Directory of Open Access Journals (Sweden)

Craig A. Doupnik

2015-01-01

Full Text Available Ion channels represent a large family of membrane proteins with many being well established targets in pharmacotherapy. The ‘druggability’ of heteromeric channels comprised of different subunits remains obscure, due largely to a lack of channel-specific probes necessary to delineate their therapeutic potential in vivo. Our initial studies reported here, investigated the family of inwardly rectifying potassium (Kir channels given the availability of high resolution crystal structures for the eukaryotic constitutively active Kir2.2 channel. We describe a ‘limited’ homology modeling approach that can yield chimeric Kir channels having an outer vestibule structure representing nearly any known vertebrate or invertebrate channel. These computationally-derived channel structures were tested in silico for ‘docking’ to NMR structures of tertiapin (TPN, a 21 amino acid peptide found in bee venom. TPN is a highly selective and potent blocker for the epithelial rat Kir1.1 channel, but does not block human or zebrafish Kir1.1 channel isoforms. Our Kir1.1 channel-TPN docking experiments recapitulated published in vitro findings for TPN-sensitive and TPN-insensitive channels. Additionally, in silico site-directed mutagenesis identified ‘hot spots’ within the channel outer vestibule that mediate energetically favorable docking scores and correlate with sites previously identified with in vitro thermodynamic mutant-cycle analysis. These ‘proof-of-principle’ results establish a framework for virtual screening of re-engineered peptide toxins for interactions with computationally derived Kir channels that currently lack channel-specific blockers. When coupled with electrophysiological validation, this virtual screening approach may accelerate the drug discovery process, and can be readily applied to other ion channels families where high resolution structures are available.

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

Volatility Discovery

DEFF Research Database (Denmark)

Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

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.

Viral pathogen discovery

Science.gov (United States)

Chiu, Charles Y

2015-01-01

Viral pathogen discovery is of critical importance to clinical microbiology, infectious diseases, and public health. Genomic approaches for pathogen discovery, including consensus polymerase chain reaction (PCR), microarrays, and unbiased next-generation sequencing (NGS), have the capacity to comprehensively identify novel microbes present in clinical samples. Although numerous challenges remain to be addressed, including the bioinformatics analysis and interpretation of large datasets, these technologies have been successful in rapidly identifying emerging outbreak threats, screening vaccines and other biological products for microbial contamination, and discovering novel viruses associated with both acute and chronic illnesses. Downstream studies such as genome assembly, epidemiologic screening, and a culture system or animal model of infection are necessary to establish an association of a candidate pathogen with disease. PMID:23725672

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.

Studying Scientific Discovery by Computer Simulation.

Science.gov (United States)

1983-03-30

Mendel’s laws of inheritance, the law of Gay- Lussac for gaseous reactions, tile law of Dulong and Petit, the derivation of atomic weights by Avogadro...neceseary mid identify by block number) scientific discovery -ittri sic properties physical laws extensive terms data-driven heuristics intensive...terms theory-driven heuristics conservation laws 20. ABSTRACT (Continue on revere. side It necessary and identify by block number) Scientific discovery

Accelerated oral nanomedicine discovery from miniaturized screening to clinical production exemplified by paediatric HIV nanotherapies

Science.gov (United States)

Giardiello, Marco; Liptrott, Neill J.; McDonald, Tom O.; Moss, Darren; Siccardi, Marco; Martin, Phil; Smith, Darren; Gurjar, Rohan; Rannard, Steve P.; Owen, Andrew

2016-10-01

Considerable scope exists to vary the physical and chemical properties of nanoparticles, with subsequent impact on biological interactions; however, no accelerated process to access large nanoparticle material space is currently available, hampering the development of new nanomedicines. In particular, no clinically available nanotherapies exist for HIV populations and conventional paediatric HIV medicines are poorly available; one current paediatric formulation utilizes high ethanol concentrations to solubilize lopinavir, a poorly soluble antiretroviral. Here we apply accelerated nanomedicine discovery to generate a potential aqueous paediatric HIV nanotherapy, with clinical translation and regulatory approval for human evaluation. Our rapid small-scale screening approach yields large libraries of solid drug nanoparticles (160 individual components) targeting oral dose. Screening uses 1 mg of drug compound per library member and iterative pharmacological and chemical evaluation establishes potential candidates for progression through to clinical manufacture. The wide applicability of our strategy has implications for multiple therapy development programmes.

Discovery of novel bacterial toxins by genomics and computational biology.

Science.gov (United States)

Doxey, Andrew C; Mansfield, Michael J; Montecucco, Cesare

2018-06-01

Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology. One consequence is that genes encoding novel bacterial toxins can be identified by bioinformatic and computational methods based on previous knowledge accumulated from studies of the biology and pathology of thousands of known bacterial protein toxins. Starting from the paradigmatic cases of diphtheria toxin, tetanus and botulinum neurotoxins, this review discusses traditional experimental approaches as well as bioinformatics and genomics-driven approaches that facilitate the discovery of novel bacterial toxins. We discuss recent work on the identification of novel botulinum-like toxins from genera such as Weissella, Chryseobacterium, and Enteroccocus, and the implications of these computationally identified toxins in the field. Finally, we discuss the promise of metagenomics in the discovery of novel toxins and their ecological niches, and present data suggesting the existence of uncharacterized, botulinum-like toxin genes in insect gut metagenomes. Copyright © 2018. Published by Elsevier Ltd.

Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.

Science.gov (United States)

Matiasz, Nicholas J; Wood, Justin; Wang, Wei; Silva, Alcino J; Hsu, William

2017-01-01

Computers help neuroscientists to analyze experimental results by automating the application of statistics; however, computer-aided experiment planning is far less common, due to a lack of similar quantitative formalisms for systematically assessing evidence and uncertainty. While ontologies and other Semantic Web resources help neuroscientists to assimilate required domain knowledge, experiment planning requires not only ontological but also epistemological (e.g., methodological) information regarding how knowledge was obtained. Here, we outline how epistemological principles and graphical representations of causality can be used to formalize experiment planning toward causal discovery. We outline two complementary approaches to experiment planning: one that quantifies evidence per the principles of convergence and consistency, and another that quantifies uncertainty using logical representations of constraints on causal structure. These approaches operationalize experiment planning as the search for an experiment that either maximizes evidence or minimizes uncertainty. Despite work in laboratory automation, humans must still plan experiments and will likely continue to do so for some time. There is thus a great need for experiment-planning frameworks that are not only amenable to machine computation but also useful as aids in human reasoning.

The history of cosmic baryons: discoveries using advanced computing

International Nuclear Information System (INIS)

Norman, Michael L

2005-01-01

We live in the era of the cosmological concordance model. This refers to the precise set of cosmological parameters which describe the average composition, geometry, and expansion rate of the universe we inhabit. Due to recent observational, theoretical, and computational advances, these parameters are now known to approximately 10% accuracy, and new efforts are underway to increase precision tenfold. It is found that we live in a spatially flat, dark matter-dominated universe whose rate of expansion is accelerating due to an unseen, unknown dark energy field. Baryons-the stuff of stars, galaxies, and us-account for only 4% of the total mass-energy inventory. And yet, it is through the astronomical study of baryons that we infer the rest. In this talk I will highlight the important role advanced scientific computing has played in getting us to the concordance model, and also the computational discoveries that have been made about the history of cosmic baryons using hydrodynamical cosmological simulations. I will conclude by discussing the central role that very large scale simulations of cosmological structure formation will play in deciphering the results of upcoming dark energy surveys

Functional Metagenomics: Construction and High-Throughput Screening of Fosmid Libraries for Discovery of Novel Carbohydrate-Active Enzymes.

Science.gov (United States)

Ufarté, Lisa; Bozonnet, Sophie; Laville, Elisabeth; Cecchini, Davide A; Pizzut-Serin, Sandra; Jacquiod, Samuel; Demanèche, Sandrine; Simonet, Pascal; Franqueville, Laure; Veronese, Gabrielle Potocki

2016-01-01

Activity-based metagenomics is one of the most efficient approaches to boost the discovery of novel biocatalysts from the huge reservoir of uncultivated bacteria. In this chapter, we describe a highly generic procedure of metagenomic library construction and high-throughput screening for carbohydrate-active enzymes. Applicable to any bacterial ecosystem, it enables the swift identification of functional enzymes that are highly efficient, alone or acting in synergy, to break down polysaccharides and oligosaccharides.

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.

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.

Discovery of resources using MADM approaches for parallel and distributed computing

Directory of Open Access Journals (Sweden)

Mandeep Kaur

2017-06-01

Full Text Available Grid, a form of parallel and distributed computing, allows the sharing of data and computational resources among its users from various geographical locations. The grid resources are diverse in terms of their underlying attributes. The majority of the state-of-the-art resource discovery techniques rely on the static resource attributes during resource selection. However, the matching resources based on the static resource attributes may not be the most appropriate resources for the execution of user applications because they may have heavy job loads, less storage space or less working memory (RAM. Hence, there is a need to consider the current state of the resources in order to find the most suitable resources. In this paper, we have proposed a two-phased multi-attribute decision making (MADM approach for discovery of grid resources by using P2P formalism. The proposed approach considers multiple resource attributes for decision making of resource selection and provides the best suitable resource(s to grid users. The first phase describes a mechanism to discover all matching resources and applies SAW method to shortlist the top ranked resources, which are communicated to the requesting super-peer. The second phase of our proposed methodology applies integrated MADM approach (AHP enriched PROMETHEE-II on the list of selected resources received from different super-peers. The pairwise comparison of the resources with respect to their attributes is made and the rank of each resource is determined. The top ranked resource is then communicated to the grid user by the grid scheduler. Our proposed methodology enables the grid scheduler to allocate the most suitable resource to the user application and also reduces the search complexity by filtering out the less suitable resources during resource discovery.

Advances in genome-wide RNAi cellular screens: a case study using the Drosophila JAK/STAT pathway

Science.gov (United States)

2012-01-01

Background Genome-scale RNA-interference (RNAi) screens are becoming ever more common gene discovery tools. However, whilst every screen identifies interacting genes, less attention has been given to how factors such as library design and post-screening bioinformatics may be effecting the data generated. Results Here we present a new genome-wide RNAi screen of the Drosophila JAK/STAT signalling pathway undertaken in the Sheffield RNAi Screening Facility (SRSF). This screen was carried out using a second-generation, computationally optimised dsRNA library and analysed using current methods and bioinformatic tools. To examine advances in RNAi screening technology, we compare this screen to a biologically very similar screen undertaken in 2005 with a first-generation library. Both screens used the same cell line, reporters and experimental design, with the SRSF screen identifying 42 putative regulators of JAK/STAT signalling, 22 of which verified in a secondary screen and 16 verified with an independent probe design. Following reanalysis of the original screen data, comparisons of the two gene lists allows us to make estimates of false discovery rates in the SRSF data and to conduct an assessment of off-target effects (OTEs) associated with both libraries. We discuss the differences and similarities between the resulting data sets and examine the relative improvements in gene discovery protocols. Conclusions Our work represents one of the first direct comparisons between first- and second-generation libraries and shows that modern library designs together with methodological advances have had a significant influence on genome-scale RNAi screens. PMID:23006893

Fragment-based screening in tandem with phenotypic screening provides novel antiparasitic hits.

Science.gov (United States)

Blaazer, Antoni R; Orrling, Kristina M; Shanmugham, Anitha; Jansen, Chimed; Maes, Louis; Edink, Ewald; Sterk, Geert Jan; Siderius, Marco; England, Paul; Bailey, David; de Esch, Iwan J P; Leurs, Rob

2015-01-01

Methods to discover biologically active small molecules include target-based and phenotypic screening approaches. One of the main difficulties in drug discovery is elucidating and exploiting the relationship between drug activity at the protein target and disease modification, a phenotypic endpoint. Fragment-based drug discovery is a target-based approach that typically involves the screening of a relatively small number of fragment-like (molecular weight <300) molecules that efficiently cover chemical space. Here, we report a fragment screening on TbrPDEB1, an essential cyclic nucleotide phosphodiesterase (PDE) from Trypanosoma brucei, and human PDE4D, an off-target, in a workflow in which fragment hits and a series of close analogs are subsequently screened for antiparasitic activity in a phenotypic panel. The phenotypic panel contained T. brucei, Trypanosoma cruzi, Leishmania infantum, and Plasmodium falciparum, the causative agents of human African trypanosomiasis (sleeping sickness), Chagas disease, leishmaniasis, and malaria, respectively, as well as MRC-5 human lung cells. This hybrid screening workflow has resulted in the discovery of various benzhydryl ethers with antiprotozoal activity and low toxicity, representing interesting starting points for further antiparasitic optimization. © 2014 Society for Laboratory Automation and Screening.

Computer aided drug design

Science.gov (United States)

Jain, A.

2017-08-01

Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems.

Science.gov (United States)

Ma, Xingpo; Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-02-10

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

Science.gov (United States)

Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-01-01

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems. PMID:29439442

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

Directory of Open Access Journals (Sweden)

Xingpo Ma

2018-02-01

Full Text Available In the post-Cloud era, the proliferation of Internet of Things (IoT has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

Scientific Discovery through Advanced Computing in Plasma Science

Science.gov (United States)

Tang, William

2005-03-01

Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations

Computer-aided drug design at Boehringer Ingelheim

Science.gov (United States)

Muegge, Ingo; Bergner, Andreas; Kriegl, Jan M.

2017-03-01

Computer-Aided Drug Design (CADD) is an integral part of the drug discovery endeavor at Boehringer Ingelheim (BI). CADD contributes to the evaluation of new therapeutic concepts, identifies small molecule starting points for drug discovery, and develops strategies for optimizing hit and lead compounds. The CADD scientists at BI benefit from the global use and development of both software platforms and computational services. A number of computational techniques developed in-house have significantly changed the way early drug discovery is carried out at BI. In particular, virtual screening in vast chemical spaces, which can be accessed by combinatorial chemistry, has added a new option for the identification of hits in many projects. Recently, a new framework has been implemented allowing fast, interactive predictions of relevant on and off target endpoints and other optimization parameters. In addition to the introduction of this new framework at BI, CADD has been focusing on the enablement of medicinal chemists to independently perform an increasing amount of molecular modeling and design work. This is made possible through the deployment of MOE as a global modeling platform, allowing computational and medicinal chemists to freely share ideas and modeling results. Furthermore, a central communication layer called the computational chemistry framework provides broad access to predictive models and other computational services.

In person versus computer screening for intimate partner violence among pregnant patients.

Science.gov (United States)

Chang, Judy C; Dado, Diane; Schussler, Sara; Hawker, Lynn; Holland, Cynthia L; Burke, Jessica G; Cluss, Patricia A

2012-09-01

To compare in person versus computerized screening for intimate partner violence (IPV) in a hospital-based prenatal clinic and explore women's assessment of the screening methods. We compared patient IPV disclosures on a computerized questionnaire to audio-taped first obstetric visits with an obstetric care provider and performed semi-structured interviews with patient participants who reported experiencing IPV. Two-hundred and fifty patient participants and 52 provider participants were in the study. Ninety-one (36%) patients disclosed IPV either via computer or in person. Of those who disclosed IPV, 60 (66%) disclosed via both methods, but 31 (34%) disclosed IPV via only one of the two methods. Twenty-three women returned for interviews. They recommended using both types together. While computerized screening was felt to be non-judgmental and more anonymous, in person screening allowed for tailored questioning and more emotional connection with the provider. Computerized screening allowed disclosure without fear of immediate judgment. In person screening allows more flexibility in wording of questions regarding IPV and opportunity for interpersonal rapport. Both computerized or self-completed screening and in person screening is recommended. Providers should address IPV using non-judgmental, descriptive language, include assessments for psychological IPV, and repeat screening in person, even if no patient disclosure occurs via computer. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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.

Sign use and cognition in automated scientific discovery: are computers only special kinds of signs?

Science.gov (United States)

Giza, Piotr

2018-04-01

James Fetzer criticizes the computational paradigm, prevailing in cognitive science by questioning, what he takes to be, its most elementary ingredient: that cognition is computation across representations. He argues that if cognition is taken to be a purposive, meaningful, algorithmic problem solving activity, then computers are incapable of cognition. Instead, they appear to be signs of a special kind, that can facilitate computation. He proposes the conception of minds as semiotic systems as an alternative paradigm for understanding mental phenomena, one that seems to overcome the difficulties of computationalism. Now, I argue, that with computer systems dealing with scientific discovery, the matter is not so simple as that. The alleged superiority of humans using signs to stand for something other over computers being merely "physical symbol systems" or "automatic formal systems" is only easy to establish in everyday life, but becomes far from obvious when scientific discovery is at stake. In science, as opposed to everyday life, the meaning of symbols is, apart from very low-level experimental investigations, defined implicitly by the way the symbols are used in explanatory theories or experimental laws relevant to the field, and in consequence, human and machine discoverers are much more on a par. Moreover, the great practical success of the genetic programming method and recent attempts to apply it to automatic generation of cognitive theories seem to show, that computer systems are capable of very efficient problem solving activity in science, which is neither purposive nor meaningful, nor algorithmic. This, I think, undermines Fetzer's argument that computer systems are incapable of cognition because computation across representations is bound to be a purposive, meaningful, algorithmic problem solving activity.

An algorithm for computing screened Coulomb scattering in GEANT4

Energy Technology Data Exchange (ETDEWEB)

Mendenhall, Marcus H. [Vanderbilt University Free Electron Laser Center, P.O. Box 351816 Station B, Nashville, TN 37235-1816 (United States)]. E-mail: marcus.h.mendenhall@vanderbilt.edu; Weller, Robert A. [Department of Electrical Engineering and Computer Science, Vanderbilt University, P.O. Box 351821 Station B, Nashville, TN 37235-1821 (United States)]. E-mail: robert.a.weller@vanderbilt.edu

2005-01-01

An algorithm has been developed for the GEANT4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in precise tracking of both the projectile and the recoil target nucleus. The algorithm permits the user to plug in an arbitrary screening function, such as Lens-Jensen screening, which is good for backscattering calculations, or Ziegler-Biersack-Littmark screening, which is good for nuclear straggling and implantation problems. This will allow many of the applications of the TRIM and SRIM codes to be extended into the much more general GEANT4 framework where nuclear and other effects can be included.

An algorithm for computing screened Coulomb scattering in GEANT4

International Nuclear Information System (INIS)

Mendenhall, Marcus H.; Weller, Robert A.

2005-01-01

An algorithm has been developed for the GEANT4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in precise tracking of both the projectile and the recoil target nucleus. The algorithm permits the user to plug in an arbitrary screening function, such as Lens-Jensen screening, which is good for backscattering calculations, or Ziegler-Biersack-Littmark screening, which is good for nuclear straggling and implantation problems. This will allow many of the applications of the TRIM and SRIM codes to be extended into the much more general GEANT4 framework where nuclear and other effects can be included

Arrayed antibody library technology for therapeutic biologic discovery.

Science.gov (United States)

Bentley, Cornelia A; Bazirgan, Omar A; Graziano, James J; Holmes, Evan M; Smider, Vaughn V

2013-03-15

Traditional immunization and display antibody discovery methods rely on competitive selection amongst a pool of antibodies to identify a lead. While this approach has led to many successful therapeutic antibodies, targets have been limited to proteins which are easily purified. In addition, selection driven discovery has produced a narrow range of antibody functionalities focused on high affinity antagonism. We review the current progress in developing arrayed protein libraries for screening-based, rather than selection-based, discovery. These single molecule per microtiter well libraries have been screened in multiplex formats against both purified antigens and directly against targets expressed on the cell surface. This facilitates the discovery of antibodies against therapeutically interesting targets (GPCRs, ion channels, and other multispanning membrane proteins) and epitopes that have been considered poorly accessible to conventional discovery methods. Copyright © 2013. Published by Elsevier Inc.

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.

Discovery of Selective Inhibitors of Imidazoleglycerol-Phosphate Dehydratase from Mycobacterium tuberculosis by Virtual Screening

Science.gov (United States)

Podshivalov, D.; Mandzhieva, Yu. B.; Sidorov-Biryukov, D. D.; Timofeev, V. I.; Kuranova, I. P.

2018-01-01

Bacterial imidazoleglycerol-phosphate dehydratase from Mycobacterium tuberculosis (HisB- Mt) is a convenient target for the discovery of selective inhibitors as potential antituberculosis drugs. The virtual screening was performed to find compounds suitable for the design of selective inhibitors of HisB- Mt. The positions of four ligands, which were selected based on the docking scoring function and docked to the activesite region of the enzyme, were refined by molecular dynamics simulation. The nearest environment of the ligands was determined. These compounds selectively bind to functionally essential active-site residues, thus blocking access of substrates to the active site of the enzyme, and can be used as lead compounds for the design of selective inhibitors of HisB- M.

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.

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.

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

Directory of Open Access Journals (Sweden)

Sun Youxian

2008-06-01

Full Text Available Abstract Background The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of

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.

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

Screening applications in drug discovery based on microfluidic technology

Science.gov (United States)

Eribol, P.; Uguz, A. K.; Ulgen, K. O.

2016-01-01

Microfluidics has been the focus of interest for the last two decades for all the advantages such as low chemical consumption, reduced analysis time, high throughput, better control of mass and heat transfer, downsizing a bench-top laboratory to a chip, i.e., lab-on-a-chip, and many others it has offered. Microfluidic technology quickly found applications in the pharmaceutical industry, which demands working with leading edge scientific and technological breakthroughs, as drug screening and commercialization are very long and expensive processes and require many tests due to unpredictable results. This review paper is on drug candidate screening methods with microfluidic technology and focuses specifically on fabrication techniques and materials for the microchip, types of flow such as continuous or discrete and their advantages, determination of kinetic parameters and their comparison with conventional systems, assessment of toxicities and cytotoxicities, concentration generations for high throughput, and the computational methods that were employed. An important conclusion of this review is that even though microfluidic technology has been in this field for around 20 years there is still room for research and development, as this cutting edge technology requires ingenuity to design and find solutions for each individual case. Recent extensions of these microsystems are microengineered organs-on-chips and organ arrays. PMID:26865904

Screening applications in drug discovery based on microfluidic technology.

Science.gov (United States)

Eribol, P; Uguz, A K; Ulgen, K O

2016-01-01

Microfluidics has been the focus of interest for the last two decades for all the advantages such as low chemical consumption, reduced analysis time, high throughput, better control of mass and heat transfer, downsizing a bench-top laboratory to a chip, i.e., lab-on-a-chip, and many others it has offered. Microfluidic technology quickly found applications in the pharmaceutical industry, which demands working with leading edge scientific and technological breakthroughs, as drug screening and commercialization are very long and expensive processes and require many tests due to unpredictable results. This review paper is on drug candidate screening methods with microfluidic technology and focuses specifically on fabrication techniques and materials for the microchip, types of flow such as continuous or discrete and their advantages, determination of kinetic parameters and their comparison with conventional systems, assessment of toxicities and cytotoxicities, concentration generations for high throughput, and the computational methods that were employed. An important conclusion of this review is that even though microfluidic technology has been in this field for around 20 years there is still room for research and development, as this cutting edge technology requires ingenuity to design and find solutions for each individual case. Recent extensions of these microsystems are microengineered organs-on-chips and organ arrays.

Discovery of new inhibitors of the bacterial peptidoglycan biosynthesis enzymes MurD and MurF by structure-based virtual screening.

Science.gov (United States)

Turk, Samo; Kovac, Andreja; Boniface, Audrey; Bostock, Julieanne M; Chopra, Ian; Blanot, Didier; Gobec, Stanislav

2009-03-01

The ATP-dependent Mur ligases (MurC, MurD, MurE and MurF) successively add L-Ala, D-Glu, meso-A(2)pm or L-Lys, and D-Ala-D-Ala to the nucleotide precursor UDP-MurNAc, and they represent promising targets for antibacterial drug discovery. We have used the molecular docking programme eHiTS for the virtual screening of 1990 compounds from the National Cancer Institute 'Diversity Set' on MurD and MurF. The 50 top-scoring compounds from screening on each enzyme were selected for experimental biochemical evaluation. Our approach of virtual screening and subsequent in vitro biochemical evaluation of the best ranked compounds has provided four novel MurD inhibitors (best IC(50)=10 microM) and one novel MurF inhibitor (IC(50)=63 microM).

Developing the Biomolecular Screening Facility at the EPFL into the Chemical Biology Screening Platform for Switzerland.

Science.gov (United States)

Turcatti, Gerardo

2014-05-01

The Biomolecular Screening Facility (BSF) is a multidisciplinary laboratory created in 2006 at the Ecole Polytechnique Federale de Lausanne (EPFL) to perform medium and high throughput screening in life sciences-related projects. The BSF was conceived and developed to meet the needs of a wide range of researchers, without privileging a particular biological discipline or therapeutic area. The facility has the necessary infrastructure, multidisciplinary expertise and flexibility to perform large screening programs using small interfering RNAs (siRNAs) and chemical collections in the areas of chemical biology, systems biology and drug discovery. In the framework of the National Centres of Competence in Research (NCCR) Chemical Biology, the BSF is hosting 'ACCESS', the Academic Chemical Screening Platform of Switzerland that provides the scientific community with chemical diversity, screening facilities and know-how in chemical genetics. In addition, the BSF started its own applied research axes that are driven by innovation in thematic areas related to preclinical drug discovery and discovery of bioactive probes.

Biophysical Screening of a Focused Library for the Discovery of CYP121 Inhibitors as Novel Antimycobacterials.

Science.gov (United States)

Brengel, Christian; Thomann, Andreas; Schifrin, Alexander; Allegretta, Giuseppe; Kamal, Ahmed A M; Haupenthal, Jörg; Schnorr, Isabell; Cho, Sang Hyun; Franzblau, Scott G; Empting, Martin; Eberhard, Jens; Hartmann, Rolf W

2017-10-09

The development of novel antimycobacterial agents against Mycobacterium tuberculosis (Mtb) is urgently required due to the appearance of multidrug resistance (MDR) combined with complicated long-term treatment. CYP121 was shown to be a promising novel target for inhibition of mycobacterial growth. In this study, we describe the rational discovery of new CYP121 inhibitors by a systematic screening based on biophysical and microbiological methods. The best hits originating from only one structural class gave initial information about molecular motifs required for binding and activity. The initial screening procedure was followed by mode-of-action studies and further biological characterizations. The results demonstrate superior antimycobacterial efficacy and a decreased toxicity profile of our frontrunner compound relative to the reference compound econazole. Due to its low molecular weight, promising biological profile, and physicochemical properties, this compound is an excellent starting point for further rational optimization. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Feasibility of Tablet Computer Screening for Opioid Abuse in the Emergency Department

Directory of Open Access Journals (Sweden)

Weiner, Scott G.

2014-12-01

Full Text Available Introduction: Tablet computer-based screening may have the potential for detecting patients at risk for opioid abuse in the emergency department (ED. Study objectives were a to determine if the revised Screener and Opioid Assessment for Patients with Pain (SOAPP®-R, a 24-question previously paper-based screening tool for opioid abuse potential, could be administered on a tablet computer to an ED patient population; b to demonstrate that >90% of patients can complete the electronic screener without assistance in 35 years. One hundred percent of subjects completed the screener. Median time to completion was 148 (interquartile range 117.5-184.3 seconds, and 95% (n=78 completed in <5 minutes. 93% (n=76 rated ease of completion as very easy. Conclusions: It is feasible to administer a screening tool to a cohort of ED patients on a tablet computer. The screener administration time is minimal and patient ease of use with this modality is high. [West J Emerg Med. 2015;16(1:18-23

Computational Design and Discovery of Ni-Based Alloys and Coatings: Thermodynamic Approaches Validated by Experiments

Energy Technology Data Exchange (ETDEWEB)

Liu, Zi-Kui [Pennsylvania State University; Gleeson, Brian [University of Pittsburgh; Shang, Shunli [Pennsylvania State University; Gheno, Thomas [University of Pittsburgh; Lindwall, Greta [Pennsylvania State University; Zhou, Bi-Cheng [Pennsylvania State University; Liu, Xuan [Pennsylvania State University; Ross, Austin [Pennsylvania State University

2018-04-23

This project developed computational tools that can complement and support experimental efforts in order to enable discovery and more efficient development of Ni-base structural materials and coatings. The project goal was reached through an integrated computation-predictive and experimental-validation approach, including first-principles calculations, thermodynamic CALPHAD (CALculation of PHAse Diagram), and experimental investigations on compositions relevant to Ni-base superalloys and coatings in terms of oxide layer growth and microstructure stabilities. The developed description included composition ranges typical for coating alloys and, hence, allow for prediction of thermodynamic properties for these material systems. The calculation of phase compositions, phase fraction, and phase stabilities, which are directly related to properties such as ductility and strength, was a valuable contribution, along with the collection of computational tools that are required to meet the increasing demands for strong, ductile and environmentally-protective coatings. Specifically, a suitable thermodynamic description for the Ni-Al-Cr-Co-Si-Hf-Y system was developed for bulk alloy and coating compositions. Experiments were performed to validate and refine the thermodynamics from the CALPHAD modeling approach. Additionally, alloys produced using predictions from the current computational models were studied in terms of their oxidation performance. Finally, results obtained from experiments aided in the development of a thermodynamic modeling automation tool called ESPEI/pycalphad - for more rapid discovery and development of new materials.

Decision trees and integrated features for computer aided mammographic screening

Energy Technology Data Exchange (ETDEWEB)

Kegelmeyer, W.P. Jr.; Groshong, B.; Allmen, M.; Woods, K.

1997-02-01

Breast cancer is a serious problem, which in the United States causes 43,000 deaths a year, eventually striking 1 in 9 women. Early detection is the only effective countermeasure, and mass mammography screening is the only reliable means for early detection. Mass screening has many shortcomings which could be addressed by a computer-aided mammographic screening system. Accordingly, we have applied the pattern recognition methods developed in earlier investigations of speculated lesions in mammograms to the detection of microcalcifications and circumscribed masses, generating new, more rigorous and uniform methods for the detection of both those signs. We have also improved the pattern recognition methods themselves, through the development of a new approach to combinations of multiple classifiers.

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 ...

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.

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.

The insulin secretory action of novel polycyclic guanidines: discovery through open innovation phenotypic screening, and exploration of structure-activity relationships.

Science.gov (United States)

Shaghafi, Michael B; Barrett, David G; Willard, Francis S; Overman, Larry E

2014-02-15

We report the discovery of the glucose-dependent insulin secretogogue activity of a novel class of polycyclic guanidines through phenotypic screening as part of the Lilly Open Innovation Drug Discovery platform. Three compounds from the University of California, Irvine, 1-3, having the 3-arylhexahydropyrrolo[1,2-c]pyrimidin-1-amine scaffold acted as insulin secretagogues under high, but not low, glucose conditions. Exploration of the structure-activity relationship around the scaffold demonstrated the key role of the guanidine moiety, as well as the importance of two lipophilic regions, and led to the identification of 9h, which stimulated insulin secretion in isolated rat pancreatic islets in a glucose-dependent manner. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Radiation levels from computer monitor screens within Benue State ...

African Journals Online (AJOL)

Investigation of possible presence of soft X-ray levels from Computer Screens at distances of 0.5m and 1.0m was carried out within Benue State University, Makurdi, using ten different monitor models. Radiation measurement was carried out using a portable digital radiation meter, INSPECTOR 06250 (SE international Inc.

Discovery of potent inhibitors of soluble epoxide hydrolase by combinatorial library design and structure-based virtual screening.

Science.gov (United States)

Xing, Li; McDonald, Joseph J; Kolodziej, Steve A; Kurumbail, Ravi G; Williams, Jennifer M; Warren, Chad J; O'Neal, Janet M; Skepner, Jill E; Roberds, Steven L

2011-03-10

Structure-based virtual screening was applied to design combinatorial libraries to discover novel and potent soluble epoxide hydrolase (sEH) inhibitors. X-ray crystal structures revealed unique interactions for a benzoxazole template in addition to the conserved hydrogen bonds with the catalytic machinery of sEH. By exploitation of the favorable binding elements, two iterations of library design based on amide coupling were employed, guided principally by the docking results of the enumerated virtual products. Biological screening of the libraries demonstrated as high as 90% hit rate, of which over two dozen compounds were single digit nanomolar sEH inhibitors by IC(50) determination. In total the library design and synthesis produced more than 300 submicromolar sEH inhibitors. In cellular systems consistent activities were demonstrated with biochemical measurements. The SAR understanding of the benzoxazole template provides valuable insights into discovery of novel sEH inhibitors as therapeutic agents.

Congestion game scheduling for virtual drug screening optimization

Science.gov (United States)

Nikitina, Natalia; Ivashko, Evgeny; Tchernykh, Andrei

2018-02-01

In virtual drug screening, the chemical diversity of hits is an important factor, along with their predicted activity. Moreover, interim results are of interest for directing the further research, and their diversity is also desirable. In this paper, we consider a problem of obtaining a diverse set of virtual screening hits in a short time. To this end, we propose a mathematical model of task scheduling for virtual drug screening in high-performance computational systems as a congestion game between computational nodes to find the equilibrium solutions for best balancing the number of interim hits with their chemical diversity. The model considers the heterogeneous environment with workload uncertainty, processing time uncertainty, and limited knowledge about the input dataset structure. We perform computational experiments and evaluate the performance of the developed approach considering organic molecules database GDB-9. The used set of molecules is rich enough to demonstrate the feasibility and practicability of proposed solutions. We compare the algorithm with two known heuristics used in practice and observe that game-based scheduling outperforms them by the hit discovery rate and chemical diversity at earlier steps. Based on these results, we use a social utility metric for assessing the efficiency of our equilibrium solutions and show that they reach greatest values.

High-throughput quantum chemistry and virtual screening for OLED material components

Science.gov (United States)

Halls, Mathew D.; Giesen, David J.; Hughes, Thomas F.; Goldberg, Alexander; Cao, Yixiang

2013-09-01

Computational structure enumeration, analysis using an automated simulation workflow and filtering of large chemical structure libraries to identify lead systems, has become a central paradigm in drug discovery research. Transferring this paradigm to challenges in materials science is now possible due to advances in the speed of computational resources and the efficiency and stability of chemical simulation packages. State-of-the-art software tools that have been developed for drug discovery can be applied to efficiently explore the chemical design space to identify solutions for problems such as organic light-emitting diode material components. In this work, virtual screening for OLED materials based on intrinsic quantum mechanical properties is illustrated. Also, a new approach to more reliably identify candidate systems is introduced that is based on the chemical reaction energetics of defect pathways for OLED materials.

Computational Screening of Light-absorbing Materials for Photoelectrochemical Water Splitting

DEFF Research Database (Denmark)

Castelli, Ivano E.; Kuhar, Korina; Pandey, Mohnish

2018-01-01

Efficient conversion of solar energy into electricity or fuels requires the identification of new semiconductors with optimal optical and electronic properties. We discuss the current and future role that computational screening is expected to play in this challenge. We discuss the identification...

Computer screen photo-excited surface plasmon resonance imaging.

Science.gov (United States)

Filippini, Daniel; Winquist, Fredrik; Lundström, Ingemar

2008-09-12

Angle and spectra resolved surface plasmon resonance (SPR) images of gold and silver thin films with protein deposits is demonstrated using a regular computer screen as light source and a web camera as detector. The screen provides multiple-angle illumination, p-polarized light and controlled spectral radiances to excite surface plasmons in a Kretchmann configuration. A model of the SPR reflectances incorporating the particularities of the source and detector explain the observed signals and the generation of distinctive SPR landscapes is demonstrated. The sensitivity and resolution of the method, determined in air and solution, are 0.145 nm pixel(-1), 0.523 nm, 5.13x10(-3) RIU degree(-1) and 6.014x10(-4) RIU, respectively, encouraging results at this proof of concept stage and considering the ubiquity of the instrumentation.

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.

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.

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

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

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.

Service discovery at home

NARCIS (Netherlands)

Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

2003-01-01

Service discovery is a fairly new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between devices. This paper provides an overview and comparison of several

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.

Cost-effectiveness of computed tomographic colonography screening for colorectal cancer in the medicare population

NARCIS (Netherlands)

A.B. Knudsen (Amy); I. Lansdorp-Vogelaar (Iris); C.M. Rutter (Carolyn); J.E. Savarino (James); M. van Ballegooijen (Marjolein); K.M. Kuntz (Karen); A. Zauber (Ann)

2010-01-01

textabstractBackground The Centers for Medicare and Medicaid Services (CMS) considered whether to reimburse computed tomographic colonography (CTC) for colorectal cancer screening of Medicare enrollees. To help inform its decision, we evaluated the reimbursement rate at which CTC screening could be

The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

Science.gov (United States)

Kunsting, Josef; Wirth, Joachim; Paas, Fred

2011-01-01

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

Service Discovery At Home

NARCIS (Netherlands)

Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

Service discovery is a fady new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between deviies. This paper provides an ovewiew and comparison of several prominent

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.

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

Reduction of the performance of a noise screen due to screen-induced wind-speed gradients: numerical computations and wind-tunnel experiments

NARCIS (Netherlands)

Salomons, E.M.

1999-01-01

Downwind sound propagation over a noise screen is investigated by numerical computations and scale model experiments in a wind tunnel. For the computations, the parabolic equation method is used, with a range-dependent sound-speed profile based on wind-speed profiles measured in the wind tunnel and

Efficient discovery of responses of proteins to compounds using active learning

Science.gov (United States)

2014-01-01

Background Drug discovery and development has been aided by high throughput screening methods that detect compound effects on a single target. However, when using focused initial screening, undesirable secondary effects are often detected late in the development process after significant investment has been made. An alternative approach would be to screen against undesired effects early in the process, but the number of possible secondary targets makes this prohibitively expensive. Results This paper describes methods for making this global approach practical by constructing predictive models for many target responses to many compounds and using them to guide experimentation. We demonstrate for the first time that by jointly modeling targets and compounds using descriptive features and using active machine learning methods, accurate models can be built by doing only a small fraction of possible experiments. The methods were evaluated by computational experiments using a dataset of 177 assays and 20,000 compounds constructed from the PubChem database. Conclusions An average of nearly 60% of all hits in the dataset were found after exploring only 3% of the experimental space which suggests that active learning can be used to enable more complete characterization of compound effects than otherwise affordable. The methods described are also likely to find widespread application outside drug discovery, such as for characterizing the effects of a large number of compounds or inhibitory RNAs on a large number of cell or tissue phenotypes. PMID:24884564

International Association for the Study of Lung Cancer Computed Tomography Screening Workshop 2011 Report

NARCIS (Netherlands)

Field, John K.; Smith, Robert A.; Aberle, Denise R.; Oudkerk, Matthijs; Baldwin, David R.; Yankelevitz, David; Pedersen, Jesper Holst; Swanson, Scott James; Travis, William D.; Wisbuba, Ignacio I.; Noguchi, Masayuki; Mulshine, Jim L.

The International Association for the Study of Lung Cancer (IASLC) Board of Directors convened a computed tomography (CT) Screening Task Force to develop an IASLC position statement, after the National Cancer Institute press statement from the National Lung Screening Trial showed that lung cancer

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.

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.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

Science.gov (United States)

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

Developments in SPR Fragment Screening.

Science.gov (United States)

Chavanieu, Alain; Pugnière, Martine

2016-01-01

Fragment-based approaches have played an increasing role alongside high-throughput screening in drug discovery for 15 years. The label-free biosensor technology based on surface plasmon resonance (SPR) is now sensitive and informative enough to serve during primary screens and validation steps. In this review, the authors discuss the role of SPR in fragment screening. After a brief description of the underlying principles of the technique and main device developments, they evaluate the advantages and adaptations of SPR for fragment-based drug discovery. SPR can also be applied to challenging targets such as membrane receptors and enzymes. The high-level of immobilization of the protein target and its stability are key points for a relevant screening that can be optimized using oriented immobilized proteins and regenerable sensors. Furthermore, to decrease the rate of false negatives, a selectivity test may be performed in parallel on the main target bearing the binding site mutated or blocked with a low-off-rate ligand. Fragment-based drug design, integrated in a rational workflow led by SPR, will thus have a predominant role for the next wave of drug discovery which could be greatly enhanced by new improvements in SPR devices.

Statistical screening of input variables in a complex computer code

International Nuclear Information System (INIS)

Krieger, T.J.

1982-01-01

A method is presented for ''statistical screening'' of input variables in a complex computer code. The object is to determine the ''effective'' or important input variables by estimating the relative magnitudes of their associated sensitivity coefficients. This is accomplished by performing a numerical experiment consisting of a relatively small number of computer runs with the code followed by a statistical analysis of the results. A formula for estimating the sensitivity coefficients is derived. Reference is made to an earlier work in which the method was applied to a complex reactor code with good results

Functional principles of registry-based service discovery

NARCIS (Netherlands)

Sundramoorthy, V.; Tan, C.; Hartel, P.H.; Hartog, den J.I.; Scholten, J.

2005-01-01

As Service Discovery Protocols (SDP) are becoming increasingly important for ubiquitous computing, they must behave according to predefined principles. We present the functional Principles of Service Discovery for robust, registry-based service discovery. A methodology to guarantee adherence to

Screening for cognitive impairment in older individuals. Validation study of a computer-based test.

Science.gov (United States)

Green, R C; Green, J; Harrison, J M; Kutner, M H

1994-08-01

This study examined the validity of a computer-based cognitive test that was recently designed to screen the elderly for cognitive impairment. Criterion-related validity was examined by comparing test scores of impaired patients and normal control subjects. Construct-related validity was computed through correlations between computer-based subtests and related conventional neuropsychological subtests. University center for memory disorders. Fifty-two patients with mild cognitive impairment by strict clinical criteria and 50 unimpaired, age- and education-matched control subjects. Control subjects were rigorously screened by neurological, neuropsychological, imaging, and electrophysiological criteria to identify and exclude individuals with occult abnormalities. Using a cut-off total score of 126, this computer-based instrument had a sensitivity of 0.83 and a specificity of 0.96. Using a prevalence estimate of 10%, predictive values, positive and negative, were 0.70 and 0.96, respectively. Computer-based subtests correlated significantly with conventional neuropsychological tests measuring similar cognitive domains. Thirteen (17.8%) of 73 volunteers with normal medical histories were excluded from the control group, with unsuspected abnormalities on standard neuropsychological tests, electroencephalograms, or magnetic resonance imaging scans. Computer-based testing is a valid screening methodology for the detection of mild cognitive impairment in the elderly, although this particular test has important limitations. Broader applications of computer-based testing will require extensive population-based validation. Future studies should recognize that normal control subjects without a history of disease who are typically used in validation studies may have a high incidence of unsuspected abnormalities on neurodiagnostic studies.

Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds

Science.gov (United States)

Marrero-Ponce, Yovani; Meneses-Marcel, Alfredo; Rivera-Borroto, Oscar M.; García-Domenech, Ramón; De Julián-Ortiz, Jesus Vicente; Montero, Alina; Escario, José Antonio; Barrio, Alicia Gómez; Pereira, David Montero; Nogal, Juan José; Grau, Ricardo; Torrens, Francisco; Vogel, Christian; Arán, Vicente J.

2008-08-01

Trichomonas vaginalis ( Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients ( C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show

Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian models.

Directory of Open Access Journals (Sweden)

Sean Ekins

Full Text Available High-throughput screening (HTS in whole cells is widely pursued to find compounds active against Mycobacterium tuberculosis (Mtb for further development towards new tuberculosis (TB drugs. Hit rates from these screens, usually conducted at 10 to 25 µM concentrations, typically range from less than 1% to the low single digits. New approaches to increase the efficiency of hit identification are urgently needed to learn from past screening data. The pharmaceutical industry has for many years taken advantage of computational approaches to optimize compound libraries for in vitro testing, a practice not fully embraced by academic laboratories in the search for new TB drugs. Adapting these proven approaches, we have recently built and validated Bayesian machine learning models for predicting compounds with activity against Mtb based on publicly available large-scale HTS data from the Tuberculosis Antimicrobial Acquisition Coordinating Facility. We now demonstrate the largest prospective validation to date in which we computationally screened 82,403 molecules with these Bayesian models, assayed a total of 550 molecules in vitro, and identified 124 actives against Mtb. Individual hit rates for the different datasets varied from 15-28%. We have identified several FDA approved and late stage clinical candidate kinase inhibitors with activity against Mtb which may represent starting points for further optimization. The computational models developed herein and the commercially available molecules derived from them are now available to any group pursuing Mtb drug discovery.

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).

In-silico guided discovery of novel CCR9 antagonists

Science.gov (United States)

Zhang, Xin; Cross, Jason B.; Romero, Jan; Heifetz, Alexander; Humphries, Eric; Hall, Katie; Wu, Yuchuan; Stucka, Sabrina; Zhang, Jing; Chandonnet, Haoqun; Lippa, Blaise; Ryan, M. Dominic; Baber, J. Christian

2018-03-01

Antagonism of CCR9 is a promising mechanism for treatment of inflammatory bowel disease, including ulcerative colitis and Crohn's disease. There is limited experimental data on CCR9 and its ligands, complicating efforts to identify new small molecule antagonists. We present here results of a successful virtual screening and rational hit-to-lead campaign that led to the discovery and initial optimization of novel CCR9 antagonists. This work uses a novel data fusion strategy to integrate the output of multiple computational tools, such as 2D similarity search, shape similarity, pharmacophore searching, and molecular docking, as well as the identification and incorporation of privileged chemokine fragments. The application of various ranking strategies, which combined consensus and parallel selection methods to achieve a balance of enrichment and novelty, resulted in 198 virtual screening hits in total, with an overall hit rate of 18%. Several hits were developed into early leads through targeted synthesis and purchase of analogs.

Design and Development of ChemInfoCloud: An Integrated Cloud Enabled Platform for Virtual Screening.

Science.gov (United States)

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Bhavasar, Arvind; Vyas, Renu

2015-01-01

The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.

Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

CERN Document Server

Pal, Sankar K

2004-01-01

Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

A virtual high-throughput screening approach to the discovery of novel inhibitors of the bacterial leucine transporter, LeuT

DEFF Research Database (Denmark)

Simmons, Katie J; Gotfryd, Kamil; Billesbølle, Christian B

2013-01-01

Abstract Membrane proteins are intrinsically involved in both human and pathogen physiology, and are the target of 60% of all marketed drugs. During the past decade, advances in the studies of membrane proteins using X-ray crystallography, electron microscopy and NMR-based techniques led to the e...... this is a virtual high-throughput screening (vHTS) technique initially developed for soluble proteins. This paper describes application of this technique to the discovery of inhibitors of the leucine transporter (LeuT), a member of the neurotransmitter:sodium symporter (NSS) family....

Cancer Biomarker Discovery: Lectin-Based Strategies Targeting Glycoproteins

Directory of Open Access Journals (Sweden)

David Clark

2012-01-01

Full Text Available Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state.

Discovery of novel SERCA inhibitors by virtual screening of a large compound library.

Science.gov (United States)

Elam, Christopher; Lape, Michael; Deye, Joel; Zultowsky, Jodie; Stanton, David T; Paula, Stefan

2011-05-01

Two screening protocols based on recursive partitioning and computational ligand docking methodologies, respectively, were employed for virtual screens of a compound library with 345,000 entries for novel inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA), a potential target for cancer chemotherapy. A total of 72 compounds that were predicted to be potential inhibitors of SERCA were tested in bioassays and 17 displayed inhibitory potencies at concentrations below 100 μM. The majority of these inhibitors were composed of two phenyl rings tethered to each other by a short link of one to three atoms. Putative interactions between SERCA and the inhibitors were identified by inspection of docking-predicted poses and some of the structural features required for effective SERCA inhibition were determined by analysis of the classification pattern employed by the recursive partitioning models. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

Energy Technology Data Exchange (ETDEWEB)

Crabtree, George [Argonne National Lab. (ANL), Argonne, IL (United States); Glotzer, Sharon [University of Michigan; McCurdy, Bill [University of California Davis; Roberto, Jim [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2010-07-26

This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. New materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of

Discovery of earth-abundant nitride semiconductors by computational screening and high-pressure synthesis

Science.gov (United States)

Hinuma, Yoyo; Hatakeyama, Taisuke; Kumagai, Yu; Burton, Lee A.; Sato, Hikaru; Muraba, Yoshinori; Iimura, Soshi; Hiramatsu, Hidenori; Tanaka, Isao; Hosono, Hideo; Oba, Fumiyasu

2016-01-01

Nitride semiconductors are attractive because they can be environmentally benign, comprised of abundant elements and possess favourable electronic properties. However, those currently commercialized are mostly limited to gallium nitride and its alloys, despite the rich composition space of nitrides. Here we report the screening of ternary zinc nitride semiconductors using first-principles calculations of electronic structure, stability and dopability. This approach identifies as-yet-unreported CaZn2N2 that has earth-abundant components, smaller carrier effective masses than gallium nitride and a tunable direct bandgap suited for light emission and harvesting. High-pressure synthesis realizes this phase, verifying the predicted crystal structure and band-edge red photoluminescence. In total, we propose 21 promising systems, including Ca2ZnN2, Ba2ZnN2 and Zn2PN3, which have not been reported as semiconductors previously. Given the variety in bandgaps of the identified compounds, the present study expands the potential suitability of nitride semiconductors for a broader range of electronic, optoelectronic and photovoltaic applications. PMID:27325228

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

Science.gov (United States)

Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

Directory of Open Access Journals (Sweden)

Ye Fang

Full Text Available Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU. First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

Hand held control unit for controlling a display screen-oriented computer game, and a display screen-oriented computer game having one or more such control units

NARCIS (Netherlands)

2001-01-01

A hand-held control unit is used to control a display screen-oriented computer game. The unit comprises a housing with a front side, a set of control members lying generally flush with the front side for through actuating thereof controlling actions of in-game display items, and an output for

Optimizing virtual fragment screening for GPCRs: Identification of novel ligands for the histamine H3 receptor using ligand- and structure-based molecular fingerprints

NARCIS (Netherlands)

Sirci, F.; Istyastono, E.P.; Vischer, H.F.; Nijmeijer, S.; Kuijer, M.; Kooistra, A.J.; Wijtmans, M.; Mannhold, R.; Leurs, R.; de Esch, I.J.P.; de Graaf, C.

2012-01-01

Virtual fragment screening (VFS) is a promising new method that uses computer models to identify small, fragment-like biologically active molecules as useful starting points for fragment-based drug discovery (FBDD). Training sets of true active and inactive fragment-like molecules to construct and

Resource Discovery in Activity-Based Sensor Networks

DEFF Research Database (Denmark)

Bucur, Doina; Bardram, Jakob

This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networ....... ABSN enhances the generic Extended Zone Routing Protocol with logical sensor grouping and greatly lowers network overhead during the process of discovery, while keeping discovery latency close to optimal.......This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

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.

In-bead screening

DEFF Research Database (Denmark)

2013-01-01

The present invention relates to screening of one-bead-one-compound (OBOC) combinatorial libraries which is useful for the discovery of compounds displaying molecular interactions with a biological or a physicochemical system, such as substrates and inhibitors of enzymes and the like. The invention...... provides a method for screening a library of compounds for their interaction with a physico- chemical or biological system and a corresponding kit for performing the method of screening a one-bead-one-compound library of compounds....

Estimation of radiation exposure from lung cancer screening program with low-dose computed tomography

Energy Technology Data Exchange (ETDEWEB)

Kim, Su Yeon; Jun, Jae Kwan [Graduate School of Cancer Science and Policy, National Cancer Center, Seoul (Korea, Republic of)

2016-12-15

The National Lung Screening Trial (NLST) demonstrated that screening with Low-dose Computed Tomography (LDCT) screening reduced lung cancer mortality in a high-risk population. Recently, the United States Preventive Services Task Force (USPSTF) gave a B recommendation for annual LDCT screening for individuals at high-risk. With the promising results, Korea developed lung cancer screening guideline and is planning a pilot study for implementation of national lung cancer screening. With widespread adoption of lung cancer screening with LDCT, there are concerns about harms of screening, including high false-positive rates and radiation exposure. Over the 3 rounds of screening in the NLST, 96.4% of positive results were false-positives. Although the initial screening is performed at low dose, subsequent diagnostic examinations following positive results additively contribute to patient's lifetime exposure. As with implementing a large-scale screening program, there is a lack of established risk assessment about the effect of radiation exposure from long-term screening program. Thus, the purpose of this study was to estimate cumulative radiation exposure of annual LDCT lung cancer screening program over 20-year period.

A "genome-to-lead" approach for insecticide discovery: pharmacological characterization and screening of Aedes aegypti D(1-like dopamine receptors.

Directory of Open Access Journals (Sweden)

Jason M Meyer

2012-01-01

Full Text Available BACKGROUND: Many neglected tropical infectious diseases affecting humans are transmitted by arthropods such as mosquitoes and ticks. New mode-of-action chemistries are urgently sought to enhance vector management practices in countries where arthropod-borne diseases are endemic, especially where vector populations have acquired widespread resistance to insecticides. METHODOLOGY/PRINCIPAL FINDINGS: We describe a "genome-to-lead" approach for insecticide discovery that incorporates the first reported chemical screen of a G protein-coupled receptor (GPCR mined from a mosquito genome. A combination of molecular and pharmacological studies was used to functionally characterize two dopamine receptors (AaDOP1 and AaDOP2 from the yellow fever mosquito, Aedes aegypti. Sequence analyses indicated that these receptors are orthologous to arthropod D(1-like (Gα(s-coupled receptors, but share less than 55% amino acid identity in conserved domains with mammalian dopamine receptors. Heterologous expression of AaDOP1 and AaDOP2 in HEK293 cells revealed dose-dependent responses to dopamine (EC(50: AaDOP1 = 3.1±1.1 nM; AaDOP2 = 240±16 nM. Interestingly, only AaDOP1 exhibited sensitivity to epinephrine (EC(50 = 5.8±1.5 nM and norepinephrine (EC(50 = 760±180 nM, while neither receptor was activated by other biogenic amines tested. Differential responses were observed between these receptors regarding their sensitivity to dopamine agonists and antagonists, level of maximal stimulation, and constitutive activity. Subsequently, a chemical library screen was implemented to discover lead chemistries active at AaDOP2. Fifty-one compounds were identified as "hits," and follow-up validation assays confirmed the antagonistic effect of selected compounds at AaDOP2. In vitro comparison studies between AaDOP2 and the human D(1 dopamine receptor (hD(1 revealed markedly different pharmacological profiles and identified amitriptyline and doxepin as AaDOP2

OPENING REMARKS: Scientific Discovery through Advanced Computing

Science.gov (United States)

Strayer, Michael

2006-01-01

as the national and regional electricity grid, carbon sequestration, virtual engineering, and the nuclear fuel cycle. The successes of the first five years of SciDAC have demonstrated the power of using advanced computing to enable scientific discovery. One measure of this success could be found in the President’s State of the Union address in which President Bush identified ‘supercomputing’ as a major focus area of the American Competitiveness Initiative. Funds were provided in the FY 2007 President’s Budget request to increase the size of the NERSC-5 procurement to between 100-150 teraflops, to upgrade the LCF Cray XT3 at Oak Ridge to 250 teraflops and acquire a 100 teraflop IBM BlueGene/P to establish the Leadership computing facility at Argonne. We believe that we are on a path to establish a petascale computing resource for open science by 2009. We must develop software tools, packages, and libraries as well as the scientific application software that will scale to hundreds of thousands of processors. Computer scientists from universities and the DOE’s national laboratories will be asked to collaborate on the development of the critical system software components such as compilers, light-weight operating systems and file systems. Standing up these large machines will not be business as usual for ASCR. We intend to develop a series of interconnected projects that identify cost, schedule, risks, and scope for the upgrades at the LCF at Oak Ridge, the establishment of the LCF at Argonne, and the development of the software to support these high-end computers. The critical first step in defining the scope of the project is to identify a set of early application codes for each leadership class computing facility. These codes will have access to the resources during the commissioning phase of the facility projects and will be part of the acceptance tests for the machines. Applications will be selected, in part, by breakthrough science, scalability, and

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/.

[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.

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.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan.

Science.gov (United States)

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan

Science.gov (United States)

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

Computational approaches to screen candidate ligands with anti- Parkinson's activity using R programming.

Science.gov (United States)

Jayadeepa, R M; Niveditha, M S

2012-01-01

It is estimated that by 2050 over 100 million people will be affected by the Parkinson's disease (PD). We propose various computational approaches to screen suitable candidate ligand with anti-Parkinson's activity from phytochemicals. Five different types of dopamine receptors have been identified in the brain, D1-D5. Dopamine receptor D3 was selected as the target receptor. The D3 receptor exists in areas of the brain outside the basal ganglia, such as the limbic system, and thus may play a role in the cognitive and emotional changes noted in Parkinson's disease. A ligand library of 100 molecules with anti-Parkinson's activity was collected from literature survey. Nature is the best combinatorial chemist and possibly has answers to all diseases of mankind. Failure of some synthetic drugs and its side effects have prompted many researches to go back to ancient healing methods which use herbal medicines to give relief. Hence, the candidate ligands with anti-Parkinson's were selected from herbal sources through literature survey. Lipinski rules were applied to screen the suitable molecules for the study, the resulting 88 molecules were energy minimized, and subjected to docking using Autodock Vina. The top eleven molecules were screened according to the docking score generated by Autodock Vina Commercial drug Ropinirole was computed similarly and was compared with the 11 phytochemicals score, the screened molecules were subjected to toxicity analysis and to verify toxic property of phytochemicals. R Programming was applied to remove the bias from the top eleven molecules. Using cluster analysis and Confusion Matrix two phytochemicals were computationally selected namely Rosmarinic acid and Gingkolide A for further studies on the disease Parkinson's.

A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents.

Directory of Open Access Journals (Sweden)

Yunierkis Perez-Castillo

Full Text Available Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease. In this sense, it is essential to discover new molecular agents capable of targeting various gastric cancer subtypes simultaneously. Here, we present a multi-objective approach for the ligand-based virtual screening discovery of chemical compounds simultaneously active against the gastric cancer cell lines AGS, NCI-N87 and SNU-1. The proposed approach relays in a novel methodology based on the development of ensemble models for the bioactivity prediction against each individual gastric cancer cell line. The methodology includes the aggregation of one ensemble per cell line using a desirability-based algorithm into virtual screening protocols. Our research leads to the proposal of a multi-targeted virtual screening protocol able to achieve high enrichment of known chemicals with anti-gastric cancer activity. Specifically, our results indicate that, using the proposed protocol, it is possible to retrieve almost 20 more times multi-targeted compounds in the first 1% of the ranked list than what is expected from a uniform distribution of the active ones in the virtual screening database. More importantly, the proposed protocol attains an outstanding initial enrichment of known multi-targeted anti-gastric cancer agents.

The Greatest Mathematical Discovery?

Energy Technology Data Exchange (ETDEWEB)

Bailey, David H.; Borwein, Jonathan M.

2010-05-12

What mathematical discovery more than 1500 years ago: (1) Is one of the greatest, if not the greatest, single discovery in the field of mathematics? (2) Involved three subtle ideas that eluded the greatest minds of antiquity, even geniuses such as Archimedes? (3) Was fiercely resisted in Europe for hundreds of years after its discovery? (4) Even today, in historical treatments of mathematics, is often dismissed with scant mention, or else is ascribed to the wrong source? Answer: Our modern system of positional decimal notation with zero, together with the basic arithmetic computational schemes, which were discovered in India about 500 CE.

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.

Radioactivity on the surfaces of computer monitors and television screens due to progeny palatal

International Nuclear Information System (INIS)

Abdel-Nady, A.; Morsy, A.A.

2002-01-01

Computer monitors and television screens can collect radon progeny. Radon decay forming meta-stable progeny, namely, Po-218, Po-214, and Po-210, which are found mostly in positively, charged aerosol particles. These particles are attract by the large negative field of a video display terminals (VDT) leading to buildup of radioactivity on the VDT screen. The charged aerosol particles might drift in the electric field between the VDT and the operator and be accelerated into the operator's face. The aim of this work is to measure these phenomena set of ultra-sensitive TASTRAK detectors used to measure the plate out of positively charged radioactive radon progeny. The track detectors were fixed on the outer monitor screen. For an occupational computer worker spending 200 days per year for 6 hours a day. It was found that the mean dose equivalent was 1.77 mSv, 0.25 mSv/year for normal CRT and LCD monitors respectively

Low-dose computed tomography for lung cancer screening: comparison of performance between annual and biennial screen

Energy Technology Data Exchange (ETDEWEB)

Sverzellati, Nicola; Silva, M. [University of Parma, Radiology, Department of Surgical Sciences, Parma (Italy); Calareso, G.; Marchiano, A. [Fondazione IRCCS Istituto Nazionale dei Tumori, Department of Radiology, Milan (Italy); Galeone, C. [University of Milano-Bicocca, Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, Milan (Italy); Sestini, S.; Pastorino, U. [Fondazione IRCCS Istituto Nazionale dei Tumori, Department of Surgery, Section of Thoracic Surgery, Milan (Italy); Sozzi, G. [Fondazione IRCCS Istituto Nazionale dei Tumori, Tumor Genomics Unit, Department of Experimental Oncology and Molecular Medicine, Milan (Italy)

2016-11-15

To compare the performance metrics of two different strategies of lung cancer screening by low-dose computed tomography (LDCT), namely, annual (LDCT1) or biennial (LDCT2) screen. Recall rate, detection rate, interval cancers, sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively) were compared between LDCT1 and LDCT2 arms of the MILD trial over the first seven (T0-T6; median follow-up 7.3 years) and four rounds (T0-T3; median follow-up 7.3 years), respectively. 1152 LDCT1 and 1151 LDCT2 participants underwent a total of 6893 and 4715 LDCT scans, respectively. The overall recall rate was higher in LDCT2 arm (6.97 %) than in LDCT1 arm (5.81 %) (p = 0.01), which was counterbalanced by the overall lower number of LDCT scans. No difference was observed for the overall detection rate (0.56 % in both arms). The two LDCT arms had similar specificity (99.2 % in both arms), sensitivity (73.5 %, in LDCT2 vs. 68.5 % in LDCT1, p = 0.62), PPV (42.4 %, in LDCT2, vs. 40.6 %, in LDCT1, p = 0.83) and NPV (99.8 %, in LDCT2 vs. 99.7 %, in LDCT1, p = 0.71). Biennial screen may save about one third of LDCT scans with similar performance indicators as compared to annual screening. (orig.)

Low-dose computed tomography for lung cancer screening: comparison of performance between annual and biennial screen

International Nuclear Information System (INIS)

Sverzellati, Nicola; Silva, M.; Calareso, G.; Marchiano, A.; Galeone, C.; Sestini, S.; Pastorino, U.; Sozzi, G.

2016-01-01

To compare the performance metrics of two different strategies of lung cancer screening by low-dose computed tomography (LDCT), namely, annual (LDCT1) or biennial (LDCT2) screen. Recall rate, detection rate, interval cancers, sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively) were compared between LDCT1 and LDCT2 arms of the MILD trial over the first seven (T0-T6; median follow-up 7.3 years) and four rounds (T0-T3; median follow-up 7.3 years), respectively. 1152 LDCT1 and 1151 LDCT2 participants underwent a total of 6893 and 4715 LDCT scans, respectively. The overall recall rate was higher in LDCT2 arm (6.97 %) than in LDCT1 arm (5.81 %) (p = 0.01), which was counterbalanced by the overall lower number of LDCT scans. No difference was observed for the overall detection rate (0.56 % in both arms). The two LDCT arms had similar specificity (99.2 % in both arms), sensitivity (73.5 %, in LDCT2 vs. 68.5 % in LDCT1, p = 0.62), PPV (42.4 %, in LDCT2, vs. 40.6 %, in LDCT1, p = 0.83) and NPV (99.8 %, in LDCT2 vs. 99.7 %, in LDCT1, p = 0.71). Biennial screen may save about one third of LDCT scans with similar performance indicators as compared to annual screening. (orig.)

BLSSpeller: exhaustive comparative discovery of conserved cis-regulatory elements.

Science.gov (United States)

De Witte, Dieter; Van de Velde, Jan; Decap, Dries; Van Bel, Michiel; Audenaert, Pieter; Demeester, Piet; Dhoedt, Bart; Vandepoele, Klaas; Fostier, Jan

2015-12-01

The accurate discovery and annotation of regulatory elements remains a challenging problem. The growing number of sequenced genomes creates new opportunities for comparative approaches to motif discovery. Putative binding sites are then considered to be functional if they are conserved in orthologous promoter sequences of multiple related species. Existing methods for comparative motif discovery usually rely on pregenerated multiple sequence alignments, which are difficult to obtain for more diverged species such as plants. As a consequence, misaligned regulatory elements often remain undetected. We present a novel algorithm that supports both alignment-free and alignment-based motif discovery in the promoter sequences of related species. Putative motifs are exhaustively enumerated as words over the IUPAC alphabet and screened for conservation using the branch length score. Additionally, a confidence score is established in a genome-wide fashion. In order to take advantage of a cloud computing infrastructure, the MapReduce programming model is adopted. The method is applied to four monocotyledon plant species and it is shown that high-scoring motifs are significantly enriched for open chromatin regions in Oryza sativa and for transcription factor binding sites inferred through protein-binding microarrays in O.sativa and Zea mays. Furthermore, the method is shown to recover experimentally profiled ga2ox1-like KN1 binding sites in Z.mays. BLSSpeller was written in Java. Source code and manual are available at http://bioinformatics.intec.ugent.be/blsspeller Klaas.Vandepoele@psb.vib-ugent.be or jan.fostier@intec.ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Abdominal ultrasound-scanning versus non-contrast computed tomography as screening method for abdominal aortic aneurysm

DEFF Research Database (Denmark)

Liisberg, Mads; Diederichsen, Axel C.; Lindholt, Jes S.

2017-01-01

Background: Validating non-contrast-enhanced computed tomography (nCT) compared to ultrasound sonography (US) as screening method for abdominal aortic aneurysm (AAA) screening. Methods: Consecutively attending men (n = 566) from the pilot study of the randomized Danish CardioVascular Screening......CT seems superior to US concerning sensitivity, and is able to detect aneurysmal lesions not detectable with US. Finally, the prevalence of AAA in Denmark seems to remain relatively high, in this small pilot study group....

Integration of Lead Discovery Tactics and the Evolution of the Lead Discovery Toolbox.

Science.gov (United States)

Leveridge, Melanie; Chung, Chun-Wa; Gross, Jeffrey W; Phelps, Christopher B; Green, Darren

2018-06-01

There has been much debate around the success rates of various screening strategies to identify starting points for drug discovery. Although high-throughput target-based and phenotypic screening has been the focus of this debate, techniques such as fragment screening, virtual screening, and DNA-encoded library screening are also increasingly reported as a source of new chemical equity. Here, we provide examples in which integration of more than one screening approach has improved the campaign outcome and discuss how strengths and weaknesses of various methods can be used to build a complementary toolbox of approaches, giving researchers the greatest probability of successfully identifying leads. Among others, we highlight case studies for receptor-interacting serine/threonine-protein kinase 1 and the bromo- and extra-terminal domain family of bromodomains. In each example, the unique insight or chemistries individual approaches provided are described, emphasizing the synergy of information obtained from the various tactics employed and the particular question each tactic was employed to answer. We conclude with a short prospective discussing how screening strategies are evolving, what this screening toolbox might look like in the future, how to maximize success through integration of multiple tactics, and scenarios that drive selection of one combination of tactics over another.

A High Throughput, 384-Well, Semi-Automated, Hepatocyte Intrinsic Clearance Assay for Screening New Molecular Entities in Drug Discovery.

Science.gov (United States)

Heinle, Lance; Peterkin, Vincent; de Morais, Sonia M; Jenkins, Gary J; Badagnani, Ilaria

2015-01-01

A high throughput, semi-automated clearance screening assay in hepatocytes was developed allowing a scientist to generate data for 96 compounds in one week. The 384-well format assay utilizes a Thermo Multidrop Combi and an optimized LC-MS/MS method. The previously reported LCMS/ MS method reduced the analytical run time by 3-fold, down to 1.2 min injection-to-injection. The Multidrop was able to deliver hepatocytes to 384-well plates with minimal viability loss. Comparison of results from the new 384-well and historical 24-well assays yielded a correlation of 0.95. In addition, results obtained for 25 marketed drugs with various metabolism pathways had a correlation of 0.75 when compared with literature values. Precision was maintained in the new format as 8 compounds tested in ≥39 independent experiments had coefficients of variation ≤21%. The ability to predict in vivo clearances using the new stability assay format was also investigated using 22 marketed drugs and 26 AbbVie compounds. Correction of intrinsic clearance values with binding to hepatocytes (in vitro data) and plasma (in vivo data) resulted in a higher in vitro to in vivo correlation when comparing 22 marketed compounds in human (0.80 vs 0.35) and 26 AbbVie Discovery compounds in rat (0.56 vs 0.17), demonstrating the importance of correcting for binding in clearance studies. This newly developed high throughput, semi-automated clearance assay allows for rapid screening of Discovery compounds to enable Structure Activity Relationship (SAR) analysis based on high quality hepatocyte stability data in sufficient quantity and quality to drive the next round of compound synthesis.

Comparison of different strategies in prenatal screening for Down's syndrome: cost effectiveness analysis of computer simulation.

Science.gov (United States)

Gekas, Jean; Gagné, Geneviève; Bujold, Emmanuel; Douillard, Daniel; Forest, Jean-Claude; Reinharz, Daniel; Rousseau, François

2009-02-13

To assess and compare the cost effectiveness of three different strategies for prenatal screening for Down's syndrome (integrated test, sequential screening, and contingent screenings) and to determine the most useful cut-off values for risk. Computer simulations to study integrated, sequential, and contingent screening strategies with various cut-offs leading to 19 potential screening algorithms. The computer simulation was populated with data from the Serum Urine and Ultrasound Screening Study (SURUSS), real unit costs for healthcare interventions, and a population of 110 948 pregnancies from the province of Québec for the year 2001. Cost effectiveness ratios, incremental cost effectiveness ratios, and screening options' outcomes. The contingent screening strategy dominated all other screening options: it had the best cost effectiveness ratio ($C26,833 per case of Down's syndrome) with fewer procedure related euploid miscarriages and unnecessary terminations (respectively, 6 and 16 per 100,000 pregnancies). It also outperformed serum screening at the second trimester. In terms of the incremental cost effectiveness ratio, contingent screening was still dominant: compared with screening based on maternal age alone, the savings were $C30,963 per additional birth with Down's syndrome averted. Contingent screening was the only screening strategy that offered early reassurance to the majority of women (77.81%) in first trimester and minimised costs by limiting retesting during the second trimester (21.05%). For the contingent and sequential screening strategies, the choice of cut-off value for risk in the first trimester test significantly affected the cost effectiveness ratios (respectively, from $C26,833 to $C37,260 and from $C35,215 to $C45,314 per case of Down's syndrome), the number of procedure related euploid miscarriages (from 6 to 46 and from 6 to 45 per 100,000 pregnancies), and the number of unnecessary terminations (from 16 to 26 and from 16 to 25 per 100

ATLAS distributed computing operation shift teams experience during the discovery year and beginning of the long shutdown 1

International Nuclear Information System (INIS)

Sedov, Alexey; Girolamo, Alessandro Di; Negri, Guidone; Sakamoto, Hiroshi; Schovancová, Jaroslava; Smirnov, Iouri; Vartapetian, Armen; Yu, Jaehoon

2014-01-01

ATLAS Distributed Computing Operation Shifts evolve to meet new requirements. New monitoring tools as well as operational changes lead to modifications in organization of shifts. In this paper we describe the structure of shifts, the roles of different shifts in ATLAS computing grid operation, the influence of a Higgs-like particle discovery on shift operation, the achievements in monitoring and automation that allowed extra focus on the experiment priority tasks, and the influence of the Long Shutdown 1 and operational changes related to the no beam period.

Cost-effectiveness of implementing computed tomography screening for lung cancer in Taiwan.

Science.gov (United States)

Yang, Szu-Chun; Lai, Wu-Wei; Lin, Chien-Chung; Su, Wu-Chou; Ku, Li-Jung; Hwang, Jing-Shiang; Wang, Jung-Der

2017-06-01

A screening program for lung cancer requires more empirical evidence. Based on the experience of the National Lung Screening Trial (NLST), we developed a method to adjust lead-time bias and quality-of-life changes for estimating the cost-effectiveness of implementing computed tomography (CT) screening in Taiwan. The target population was high-risk (≥30 pack-years) smokers between 55 and 75 years of age. From a nation-wide, 13-year follow-up cohort, we estimated quality-adjusted life expectancy (QALE), loss-of-QALE, and lifetime healthcare expenditures per case of lung cancer stratified by pathology and stage. Cumulative stage distributions for CT-screening and no-screening were assumed equal to those for CT-screening and radiography-screening in the NLST to estimate the savings of loss-of-QALE and additional costs of lifetime healthcare expenditures after CT screening. Costs attributable to screen-negative subjects, false-positive cases and radiation-induced lung cancer were included to obtain the incremental cost-effectiveness ratio from the public payer's perspective. The incremental costs were US$22,755 per person. After dividing this by savings of loss-of-QALE (1.16 quality-adjusted life year (QALY)), the incremental cost-effectiveness ratio was US$19,683 per QALY. This ratio would fall to US$10,947 per QALY if the stage distribution for CT-screening was the same as that of screen-detected cancers in the NELSON trial. Low-dose CT screening for lung cancer among high-risk smokers would be cost-effective in Taiwan. As only about 5% of our women are smokers, future research is necessary to identify the high-risk groups among non-smokers and increase the coverage. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Mass spectrometry for fragment screening.

Science.gov (United States)

Chan, Daniel Shiu-Hin; Whitehouse, Andrew J; Coyne, Anthony G; Abell, Chris

2017-11-08

Fragment-based approaches in chemical biology and drug discovery have been widely adopted worldwide in both academia and industry. Fragment hits tend to interact weakly with their targets, necessitating the use of sensitive biophysical techniques to detect their binding. Common fragment screening techniques include differential scanning fluorimetry (DSF) and ligand-observed NMR. Validation and characterization of hits is usually performed using a combination of protein-observed NMR, isothermal titration calorimetry (ITC) and X-ray crystallography. In this context, MS is a relatively underutilized technique in fragment screening for drug discovery. MS-based techniques have the advantage of high sensitivity, low sample consumption and being label-free. This review highlights recent examples of the emerging use of MS-based techniques in fragment screening. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

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.

A new approach to the rationale discovery of polymeric biomaterials

Science.gov (United States)

Kohn, Joachim; Welsh, William J.; Knight, Doyle

2007-01-01

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

Computer-assisted static/dynamic renal imaging: a screening test for renovascular hypertension

International Nuclear Information System (INIS)

Keim, H.J.; Johnson, P.M.; Vaughan, E.D. Jr.; Beg, K.; Follett, D.A.; Freeman, L.M.; Laragh, J.H.

1979-01-01

Computer-assisted static/dynamic renal imaging with [ 197 Hg] chlormerodrin and [/sup 99m/Tc] pertechnetate was evaluated prospectively as a screening test for renovascular hypertension. Results are reported for 51 patients: 33 with benign essential hypertension and 18 with renovascular hypertension, and for 21 normal controls. All patients underwent renal arteriography. Patients with significant obesity, renal insufficiency, or renoparenchymal disease were excluded from this study. Independent visual analyses of renal gamma images and time-activity transit curves identified 17 of the 18 patients with renovascular hypertension; one study was equivocal. There were five equivocal and three false-positive results in the essential hypertension and normal control groups. The sensitivity of the method was 94% and the specificity 85%. Since the prevalence of the renovascular subset of hypertension is approximately 5%, the predictive value is only 25%. Inclusion of computer-generated data did not improve this result. Accordingly, this method is not recommended as a primary screening test for renovascular hypertension

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.

The multiple roles of computational chemistry in fragment-based drug design

Science.gov (United States)

Law, Richard; Barker, Oliver; Barker, John J.; Hesterkamp, Thomas; Godemann, Robert; Andersen, Ole; Fryatt, Tara; Courtney, Steve; Hallett, Dave; Whittaker, Mark

2009-08-01

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

A virtual screening method for inhibitory peptides of Angiotensin I-converting enzyme.

Science.gov (United States)

Wu, Hongxi; Liu, Yalan; Guo, Mingrong; Xie, Jingli; Jiang, XiaMin

2014-09-01

Natural small peptides from foods have been proven to be efficient inhibitors of Angiotensin I-converting enzyme (ACE) for the regulation of blood pressure. The traditional ACE inhibitory peptides screening method is both time consuming and money costing, to the contrary, virtual screening method by computation can break these limitations. We establish a virtual screening method to obtain ACE inhibitory peptides with the help of Libdock module of Discovery Studio 3.5 software. A significant relationship between Libdock score and experimental IC(50) was found, Libdock score = 10.063 log(1/IC(50)) + 68.08 (R(2) = 0.62). The credibility of the relationship was confirmed by testing the coincidence of the estimated log(1/IC(50)) and measured log(1/IC(50)) (IC(50) is 50% inhibitory concentration toward ACE, in μmol/L) of 5 synthetic ACE inhibitory peptides, which was virtual hydrolyzed and screened from a kind of seafood, Phascolosoma esculenta. Accordingly, Libdock method is a valid IC(50) estimation tool and virtual screening method for small ACE inhibitory peptides. © 2014 Institute of Food Technologists®

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.

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.

Development and Usability Testing of a Computer-Tailored Decision Support Tool for Lung Cancer Screening: Study Protocol.

Science.gov (United States)

Carter-Harris, Lisa; Comer, Robert Skipworth; Goyal, Anurag; Vode, Emilee Christine; Hanna, Nasser; Ceppa, DuyKhanh; Rawl, Susan M

2017-11-16

Awareness of lung cancer screening remains low in the screening-eligible population, and when patients visit their clinician never having heard of lung cancer screening, engaging in shared decision making to arrive at an informed decision can be a challenge. Therefore, methods to effectively support both patients and clinicians to engage in these important discussions are essential. To facilitate shared decision making about lung cancer screening, effective methods to prepare patients to have these important discussions with their clinician are needed. Our objective is to develop a computer-tailored decision support tool that meets the certification criteria of the International Patient Decision Aid Standards instrument version 4.0 that will support shared decision making in lung cancer screening decisions. Using a 3-phase process, we will develop and test a prototype of a computer-tailored decision support tool in a sample of lung cancer screening-eligible individuals. In phase I, we assembled a community advisory board comprising 10 screening-eligible individuals to develop the prototype. In phase II, we recruited a sample of 13 screening-eligible individuals to test the prototype for usability, acceptability, and satisfaction. In phase III, we are conducting a pilot randomized controlled trial (RCT) with 60 screening-eligible participants who have never been screened for lung cancer. Outcomes tested include lung cancer and screening knowledge, lung cancer screening health beliefs (perceived risk, perceived benefits, perceived barriers, and self-efficacy), perception of being prepared to engage in a patient-clinician discussion about lung cancer screening, occurrence of a patient-clinician discussion about lung cancer screening, and stage of adoption for lung cancer screening. Phases I and II are complete. Phase III is underway. As of July 15, 2017, 60 participants have been enrolled into the study, and have completed the baseline survey, intervention, and first

High-throughput screening platform for natural product-based drug discovery against 3 neglected tropical diseases: human African trypanosomiasis, leishmaniasis, and Chagas disease.

Science.gov (United States)

Annang, F; Pérez-Moreno, G; García-Hernández, R; Cordon-Obras, C; Martín, J; Tormo, J R; Rodríguez, L; de Pedro, N; Gómez-Pérez, V; Valente, M; Reyes, F; Genilloud, O; Vicente, F; Castanys, S; Ruiz-Pérez, L M; Navarro, M; Gamarro, F; González-Pacanowska, D

2015-01-01

African trypanosomiasis, leishmaniasis, and Chagas disease are 3 neglected tropical diseases for which current therapeutic interventions are inadequate or toxic. There is an urgent need to find new lead compounds against these diseases. Most drug discovery strategies rely on high-throughput screening (HTS) of synthetic chemical libraries using phenotypic and target-based approaches. Combinatorial chemistry libraries contain hundreds of thousands of compounds; however, they lack the structural diversity required to find entirely novel chemotypes. Natural products, in contrast, are a highly underexplored pool of unique chemical diversity that can serve as excellent templates for the synthesis of novel, biologically active molecules. We report here a validated HTS platform for the screening of microbial extracts against the 3 diseases. We have used this platform in a pilot project to screen a subset (5976) of microbial extracts from the MEDINA Natural Products library. Tandem liquid chromatography-mass spectrometry showed that 48 extracts contain potentially new compounds that are currently undergoing de-replication for future isolation and characterization. Known active components included actinomycin D, bafilomycin B1, chromomycin A3, echinomycin, hygrolidin, and nonactins, among others. The report here is, to our knowledge, the first HTS of microbial natural product extracts against the above-mentioned kinetoplastid parasites. © 2014 Society for Laboratory Automation and Screening.

Reverse screening methods to search for the protein targets of chemopreventive compounds

Science.gov (United States)

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-05-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and

Efficacy of computer-aided detection system for screening mammography

International Nuclear Information System (INIS)

Saito, Mioko; Ohnuki, Koji; Yamada, Takayuki; Saito, Haruo; Ishibashi, Tadashi; Ohuchi, Noriaki; Takahashi, Shoki

2002-01-01

A study was conducted to evaluate the efficacy of a computer-aided detection (CAD) system for screening mammography (MMG). Screening mammograms of 2,231 women aged over 50 yr were examined. Medio-lateral oblique (MLO) images were obtained, and two expert observers interpreted the mammograms by consensus. First, each mammogram was interpreted without the assistance of CAD, followed immediately by a re-evaluation of areas marked by the CAD system. Data were recorded to measure the effect of CAD on the recall rate, cancer detection rate and detection rate of masses, microcalcifications and other findings. The CAD system increased the recall rate from 2.3% to 2.6%. Six recalled cases were diagnosed as breast cancer pathologically, and CAD detected all of these lesions. Seven additional cases in which CAD detected abnormal findings had no malignancy. The detection rate of CAD for microcalcifications was high (95.0%). However, the detection rate for mass lesions and other findings was low (29.2% and 25.0% respectively). The false positivity rate was 0.13/film for microcalcifications, and 0.25/film for mass lesions. The efficacy of the CAD system for detecting microcalcifications on screening mammograms was confirmed. However, the low detection rate of mass lesions and relatively high rate of false positivity need to be further improved. (author)

Atrial Fibrillation Screening in Nonmetropolitan Areas Using a Telehealth Surveillance System With an Embedded Cloud-Computing Algorithm: Prospective Pilot Study

Science.gov (United States)

Chen, Ying-Hsien; Hung, Chi-Sheng; Huang, Ching-Chang; Hung, Yu-Chien

2017-01-01

Background Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. Objective The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. Methods We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Results Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4%, 22/922) residents with AF were identified by the physician’s ECG interpretation, and only 0.2% (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5% (95% CI 77.2%-99.9%) and specificity of 97.7% (95% CI 96.5%-98.5%). The overall satisfaction score for the process of AF screening was 92.1%. Conclusions AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. PMID:28951384

Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control

Science.gov (United States)

Raschka, Sebastian; Scott, Anne M.; Liu, Nan; Gunturu, Santosh; Huertas, Mar; Li, Weiming; Kuhn, Leslie A.

2018-03-01

While the advantage of screening vast databases of molecules to cover greater molecular diversity is often mentioned, in reality, only a few studies have been published demonstrating inhibitor discovery by screening more than a million compounds for features that mimic a known three-dimensional (3D) ligand. Two factors contribute: the general difficulty of discovering potent inhibitors, and the lack of free, user-friendly software to incorporate project-specific knowledge and user hypotheses into 3D ligand-based screening. The Screenlamp modular toolkit presented here was developed with these needs in mind. We show Screenlamp's ability to screen more than 12 million commercially available molecules and identify potent in vivo inhibitors of a G protein-coupled bile acid receptor within the first year of a discovery project. This pheromone receptor governs sea lamprey reproductive behavior, and to our knowledge, this project is the first to establish the efficacy of computational screening in discovering lead compounds for aquatic invasive species control. Significant enhancement in activity came from selecting compounds based on one of the hypotheses: that matching two distal oxygen groups in the 3D structure of the pheromone is crucial for activity. Six of the 15 most active compounds met these criteria. A second hypothesis—that presence of an alkyl sulfate side chain results in high activity—identified another 6 compounds in the top 10, demonstrating the significant benefits of hypothesis-driven screening.

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

Theoretical design and discovery of the most-promising, previously overlooked hybrid perovskite compounds

Energy Technology Data Exchange (ETDEWEB)

Zunger, Alex [University of Colorado Boulder; Kazmerski, Lawrence [University of Colorado Boulder; Dalpian, Gustavo [University of Colorado Boulder

2018-03-14

The material class of hybrid organic-inorganic perovskites (AMX3) has risen rapidly from a virtually unknown material in photovoltaic applications a short 8-years ago into 20-23% efficient thin-film solar cell devices. As promising as this class of materials is, however, there are limitations associated with its poor long-term stability, non-optimal band gap, and the presence of toxic Pb atom on the metalloid site. An Edisonian laboratory exploration (i.e., growth + characterization) via trial-and-error processes of all other candidate materials, is unpractical. Our approach uses high speed computational design and discovery to screen the ‘best of class” candidates based upon optimal functionalities.

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....

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.

Accelerating the discovery of materials for clean energy in the era of smart automation

Science.gov (United States)

Tabor, Daniel P.; Roch, Loïc M.; Saikin, Semion K.; Kreisbeck, Christoph; Sheberla, Dennis; Montoya, Joseph H.; Dwaraknath, Shyam; Aykol, Muratahan; Ortiz, Carlos; Tribukait, Hermann; Amador-Bedolla, Carlos; Brabec, Christoph J.; Maruyama, Benji; Persson, Kristin A.; Aspuru-Guzik, Alán

2018-05-01

The discovery and development of novel materials in the field of energy are essential to accelerate the transition to a low-carbon economy. Bringing recent technological innovations in automation, robotics and computer science together with current approaches in chemistry, materials synthesis and characterization will act as a catalyst for revolutionizing traditional research and development in both industry and academia. This Perspective provides a vision for an integrated artificial intelligence approach towards autonomous materials discovery, which, in our opinion, will emerge within the next 5 to 10 years. The approach we discuss requires the integration of the following tools, which have already seen substantial development to date: high-throughput virtual screening, automated synthesis planning, automated laboratories and machine learning algorithms. In addition to reducing the time to deployment of new materials by an order of magnitude, this integrated approach is expected to lower the cost associated with the initial discovery. Thus, the price of the final products (for example, solar panels, batteries and electric vehicles) will also decrease. This in turn will enable industries and governments to meet more ambitious targets in terms of reducing greenhouse gas emissions at a faster pace.

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.

Empirical study of supervised gene screening

Directory of Open Access Journals (Sweden)

Ma Shuangge

2006-12-01

Full Text Available Abstract Background Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray measurements usually consists of three steps: (1 unsupervised gene screening; (2 supervised gene screening; and (3 statistical model building. Supervised gene screening based on marginal gene ranking is commonly used to reduce the number of genes in the model building. Various simple statistics, such as t-statistic or signal to noise ratio, have been used to rank genes in the supervised screening. Despite of its extensive usage, statistical study of supervised gene screening remains scarce. Our study is partly motivated by the differences in gene discovery results caused by using different supervised gene screening methods. Results We investigate concordance and reproducibility of supervised gene screening based on eight commonly used marginal statistics. Concordance is assessed by the relative fractions of overlaps between top ranked genes screened using different marginal statistics. We propose a Bootstrap Reproducibility Index, which measures reproducibility of individual genes under the supervised screening. Empirical studies are based on four public microarray data. We consider the cases where the top 20%, 40% and 60% genes are screened. Conclusion From a gene discovery point of view, the effect of supervised gene screening based on different marginal statistics cannot be ignored. Empirical studies show that (1 genes passed different supervised screenings may be considerably different; (2 concordance may vary, depending on the underlying data structure and percentage of selected genes; (3 evaluated with the Bootstrap Reproducibility Index, genes passed supervised screenings are only moderately reproducible; and (4 concordance cannot be improved by supervised screening based on reproducibility.

Optimisation and assessment of three modern touch screen tablet computers for clinical vision testing.

Directory of Open Access Journals (Sweden)

Humza J Tahir

Full Text Available Technological advances have led to the development of powerful yet portable tablet computers whose touch-screen resolutions now permit the presentation of targets small enough to test the limits of normal visual acuity. Such devices have become ubiquitous in daily life and are moving into the clinical space. However, in order to produce clinically valid tests, it is important to identify the limits imposed by the screen characteristics, such as resolution, brightness uniformity, contrast linearity and the effect of viewing angle. Previously we have conducted such tests on the iPad 3. Here we extend our investigations to 2 other devices and outline a protocol for calibrating such screens, using standardised methods to measure the gamma function, warm up time, screen uniformity and the effects of viewing angle and screen reflections. We demonstrate that all three devices manifest typical gamma functions for voltage and luminance with warm up times of approximately 15 minutes. However, there were differences in homogeneity and reflectance among the displays. We suggest practical means to optimise quality of display for vision testing including screen calibration.

Optimisation and assessment of three modern touch screen tablet computers for clinical vision testing.

Science.gov (United States)

Tahir, Humza J; Murray, Ian J; Parry, Neil R A; Aslam, Tariq M

2014-01-01

Technological advances have led to the development of powerful yet portable tablet computers whose touch-screen resolutions now permit the presentation of targets small enough to test the limits of normal visual acuity. Such devices have become ubiquitous in daily life and are moving into the clinical space. However, in order to produce clinically valid tests, it is important to identify the limits imposed by the screen characteristics, such as resolution, brightness uniformity, contrast linearity and the effect of viewing angle. Previously we have conducted such tests on the iPad 3. Here we extend our investigations to 2 other devices and outline a protocol for calibrating such screens, using standardised methods to measure the gamma function, warm up time, screen uniformity and the effects of viewing angle and screen reflections. We demonstrate that all three devices manifest typical gamma functions for voltage and luminance with warm up times of approximately 15 minutes. However, there were differences in homogeneity and reflectance among the displays. We suggest practical means to optimise quality of display for vision testing including screen calibration.

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.

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.

A computer-tailored intervention to promote informed decision making for prostate cancer screening among African American men.

Science.gov (United States)

Allen, Jennifer D; Mohllajee, Anshu P; Shelton, Rachel C; Drake, Bettina F; Mars, Dana R

2009-12-01

African American men experience a disproportionate burden of prostate cancer (CaP) morbidity and mortality. National screening guidelines advise men to make individualized screening decisions through a process termed informed decision making (IDM). In this pilot study, a computer-tailored decision-aid designed to promote IDM was evaluated using a pre-/posttest design. African American men aged 40 years and older were recruited from a variety of community settings (n = 108). At pretest, 43% of men reported having made a screening decision; at posttest 47% reported this to be the case (p = .39). Significant improvements were observed between pre- and posttest on scores of knowledge, decision self-efficacy, and decisional conflict. Men were also more likely to want an active role in decision making after using the tool. These results suggest that use of a computer-tailored decision aid is a promising strategy to promote IDM for CaP screening among African American men.

A computer-tailored intervention to promote informed decision making for prostate cancer screening among African-American men

Science.gov (United States)

Allen, Jennifer D.; Mohllajee, Anshu P.; Shelton, Rachel C.; Drake, Bettina F.; Mars, Dana R.

2010-01-01

African-American men experience a disproportionate burden of prostate cancer (CaP) morbidity and mortality. National screening guidelines advise men to make individualized screening decisions through a process termed “informed decision making” (IDM). In this pilot study, a computer-tailored decision-aid designed to promote IDM was evaluated using a pre/post test design. African-American men aged 40+ recruited from a variety of community settings (n=108). At pre-test, 43% of men reported having made a screening decision; at post-test 47% reported this to be the case (p=0.39). Significant improvements were observed on scores (0–100%) of knowledge (54% vs 72%; pMen were also more likely to want an active role in decision-making after using the tool (67% vs 75%; p=0.03). These results suggest that use of a computer-tailored decision-aid is a promising strategy to promote IDM for CaP screening among African-American men. PMID:19477736

Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

Directory of Open Access Journals (Sweden)

Mariusz Butkiewicz

2013-01-01

Full Text Available With the rapidly increasing availability of High-Throughput Screening (HTS data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR models are built using Artificial Neural Networks (ANNs, Support Vector Machines (SVMs, Decision Trees (DTs, and Kohonen networks (KNs. Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.

Noninvasive Computed Tomography-based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial.

Science.gov (United States)

Maldonado, Fabien; Duan, Fenghai; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Karwoski, Ronald A; Garg, Kavita; Greco, Erin; Nath, Hrudaya; Robb, Richard A; Bartholmai, Brian J; Peikert, Tobias

2015-09-15

Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.

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.

Computational and Experimental Approaches to Cancer Biomarker Discovery

DEFF Research Database (Denmark)

Krzystanek, Marcin

of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...... and the state or level of a large number of molecular entities is investigated. Such associative analysis could be confounded by several factors, leading to false discoveries. For example, it is assumed that with the exception of the true biomarkers most molecular entities such as gene expression levels show...... random distribution in a given cohort. However, gene expression levels may also be affected by technical bias when the actual measurement technology or sample handling may introduce a systematic error. If the distribution of systematic errors correlates with the biological phenotype then the risk...

A graph-based approach to construct target-focused libraries for virtual screening.

Science.gov (United States)

Naderi, Misagh; Alvin, Chris; Ding, Yun; Mukhopadhyay, Supratik; Brylinski, Michal

2016-01-01

Due to exorbitant costs of high-throughput screening, many drug discovery projects commonly employ inexpensive virtual screening to support experimental efforts. However, the vast majority of compounds in widely used screening libraries, such as the ZINC database, will have a very low probability to exhibit the desired bioactivity for a given protein. Although combinatorial chemistry methods can be used to augment existing compound libraries with novel drug-like compounds, the broad chemical space is often too large to be explored. Consequently, the trend in library design has shifted to produce screening collections specifically tailored to modulate the function of a particular target or a protein family. Assuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. On this account, we developed eSynth, an exhaustive graph-based search algorithm to computationally synthesize new compounds by reconnecting these building blocks following their connectivity patterns. We conducted a series of benchmarking calculations against the Directory of Useful Decoys, Enhanced database. First, in a self-benchmarking test, the correctness of the algorithm is validated with the objective to recover a molecule from its building blocks. Encouragingly, eSynth can efficiently rebuild more than 80 % of active molecules from their fragment components. Next, the capability to discover novel scaffolds is assessed in a cross-benchmarking test, where eSynth successfully reconstructed 40 % of the target molecules using fragments extracted from chemically distinct compounds. Despite an enormous chemical space to be explored, eSynth is computationally efficient; half of the molecules are rebuilt in less than a second, whereas 90 % take only about a minute to be generated. eSynth can successfully reconstruct chemically feasible molecules from molecular fragments

Screening_mgmt: a Python module for managing screening data.

Science.gov (United States)

Helfenstein, Andreas; Tammela, Päivi

2015-02-01

High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. © 2014 Society for Laboratory Automation and Screening.

Atrial Fibrillation Screening in Nonmetropolitan Areas Using a Telehealth Surveillance System With an Embedded Cloud-Computing Algorithm: Prospective Pilot Study.

Science.gov (United States)

Chen, Ying-Hsien; Hung, Chi-Sheng; Huang, Ching-Chang; Hung, Yu-Chien; Hwang, Juey-Jen; Ho, Yi-Lwun

2017-09-26

Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4%, 22/922) residents with AF were identified by the physician's ECG interpretation, and only 0.2% (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5% (95% CI 77.2%-99.9%) and specificity of 97.7% (95% CI 96.5%-98.5%). The overall satisfaction score for the process of AF screening was 92.1%. AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. ©Ying-Hsien Chen, Chi-Sheng Hung, Ching-Chang Huang, Yu-Chien Hung, Juey-Jen Hwang, Yi-Lwun Ho. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 26.09.2017.

Practical considerations and effects of metallic screen fluorescence and backscatter control in gamma computed radiography

International Nuclear Information System (INIS)

Mango, Steven

2016-01-01

It is a fairly common misconception that the role of metallic screens used with computed radiography is primarily that of scatter control, and that any amplification of the image signal is minimal. To the contrary, this paper shows how the physical interaction between gamma rays and front metallic screens can yield a significant boost in signal and whether that increased signal is, in fact, beneficial or detrimental to image quality. For rear metallic screens, this signal boost is differentiated from backscatter, and image quality considerations should be more carefully thought out because of the separation between the screen and the imaging layer provided by the imaging plate support. Various physical interactions are explained, and a series of practical experiments show the various changes in signal level and image quality with various thicknesses of lead and copper screens. Recommendations are made for the configuration of the imaging plate and screens for optimum image quality and for the control and monitoring of scatter.

Drug repurposing: translational pharmacology, chemistry, computers and the clinic.

Science.gov (United States)

Issa, Naiem T; Byers, Stephen W; Dakshanamurthy, Sivanesan

2013-01-01

The process of discovering a pharmacological compound that elicits a desired clinical effect with minimal side effects is a challenge. Prior to the advent of high-performance computing and large-scale screening technologies, drug discovery was largely a serendipitous endeavor, as in the case of thalidomide for erythema nodosum leprosum or cancer drugs in general derived from flora located in far-reaching geographic locations. More recently, de novo drug discovery has become a more rationalized process where drug-target-effect hypotheses are formulated on the basis of already known compounds/protein targets and their structures. Although this approach is hypothesis-driven, the actual success has been very low, contributing to the soaring costs of research and development as well as the diminished pharmaceutical pipeline in the United States. In this review, we discuss the evolution in computational pharmacology as the next generation of successful drug discovery and implementation in the clinic where high-performance computing (HPC) is used to generate and validate drug-target-effect hypotheses completely in silico. The use of HPC would decrease development time and errors while increasing productivity prior to in vitro, animal and human testing. We highlight approaches in chemoinformatics, bioinformatics as well as network biopharmacology to illustrate potential avenues from which to design clinically efficacious drugs. We further discuss the implications of combining these approaches into an integrative methodology for high-accuracy computational predictions within the context of drug repositioning for the efficient streamlining of currently approved drugs back into clinical trials for possible new indications.

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...

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.

Virtual Ligand Screening Using PL-PatchSurfer2, a Molecular Surface-Based Protein-Ligand Docking Method.

Science.gov (United States)

Shin, Woong-Hee; Kihara, Daisuke

2018-01-01

Virtual screening is a computational technique for predicting a potent binding compound for a receptor protein from a ligand library. It has been a widely used in the drug discovery field to reduce the efforts of medicinal chemists to find hit compounds by experiments.Here, we introduce our novel structure-based virtual screening program, PL-PatchSurfer, which uses molecular surface representation with the three-dimensional Zernike descriptors, which is an effective mathematical representation for identifying physicochemical complementarities between local surfaces of a target protein and a ligand. The advantage of the surface-patch description is its tolerance on a receptor and compound structure variation. PL-PatchSurfer2 achieves higher accuracy on apo form and computationally modeled receptor structures than conventional structure-based virtual screening programs. Thus, PL-PatchSurfer2 opens up an opportunity for targets that do not have their crystal structures. The program is provided as a stand-alone program at http://kiharalab.org/plps2 . We also provide files for two ligand libraries, ChEMBL and ZINC Drug-like.

ScreenCube: A 3D Printed System for Rapid and Cost-Effective Chemical Screening in Adult Zebrafish.

Science.gov (United States)

Monstad-Rios, Adrian T; Watson, Claire J; Kwon, Ronald Y

2018-02-01

Phenotype-based small molecule screens in zebrafish embryos and larvae have been successful in accelerating pathway and therapeutic discovery for diverse biological processes. Yet, the application of chemical screens to adult physiologies has been relatively limited due to additional demands on cost, space, and labor associated with screens in adult animals. In this study, we present a 3D printed system and methods for intermittent drug dosing that enable rapid and cost-effective chemical administration in adult zebrafish. Using prefilled screening plates, the system enables dosing of 96 fish in ∼3 min, with a 10-fold reduction in drug quantity compared to that used in previous chemical screens in adult zebrafish. We characterize water quality kinetics during immersion in the system and use these kinetics to rationally design intermittent dosing regimens that result in 100% fish survival. As a demonstration of system fidelity, we show the potential to identify two known chemical inhibitors of adult tail fin regeneration, cyclopamine and dorsomorphin. By developing methods for rapid and cost-effective chemical administration in adult zebrafish, this study expands the potential for small molecule discovery in postembryonic models of development, disease, and regeneration.

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....

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.

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

Science.gov (United States)

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

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.

Heuristic lipophilicity potential for computer-aided rational drug design: Optimizations of screening functions and parameters

Science.gov (United States)

Du, Qishi; Mezey, Paul G.

1998-09-01

In this research we test and compare three possible atom-basedscreening functions used in the heuristic molecular lipophilicity potential(HMLP). Screening function 1 is a power distance-dependent function, b_{{i}} /| {R_{{i}}- r} |^γ, screening function 2is an exponential distance-dependent function, biexp(-| {R_i- r} |/d_0 , and screening function 3 is aweighted distance-dependent function, {{sign}}( {b_i } ){{exp}}ξ ( {| {R_i- r} |/| {b_i } |} )For every screening function, the parameters (γ ,d0, and ξ are optimized using 41 common organic molecules of 4 types of compounds:aliphatic alcohols, aliphatic carboxylic acids, aliphatic amines, andaliphatic alkanes. The results of calculations show that screening function3 cannot give chemically reasonable results, however, both the powerscreening function and the exponential screening function give chemicallysatisfactory results. There are two notable differences between screeningfunctions 1 and 2. First, the exponential screening function has largervalues in the short distance than the power screening function, thereforemore influence from the nearest neighbors is involved using screeningfunction 2 than screening function 1. Second, the power screening functionhas larger values in the long distance than the exponential screeningfunction, therefore screening function 1 is effected by atoms at longdistance more than screening function 2. For screening function 1, thesuitable range of parameter d0 is 1.5 < d0 < 3.0, and d0 = 2.0 is recommended. HMLP developed in this researchprovides a potential tool for computer-aided three-dimensional drugdesign.

Noninvasive Computed Tomography–based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial

Science.gov (United States)

Maldonado, Fabien; Duan, Fenghai; Raghunath, Sushravya M.; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Garg, Kavita; Greco, Erin; Nath, Hrudaya; Robb, Richard A.; Bartholmai, Brian J.

2015-01-01

Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. Measurements and Main Results: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. Conclusions: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas. PMID:26052977

Computational screening of mixed metal halide ammines

DEFF Research Database (Denmark)

Jensen, Peter Bjerre; Lysgaard, Steen; Quaade, Ulrich

2013-01-01

Metal halide ammines, e.g. Mg(NH3)6Cl2 and Sr(NH3)8Cl2, can reversibly store ammonia, with high volumetric hydrogen storage capacities. The storage in the halide ammines is very safe, and the salts are therefore highly relevant as a carbon-free energy carrier in future transportation infrastructure...... selection. The GA is evolving from an initial (random) population and selecting those with highest fitness, a function based on e.g. stability, release temperature and storage capacity. The search space includes all alkaline, alkaline earth, 3d and 4d metals and the four lightest halides. In total...... the search spaces consists of millions combinations, which makes a GA ideal, to reduce the number of necessary calculations. We are screening for a one step release from either a hexa or octa ammine, and we have found promising candidates, which will be further investigated ? both computationally...

Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

Science.gov (United States)

Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

2013-01-01

An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

Advances in Chance Discovery : Extended Selection from International Workshops

CERN Document Server

Abe, Akinori

2013-01-01

Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making. Partially because the editors Ohsawa and Abe are teaching at schools of Engineering and of Literature with sharing the interest in chance discovery, this book reflects interdisciplinary aspects of progress: First, as an interdisciplinary melting pot of cognitive science, computational intelligence, data mining/visualization, collective intelligence, … etc, chance discovery came to reach new application domains e.g. health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc. Second, basic technologies and sciences including sensor technologies, medical sciences, communication technologies etc. joined this field and interacted with cognitive/computational scientists in workshops on chance discovery, to obtain breakthroughs by stimulating each other. Third, �...

Recommendations from the European Society of Thoracic Surgeons (ESTS) regarding computed tomography screening for lung cancer in Europe

DEFF Research Database (Denmark)

Pedersen, Jesper Holst; Rzyman, Witold; Veronesi, Giulia

2017-01-01

In order to provide recommendations regarding implementation of computed tomography (CT) screening in Europe the ESTS established a working group with eight experts in the field. On a background of the current situation regarding CT screening in Europe and the available evidence, ten recommendati...

[China National Lung Cancer Screening Guideline with Low-dose Computed 
Tomography (2018 version)].

Science.gov (United States)

Zhou, Qinghua; Fan, Yaguang; Wang, Ying; Qiao, Youlin; Wang, Guiqi; Huang, Yunchao; Wang, Xinyun; Wu, Ning; Zhang, Guozheng; Zheng, Xiangpeng; Bu, Hong; Li, Yin; Wei, Sen; Chen, Liang'an; Hu, Chengping; Shi, Yuankai; Sun, Yan

2018-02-20

Lung cancer is the leading cause of cancer-related death in China. The results from a randomized controlled trial using annual low-dose computed tomography (LDCT) in specific high-risk groups demonstrated a 20% reduction in lung cancer mortality. The aim of tihs study is to establish the China National lung cancer screening guidelines for clinical practice. The China lung cancer early detection and treatment expert group (CLCEDTEG) established the China National Lung Cancer Screening Guideline with multidisciplinary representation including 4 thoracic surgeons, 4 thoracic radiologists, 2 medical oncologists, 2 pulmonologists, 2 pathologist, and 2 epidemiologist. Members have engaged in interdisciplinary collaborations regarding lung cancer screening and clinical care of patients with at risk for lung cancer. The expert group reviewed the literature, including screening trials in the United States and Europe and China, and discussed local best clinical practices in the China. A consensus-based guidelines, China National Lung Cancer Screening Guideline (CNLCSG), was recommended by CLCEDTEG appointed by the National Health and Family Planning Commission, based on results of the National Lung Screening Trial, systematic review of evidence related to LDCT screening, and protocol of lung cancer screening program conducted in rural China. Annual lung cancer screening with LDCT is recommended for high risk individuals aged 50-74 years who have at least a 20 pack-year smoking history and who currently smoke or have quit within the past five years. Individualized decision making should be conducted before LDCT screening. LDCT screening also represents an opportunity to educate patients as to the health risks of smoking; thus, education should be integrated into the screening process in order to assist smoking cessation. A lung cancer screening guideline is recommended for the high-risk population in China. Additional research , including LDCT combined with biomarkers, is

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

From structure prediction to genomic screens for novel non-coding RNAs.

Science.gov (United States)

Gorodkin, Jan; Hofacker, Ivo L

2011-08-01

Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.

MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

International Nuclear Information System (INIS)

Yang, Xu; Lazar, Iulia M

2009-01-01

The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented. MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000. Preliminary experiments have

Modeling nanoscale gas sensors under realistic conditions: Computational screening of metal-doped carbon nanotubes

DEFF Research Database (Denmark)

García Lastra, Juan Maria; Mowbray, Duncan; Thygesen, Kristian Sommer

2010-01-01

We use computational screening to systematically investigate the use of transition-metal-doped carbon nanotubes for chemical-gas sensing. For a set of relevant target molecules (CO, NH3, and H2S) and the main components of air (N2, O2, and H2O), we calculate the binding energy and change in condu......We use computational screening to systematically investigate the use of transition-metal-doped carbon nanotubes for chemical-gas sensing. For a set of relevant target molecules (CO, NH3, and H2S) and the main components of air (N2, O2, and H2O), we calculate the binding energy and change...... the change in the nanotube resistance per doping site as a function of the target molecule concentration assuming charge transport in the diffusive regime. Our analysis points to Ni-doped nanotubes as candidates for CO sensors working under typical atmospheric conditions....

Evaluation of the potential benefit of computer-aided diagnosis (CAD) for lung cancer screening using photofluorography

International Nuclear Information System (INIS)

Matsumoto, Tsuneo; Nakamura, Hiroshi; Nakanishi, Takashi; Doi, Kunio; Kano, Akiko.

1993-01-01

To evaluate the potential benefit of computer-aided diagnosis (CAD) in lung cancer screenings using photofluorographic films, we performed an observer test with 12 radiologists. We used 60 photofluorographic films obtained from a lung cancer screening program in Yamaguchi Prefecture (30 contained cancerous nodules and 30 had no nodules). In these cases, our current automated detection scheme achieved a sensitivity of 80%, but yielded an average of 11 false-positives per image. The observer study consisted of three viewing conditions: 1) only the original image (single reading), 2) the original image and computer output obtained from the current CAD scheme (CAD 1), 3) the original image and computer output obtained from a simulated improved CAD scheme with the same 80% true-positive rate, but with an average of one false-positive per image (CAD 2). Compared with double reading using independent interpretations, which is based on a higher score between two single readings, CAD 2 was more sensitive in subtle cases. The specificity of CAD was superior to that of double reading. Although CAD 1 (Az=0.805) was inferior to double reading (Az=0.837) in terms of the ROC curve, CAD 2 (Az=0.872) significantly improved the ROC curve and also significantly reduced observation time (p<0.05). If the number of false positives can be reduced, computer-aided diagnosis may play an important role in lung cancer screening programs. (author)

GPU acceleration of Dock6's Amber scoring computation.

Science.gov (United States)

Yang, Hailong; Zhou, Qiongqiong; Li, Bo; Wang, Yongjian; Luan, Zhongzhi; Qian, Depei; Li, Hanlu

2010-01-01

Dressing the problem of virtual screening is a long-term goal in the drug discovery field, which if properly solved, can significantly shorten new drugs' R&D cycle. The scoring functionality that evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires a large amount of floating-point calculations, which usually takes several weeks or even months to be finished. This time-consuming procedure is unacceptable, especially when highly fatal and infectious virus arises such as SARS and H1N1, which forces the scoring task to be done in a limited time. This paper presents how to leverage the computational power of GPU to accelerate Dock6's (http://dock.compbio.ucsf.edu/DOCK_6/) Amber (J. Comput. Chem. 25: 1157-1174, 2004) scoring with NVIDIA CUDA (NVIDIA Corporation Technical Staff, Compute Unified Device Architecture - Programming Guide, NVIDIA Corporation, 2008) (Compute Unified Device Architecture) platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer, and divergence hidden. Our experiments show that the GPU-accelerated Amber scoring achieves a 6.5× speedup with respect to the original version running on AMD dual-core CPU for the same problem size. This acceleration makes the Amber scoring more competitive and efficient for large-scale virtual screening problems.

From computational discovery to experimental characterization of a high hole mobility organic crystal.

KAUST Repository

Sokolov, Anatoliy N

2011-08-16

For organic semiconductors to find ubiquitous electronics applications, the development of new materials with high mobility and air stability is critical. Despite the versatility of carbon, exploratory chemical synthesis in the vast chemical space can be hindered by synthetic and characterization difficulties. Here we show that in silico screening of novel derivatives of the dinaphtho[2,3-b:2\\',3\\'-f]thieno[3,2-b]thiophene semiconductor with high hole mobility and air stability can lead to the discovery of a new high-performance semiconductor. On the basis of estimates from the Marcus theory of charge transfer rates, we identified a novel compound expected to demonstrate a theoretic twofold improvement in mobility over the parent molecule. Synthetic and electrical characterization of the compound is reported with single-crystal field-effect transistors, showing a remarkable saturation and linear mobility of 12.3 and 16 cm(2) V(-1) s(-1), respectively. This is one of the very few organic semiconductors with mobility greater than 10 cm(2) V(-1) s(-1) reported to date.

Fragment-based approaches to the discovery of kinase inhibitors.

Science.gov (United States)

Mortenson, Paul N; Berdini, Valerio; O'Reilly, Marc

2014-01-01

Protein kinases are one of the most important families of drug targets, and aberrant kinase activity has been linked to a large number of disease areas. Although eminently targetable using small molecules, kinases present a number of challenges as drug targets, not least obtaining selectivity across such a large and relatively closely related target family. Fragment-based drug discovery involves screening simple, low-molecular weight compounds to generate initial hits against a target. These hits are then optimized to more potent compounds via medicinal chemistry, usually facilitated by structural biology. Here, we will present a number of recent examples of fragment-based approaches to the discovery of kinase inhibitors, detailing the construction of fragment-screening libraries, the identification and validation of fragment hits, and their optimization into potent and selective lead compounds. The advantages of fragment-based methodologies will be discussed, along with some of the challenges associated with using this route. Finally, we will present a number of key lessons derived both from our own experience running fragment screens against kinases and from a large number of published studies.

High-throughput screening for bioactive components from traditional Chinese medicine.

Science.gov (United States)

Zhu, Yanhui; Zhang, Zhiyun; Zhang, Meng; Mais, Dale E; Wang, Ming-Wei

2010-12-01

Throughout the centuries, traditional Chinese medicine has been a rich resource in the development of new drugs. Modern drug discovery, which relies increasingly on automated high throughput screening and quick hit-to-lead development, however, is confronted with the challenges of the chemical complexity associated with natural products. New technologies for biological screening as well as library building are in great demand in order to meet the requirements. Here we review the developments in these techniques under the perspective of their applicability in natural product drug discovery. Methods in library building, component characterizing, biological evaluation, and other screening methods including NMR and X-ray diffraction are discussed.

Community-Based Multidisciplinary Computed Tomography Screening Program Improves Lung Cancer Survival.

Science.gov (United States)

Miller, Daniel L; Mayfield, William R; Luu, Theresa D; Helms, Gerald A; Muster, Alan R; Beckler, Vickie J; Cann, Aaron

2016-05-01

Lung cancer is the most common cause of cancer deaths in the United States. Overall survival is less than 20%, with the majority of patients presenting with advanced disease. The National Lung Screening Trial, performed mainly in academic medical centers, showed that cancer mortality can be reduced with computed tomography (CT) screening compared with chest radiography in high-risk patients. To determine whether this survival advantage can be duplicated in a community-based multidisciplinary thoracic oncology program, we initiated a CT scan screening program for lung cancer within an established health care system. In 2008, we launched a lung cancer CT screening program within the WellStar Health System (WHS) consisting of five hospitals, three health parks, 140 outpatient medical offices, and 12 imaging centers that provide care in a five-county area of approximately 1.4 million people in Metro-Atlanta. Screening criteria incorporated were the International Early Lung Cancer Action Program (2008 to 2010) and National Comprehensive Cancer Network guidelines (2011 to 2013) for moderate- and high-risk patients. A total of 1,267 persons underwent CT lung cancer screening in WHS from 2008 through 2013; 53% were men, 87% were 50 years of age or older, and 83% were current or former smokers. Noncalcified indeterminate pulmonary nodules were found in 518 patients (41%). Thirty-six patients (2.8%) underwent a diagnostic procedure for positive findings on their CT scan; 30 proved to have cancer, 28 (2.2%) primary lung cancer and 2 metastatic cancer, and 6 had benign disease. Fourteen patients (50%) had their lung cancer discovered on their initial CT scan, 11 on subsequent scans associated with indeterminate pulmonary nodules growth and 3 patients who had a new indeterminate pulmonary nodules. Only 15 (54%) of these 28 patients would have qualified as a National Lung Screening Trial high-risk patient; 75% had stage I or II disease. Overall 5-year survival was 64% and 5-year

Quantum probability ranking principle for ligand-based virtual screening

Science.gov (United States)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening.

Science.gov (United States)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

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.

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).

Utility of screening computed tomography of chest, abdomen and pelvis in patients after heart transplantation

International Nuclear Information System (INIS)

Dasari, Tarun W.; Pavlovic-Surjancev, Biljana; Dusek, Linda; Patel, Nilamkumar; Heroux, Alain L.

2011-01-01

Introduction: Malignancy is a late cause of mortality in heart transplant recipients. It is unknown if screening computed tomography scan would lead to early detection of such malignancies or serious vascular anomalies post heart transplantation. Methods: This is a single center observational study of patients undergoing surveillance computed tomography of chest, abdomen and pelvis atleast 5 years after transplantation. Abnormal findings, included pulmonary nodules, lymphadenopathy and intra-thoracic and intra-abdominal masses and vascular anomalies such as abdominal aortic aneurysm. The clinical follow up of each of these major abnormal findings is summarized. Results: A total of 63 patients underwent computed tomography scan of chest, abdomen and pelvis at least 5 years after transplantation. Of these, 54 (86%) were male and 9 (14%) were female. Mean age was 52 ± 9.2 years. Computed tomography revealed 1 lung cancer (squamous cell) only. Non specific pulmonary nodules were seen in 6 patients (9.5%). The most common incidental finding was abdominal aortic aneurysms (N = 6 (9.5%)), which necessitated follow up computed tomography (N = 5) or surgery (N = 1). Mean time to detection of abdominal aortic aneurysms from transplantation was 14.6 ± 4.2 years. Mean age at the time of detection of abdominal aortic aneurysms was 74.5 ± 3.2 years. Conclusion: Screening computed tomography scan in patients 5 years from transplantation revealed only one malignancy but lead to increased detection of abdominal aortic aneurysms. Thus the utility is low in terms of detection of malignancy. Based on this study we do not recommend routine computed tomography post heart transplantation.

Resource utilization and costs during the initial years of lung cancer screening with computed tomography in Canada.

Science.gov (United States)

Cressman, Sonya; Lam, Stephen; Tammemagi, Martin C; Evans, William K; Leighl, Natasha B; Regier, Dean A; Bolbocean, Corneliu; Shepherd, Frances A; Tsao, Ming-Sound; Manos, Daria; Liu, Geoffrey; Atkar-Khattra, Sukhinder; Cromwell, Ian; Johnston, Michael R; Mayo, John R; McWilliams, Annette; Couture, Christian; English, John C; Goffin, John; Hwang, David M; Puksa, Serge; Roberts, Heidi; Tremblay, Alain; MacEachern, Paul; Burrowes, Paul; Bhatia, Rick; Finley, Richard J; Goss, Glenwood D; Nicholas, Garth; Seely, Jean M; Sekhon, Harmanjatinder S; Yee, John; Amjadi, Kayvan; Cutz, Jean-Claude; Ionescu, Diana N; Yasufuku, Kazuhiro; Martel, Simon; Soghrati, Kamyar; Sin, Don D; Tan, Wan C; Urbanski, Stefan; Xu, Zhaolin; Peacock, Stuart J

2014-10-01

It is estimated that millions of North Americans would qualify for lung cancer screening and that billions of dollars of national health expenditures would be required to support population-based computed tomography lung cancer screening programs. The decision to implement such programs should be informed by data on resource utilization and costs. Resource utilization data were collected prospectively from 2059 participants in the Pan-Canadian Early Detection of Lung Cancer Study using low-dose computed tomography (LDCT). Participants who had 2% or greater lung cancer risk over 3 years using a risk prediction tool were recruited from seven major cities across Canada. A cost analysis was conducted from the Canadian public payer's perspective for resources that were used for the screening and treatment of lung cancer in the initial years of the study. The average per-person cost for screening individuals with LDCT was $453 (95% confidence interval [CI], $400-$505) for the initial 18-months of screening following a baseline scan. The screening costs were highly dependent on the detected lung nodule size, presence of cancer, screening intervention, and the screening center. The mean per-person cost of treating lung cancer with curative surgery was $33,344 (95% CI, $31,553-$34,935) over 2 years. This was lower than the cost of treating advanced-stage lung cancer with chemotherapy, radiotherapy, or supportive care alone, ($47,792; 95% CI, $43,254-$52,200; p = 0.061). In the Pan-Canadian study, the average cost to screen individuals with a high risk for developing lung cancer using LDCT and the average initial cost of curative intent treatment were lower than the average per-person cost of treating advanced stage lung cancer which infrequently results in a cure.

Optimization of TRPV6 Calcium Channel Inhibitors Using a 3D Ligand-Based Virtual Screening Method.

OpenAIRE

Simonin Céline; Awale Mahendra; Brand Michael; van Deursen Ruud; Schwartz Julian; Fine Michael; Kovacs Gergely; Häfliger Pascal; Gyimesi Gergely; Sithampari Abilashan; Charles Roch-Philippe; Hediger Matthias A; Reymond Jean-Louis

2015-01-01

Herein we report the discovery of the first potent and selective inhibitor of TRPV6 a calcium channel overexpressed in breast and prostate cancer and its use to test the effect of blocking TRPV6 mediated Ca(2+) influx on cell growth. The inhibitor was discovered through a computational method xLOS a 3D shape and pharmacophore similarity algorithm a type of ligand based virtual screening (LBVS) method described briefly here. Starting with a single weakly active seed molecule two successive rou...

An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information

Science.gov (United States)

Melendez, Jaime; Sánchez, Clara I.; Philipsen, Rick H. H. M.; Maduskar, Pragnya; Dawson, Rodney; Theron, Grant; Dheda, Keertan; van Ginneken, Bram

2016-04-01

Lack of human resources and radiological interpretation expertise impair tuberculosis (TB) screening programmes in TB-endemic countries. Computer-aided detection (CAD) constitutes a viable alternative for chest radiograph (CXR) reading. However, no automated techniques that exploit the additional clinical information typically available during screening exist. To address this issue and optimally exploit this information, a machine learning-based combination framework is introduced. We have evaluated this framework on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa. Each record comprised a CAD score, automatically computed from a CXR, and 12 clinical features. Comparisons with strategies relying on either CAD scores or clinical information alone were performed. Our results indicate that the combination framework outperforms the individual strategies in terms of the area under the receiving operating characteristic curve (0.84 versus 0.78 and 0.72), specificity at 95% sensitivity (49% versus 24% and 31%) and negative predictive value (98% versus 95% and 96%). Thus, it is believed that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.

Virtual screening, SAR, and discovery of 5-(indole-3-yl)-2-[(2-nitrophenyl)amino] [1,3,4]-oxadiazole as a novel Bcl-2 inhibitor.

Science.gov (United States)

Ziedan, Noha I; Hamdy, Rania; Cavaliere, Alessandra; Kourti, Malamati; Prencipe, Filippo; Brancale, Andrea; Jones, Arwyn T; Westwell, Andrew D

2017-07-01

A new series of oxadiazoles were designed to act as inhibitors of the anti-apoptotic Bcl-2 protein. Virtual screening led to the discovery of new hits that interact with Bcl-2 at the BH3 binding pocket. Further study of the structure-activity relationship of the most active compound of the first series, compound 1, led to the discovery of a novel oxadiazole analogue, compound 16j, that was a more potent small-molecule inhibitor of Bcl-2. 16j had good in vitro inhibitory activity with submicromolar IC 50 values in a metastatic human breast cancer cell line (MDA-MB-231) and a human cervical cancer cell line (HeLa). The antitumour effect of 16j is concomitant with its ability to bind to Bcl-2 protein as shown by an enzyme-linked immunosorbent assay (IC 50  = 4.27 μm). Compound 16j has a great potential to develop into highly active anticancer agent. © 2017 John Wiley & Sons A/S.

Grid heterogeneity in in-silico experiments: an exploration of drug screening using DOCK on cloud environments.

Science.gov (United States)

Yim, Wen-Wai; Chien, Shu; Kusumoto, Yasuyuki; Date, Susumu; Haga, Jason

2010-01-01

Large-scale in-silico screening is a necessary part of drug discovery and Grid computing is one answer to this demand. A disadvantage of using Grid computing is the heterogeneous computational environments characteristic of a Grid. In our study, we have found that for the molecular docking simulation program DOCK, different clusters within a Grid organization can yield inconsistent results. Because DOCK in-silico virtual screening (VS) is currently used to help select chemical compounds to test with in-vitro experiments, such differences have little effect on the validity of using virtual screening before subsequent steps in the drug discovery process. However, it is difficult to predict whether the accumulation of these discrepancies over sequentially repeated VS experiments will significantly alter the results if VS is used as the primary means for identifying potential drugs. Moreover, such discrepancies may be unacceptable for other applications requiring more stringent thresholds. This highlights the need for establishing a more complete solution to provide the best scientific accuracy when executing an application across Grids. One possible solution to platform heterogeneity in DOCK performance explored in our study involved the use of virtual machines as a layer of abstraction. This study investigated the feasibility and practicality of using virtual machine and recent cloud computing technologies in a biological research application. We examined the differences and variations of DOCK VS variables, across a Grid environment composed of different clusters, with and without virtualization. The uniform computer environment provided by virtual machines eliminated inconsistent DOCK VS results caused by heterogeneous clusters, however, the execution time for the DOCK VS increased. In our particular experiments, overhead costs were found to be an average of 41% and 2% in execution time for two different clusters, while the actual magnitudes of the execution time

Changing the Scale and Efficiency of Chemical Warfare Countermeasure Discovery Using the Zebrafish

Science.gov (United States)

Peterson, Randall T.; MacRae, Calum A.

2013-01-01

As the scope of potential chemical warfare agents grows rapidly and as the diversity of potential threat scenarios expands with non-state actors, so a need for innovative approaches to countermeasure development has emerged. In the last few years, the utility of the zebrafish as a model organism that is amenable to high-throughput screening has become apparent and this system has been applied to the unbiased discovery of chemical warfare countermeasures. This review summarizes the in vivo screening approach that has been pioneered in the countermeasure discovery arena, and highlights the successes to date as well as the potential challenges in moving the field forward. Importantly, the establishment of a zebrafish platform for countermeasure discovery would offer a rapid response system for the development of antidotes to the continuous stream of new potential chemical warfare agents. PMID:24273586

China National Lung Cancer Screening Guideline with Low-dose Computed 
Tomography (2018 version

Directory of Open Access Journals (Sweden)

Qinghua ZHOU

2018-02-01

Full Text Available Background and objective Lung cancer is the leading cause of cancer-related death in China. The results from a randomized controlled trial using annual low-dose computed tomography (LDCT in specific high-risk groups demonstrated a 20% reduction in lung cancer mortality. The aim of tihs study is to establish the China National lung cancer screening guidelines for clinical practice. Methods The China lung cancer early detection and treatment expert group (CLCEDTEG established the China National Lung Cancer Screening Guideline with multidisciplinary representation including 4 thoracic surgeons, 4 thoracic radiologists, 2 medical oncologists, 2 pulmonologists, 2 pathologist, and 2 epidemiologist. Members have engaged in interdisciplinary collaborations regarding lung cancer screening and clinical care of patients with at risk for lung cancer. The expert group reviewed the literature, including screening trials in the United States and Europe and China, and discussed local best clinical practices in the China. A consensus-based guidelines, China National Lung Cancer Screening Guideline (CNLCSG, was recommended by CLCEDTEG appointed by the National Health and Family Planning Commission, based on results of the National Lung Screening Trial, systematic review of evidence related to LDCT screening, and protocol of lung cancer screening program conducted in rural China. Results Annual lung cancer screening with LDCT is recommended for high risk individuals aged 50-74 years who have at least a 20 pack-year smoking history and who currently smoke or have quit within the past five years. Individualized decision making should be conducted before LDCT screening. LDCT screening also represents an opportunity to educate patients as to the health risks of smoking; thus, education should be integrated into the screening process in order to assist smoking cessation. Conclusion A lung cancer screening guideline is recommended for the high-risk population in China

Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones.

Science.gov (United States)

Martins Alho, Miriam A; Marrero-Ponce, Yovani; Barigye, Stephen J; Meneses-Marcel, Alfredo; Machado Tugores, Yanetsy; Montero-Torres, Alina; Gómez-Barrio, Alicia; Nogal, Juan J; García-Sánchez, Rory N; Vega, María Celeste; Rolón, Miriam; Martínez-Fernández, Antonio R; Escario, José A; Pérez-Giménez, Facundo; Garcia-Domenech, Ramón; Rivera, Norma; Mondragón, Ricardo; Mondragón, Mónica; Ibarra-Velarde, Froylán; Lopez-Arencibia, Atteneri; Martín-Navarro, Carmen; Lorenzo-Morales, Jacob; Cabrera-Serra, Maria Gabriela; Piñero, Jose; Tytgat, Jan; Chicharro, Roberto; Arán, Vicente J

2014-03-01

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In an effort to overcome this problem, the main purpose of this study is to develop a QSARs-based ensemble classifier for antiprotozoan drug-like entities from a heterogeneous compounds collection. Here, we use some of the TOMOCOMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved. Firstly, we construct a wide-spectrum benchmark database comprising of 680 organic chemicals with great structural variability (254 of them antiprotozoan agents and 426 to drugs having other clinical uses). This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. In total, seven discriminant functions were obtained, by using the whole set of atom-based linear indices. All the LDA-based QSAR models show accuracies above 85% in the training set and values of Matthews correlation coefficients (C) vary from 0.70 to 0.86. The external validation set shows rather-good global classifications of around 80% (92.05% for best equation). Later, we developed a multi-agent QSAR classification system, in

Resource Discovery in Activity-Based Sensor Networks

DEFF Research Database (Denmark)

Bucur, Doina; Bardram, Jakob

This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

Computer Vision Tool and Technician as First Reader of Lung Cancer Screening CT Scans

NARCIS (Netherlands)

Ritchie, A.J.; Sanghera, C.; Jacobs, C.; Zhang, W.; Mayo, J.; Schmidt, H.; Gingras, M.; Pasian, S.; Stewart, L.; Tsai, S.; Manos, D.; Seely, J.M.; Burrowes, P.; Bhatia, R.; Atkar-Khattra, S.; Ginneken, B. van; Tammemagi, M.; Tsao, M.S.; Lam, S.; et al.,

2016-01-01

To implement a cost-effective low-dose computed tomography (LDCT) lung cancer screening program at the population level, accurate and efficient interpretation of a large volume of LDCT scans is needed. The objective of this study was to evaluate a workflow strategy to identify abnormal LDCT scans in

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.

In Silico Screening for Biothreat Countermeasures

National Research Council Canada - National Science Library

Westerhoff, Lance M

2006-01-01

The current state of the art of in silico drug discovery or computer aided drug discovery relies almost exclusively on molecular mechanics force fields, such as AMBER and CHARMM, and empirical potentials...

Using the iPlant collaborative discovery environment.

Science.gov (United States)

Oliver, Shannon L; Lenards, Andrew J; Barthelson, Roger A; Merchant, Nirav; McKay, Sheldon J

2013-06-01

The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.

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.

SNP Discovery In Marine Fish Species By 454 Sequencing

DEFF Research Database (Denmark)

Panitz, Frank; Nielsen, Rasmus Ory; van Houdt, Jeroen K J

2011-01-01

Based on the 454 Next-Generation-Sequencing technology (Roche) a high throughput screening method was devised in order to generate novel genetic markers (SNPs). SNP discovery was performed for three target species of marine fish: hake (Merluccius merluccius), herring (Clupea harengus) and sole...

Developing computer-based training programs for basic mammalian histology: Didactic versus discovery-based design

Science.gov (United States)

Fabian, Henry Joel

Educators have long tried to understand what stimulates students to learn. The Swiss psychologist and zoologist, Jean Claude Piaget, suggested that students are stimulated to learn when they attempt to resolve confusion. He reasoned that students try to explain the world with the knowledge they have acquired in life. When they find their own explanations to be inadequate to explain phenomena, students find themselves in a temporary state of confusion. This prompts students to seek more plausible explanations. At this point, students are primed for learning (Piaget 1964). The Piagetian approach described above is called learning by discovery. To promote discovery learning, a teacher must first allow the student to recognize his misconception and then provide a plausible explanation to replace that misconception (Chinn and Brewer 1993). One application of this method is found in the various learning cycles, which have been demonstrated to be effective means for teaching science (Renner and Lawson 1973, Lawson 1986, Marek and Methven 1991, and Glasson & Lalik 1993). In contrast to the learning cycle, tutorial computer programs are generally not designed to correct student misconceptions, but rather follow a passive, didactic method of teaching. In the didactic or expositional method, the student is told about a phenomenon, but is neither encouraged to explore it, nor explain it in his own terms (Schneider and Renner 1980).

A Comparison between Effect of Viewing Text on Computer Screen and iPad® on Visual Symptoms and Functions

Directory of Open Access Journals (Sweden)

Pittaya Phamonvaechavan

2017-07-01

Full Text Available Objective: To compare the ocular symptoms following sustained near vision between laptop computer and iPad®. Methods: Forty normal subjects read text from a laptop computer screen and an iPad® screen for a continuous 20 min period. Similar text was used in both sessions, which was matched for size and contrast. After finishing viewing text, subjects immediately completed a written questionnaire categorizing symptom scores into three groups: Dry eye, Pain and Blurred vision score. The accommodative amplitude and fusional convergence amplitude at near vision were also assessed before and after reading. Results: In both conditions, mean symptom scores were higher during iPad use. When comparing the computer and iPad conditions, mean scores were statistically significant different in Pain score (6.30 vs 8.70; p=0.025 and Blurred vision score (10.13 vs 12.03; p=0.041 but no statistically significant difference in Dry eye score (6.30 vs 6.60; p=0.71. There were significant change in accommodative amplitude and fusional convergence amplitude with near vision when compared before and after near-vision tasks in both cases. Conclusion: Pain and Blurred vision symptoms following sustained iPad use were significantly worse than those reported after computer use under similar viewing conditions. However, both computer screen and iPad cause ocular symptoms having an impact on quality of life.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

Science.gov (United States)

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

Computational science and re-discovery: open-source implementation of ellipsoidal harmonics for problems in potential theory

International Nuclear Information System (INIS)

Bardhan, Jaydeep P; Knepley, Matthew G

2012-01-01

We present two open-source (BSD) implementations of ellipsoidal harmonic expansions for solving problems of potential theory using separation of variables. Ellipsoidal harmonics are used surprisingly infrequently, considering their substantial value for problems ranging in scale from molecules to the entire solar system. In this paper, we suggest two possible reasons for the paucity relative to spherical harmonics. The first is essentially historical—ellipsoidal harmonics developed during the late 19th century and early 20th, when it was found that only the lowest-order harmonics are expressible in closed form. Each higher-order term requires the solution of an eigenvalue problem, and tedious manual computation seems to have discouraged applications and theoretical studies. The second explanation is practical: even with modern computers and accurate eigenvalue algorithms, expansions in ellipsoidal harmonics are significantly more challenging to compute than those in Cartesian or spherical coordinates. The present implementations reduce the 'barrier to entry' by providing an easy and free way for the community to begin using ellipsoidal harmonics in actual research. We demonstrate our implementation using the specific and physiologically crucial problem of how charged proteins interact with their environment, and ask: what other analytical tools await re-discovery in an era of inexpensive computation?

From structure prediction to genomic screens for novel non-coding RNAs.

Directory of Open Access Journals (Sweden)

Jan Gorodkin

2011-08-01

Full Text Available Non-coding RNAs (ncRNAs are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs. A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.

Cervical cancer screening at crossroads

DEFF Research Database (Denmark)

Lynge, Elsebeth; Rygaard, Carsten; Baillet, Miguel Vazquez-Prada

2014-01-01

Cervical screening has been one of the most successful public health prevention programmes. For 50 years, cytology formed the basis for screening, and detected cervical intraepithelial lesions (CIN) were treated surgically to prevent progression to cancer. In a high-risk country as Denmark......, screening decreased the incidence of cervical cancer from 34 to 11 per 100,000, age-standardized rate (World Standard Population). Screening is, however, also expensive; Denmark (population: 5.6 million) undertakes close to half a million tests per year, and has 6-8 CIN-treated women for each prevented...... cancer case. The discovery of human papillomavirus (HPV) as the cause of cervical cancer dramatically changed perspectives for disease control. Screening with HPV testing was launched around 1990, and preventive HPV vaccination was licensed in 2006. Long-term randomized controlled trials (RCT...

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.

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.

Evaluating Computer Screen Time and Its Possible Link to Psychopathology in the Context of Age: A Cross-Sectional Study of Parents and Children.

Science.gov (United States)

Segev, Aviv; Mimouni-Bloch, Aviva; Ross, Sharon; Silman, Zmira; Maoz, Hagai; Bloch, Yuval

2015-01-01

Several studies have suggested that high levels of computer use are linked to psychopathology. However, there is ambiguity about what should be considered normal or over-use of computers. Furthermore, the nature of the link between computer usage and psychopathology is controversial. The current study utilized the context of age to address these questions. Our hypothesis was that the context of age will be paramount for differentiating normal from excessive use, and that this context will allow a better understanding of the link to psychopathology. In a cross-sectional study, 185 parents and children aged 3-18 years were recruited in clinical and community settings. They were asked to fill out questionnaires regarding demographics, functional and academic variables, computer use as well as psychiatric screening questionnaires. Using a regression model, we identified 3 groups of normal-use, over-use and under-use and examined known factors as putative differentiators between the over-users and the other groups. After modeling computer screen time according to age, factors linked to over-use were: decreased socialization (OR 3.24, Confidence interval [CI] 1.23-8.55, p = 0.018), difficulty to disengage from the computer (OR 1.56, CI 1.07-2.28, p = 0.022) and age, though borderline-significant (OR 1.1 each year, CI 0.99-1.22, p = 0.058). While psychopathology was not linked to over-use, post-hoc analysis revealed that the link between increased computer screen time and psychopathology was age-dependent and solidified as age progressed (p = 0.007). Unlike computer usage, the use of small-screens and smartphones was not associated with psychopathology. The results suggest that computer screen time follows an age-based course. We conclude that differentiating normal from over-use as well as defining over-use as a possible marker for psychiatric difficulties must be performed within the context of age. If verified by additional studies, future research should integrate

Induced pluripotent stem cells for regenerative cardiovascular therapies and biomedical discovery.

Science.gov (United States)

Nsair, Ali; MacLellan, W Robb

2011-04-30

The discovery of induced pluripotent stem cells (iPSC) has, in the short time since their discovery, revolutionized the field of stem cell biology. This technology allows the generation of a virtually unlimited supply of cells with pluripotent potential similar to that of embryonic stem cells (ESC). However, in contrast to ESC, iPSC are not subject to the same ethical concerns and can be easily generated from living individuals. For the first time, patient-specific iPSC can be generated and offer a supply of genetically identical cells that can be differentiated into all somatic cell types for potential use in regenerative therapies or drug screening and testing. As the techniques for generation of iPSC lines are constantly evolving, new uses for human iPSC are emerging from in-vitro disease modeling to high throughput drug discovery and screening. This technology promises to revolutionize the field of medicine and offers new hope for understanding and treatment of numerous diseases. Copyright © 2011 Elsevier B.V. All rights reserved.

Virtual screening of electron acceptor materials for organic photovoltaic applications

International Nuclear Information System (INIS)

D Halls, Mathew; Giesen, David J; Goldberg, Alexander; Djurovich, Peter J; Sommer, Jonathan; McAnally, Eric; Thompson, Mark E

2013-01-01

Virtual screening involves the generation of structure libraries, automated analysis to predict properties related to application performance and subsequent screening to identify lead systems and estimate critical structure–property limits across a targeted chemical design space. This approach holds great promise for informing experimental discovery and development efforts for next-generation materials, such as organic semiconductors. In this work, the virtual screening approach is illustrated for nitrogen-substituted pentacene molecules to identify systems for development as electron acceptor materials for use in organic photovoltaic (OPV) devices. A structure library of tetra-azapentacenes (TAPs) was generated by substituting four nitrogens for CH at 12 sites on the pentacene molecular framework. Molecular properties (e.g. E LUMO , E g and μ) were computed for each candidate structure using hybrid DFT at the B3LYP/6-311G** level of theory. The resulting TAPs library was then analyzed with respect to intrinsic properties associated with OPV acceptor performance. Marcus reorganization energies for charge transport for the most favorable TAP candidates were then calculated to further determine suitability as OPV electron acceptors. The synthesis, characterization and OPV device testing of TAP materials is underway, guided by these results. (paper)

DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard; Allcock, William; Beggio, Chris; Campbell, Stuart; Cherry, Andrew; Cholia, Shreyas; Dart, Eli; England, Clay; Fahey, Tim; Foertter, Fernanda; Goldstone, Robin; Hick, Jason; Karelitz, David; Kelly, Kaki; Monroe, Laura; Prabhat,; Skinner, David; White, Julia

2014-10-17

U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at the DOE national laboratories. The report contains findings from that review.

Fighting obesity with a sugar-based library: discovery of novel MCH-1R antagonists by a new computational-VAST approach for exploration of GPCR binding sites.

Science.gov (United States)

Heifetz, Alexander; Barker, Oliver; Verquin, Geraldine; Wimmer, Norbert; Meutermans, Wim; Pal, Sandeep; Law, Richard J; Whittaker, Mark

2013-05-24

Obesity is an increasingly common disease. While antagonism of the melanin-concentrating hormone-1 receptor (MCH-1R) has been widely reported as a promising therapeutic avenue for obesity treatment, no MCH-1R antagonists have reached the market. Discovery and optimization of new chemical matter targeting MCH-1R is hindered by reduced HTS success rates and a lack of structural information about the MCH-1R binding site. X-ray crystallography and NMR, the major experimental sources of structural information, are very slow processes for membrane proteins and are not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of these methods to impact the drug discovery process for GPCR targets in "real-time", and hence, there is an urgent need for other practical and cost-efficient alternatives. We present here a conceptually pioneering approach that integrates GPCR modeling with design, synthesis, and screening of a diverse library of sugar-based compounds from the VAST technology (versatile assembly on stable templates) to provide structural insights on the MCH-1R binding site. This approach creates a cost-efficient new avenue for structure-based drug discovery (SBDD) against GPCR targets. In our work, a primary VAST hit was used to construct a high-quality MCH-1R model. Following model validation, a structure-based virtual screen yielded a 14% hit rate and 10 novel chemotypes of potent MCH-1R antagonists, including EOAI3367472 (IC50 = 131 nM) and EOAI3367474 (IC50 = 213 nM).

Development and initial testing of a computer-based patient decision aid to promote colorectal cancer screening for primary care practice

Directory of Open Access Journals (Sweden)

Fowler Beth

2005-11-01

Full Text Available Abstract Background Although colorectal cancer screening is recommended by major policy-making organizations, rates of screening remain low. Our aim was to develop a patient-directed, computer-based decision aid about colorectal cancer screening and investigate whether it could increase patient interest in screening. Methods We used content from evidence-based literature reviews and our previous decision aid research to develop a prototype. We performed two rounds of usability testing with representative patients to revise the content and format. The final decision aid consisted of an introductory segment, four test-specific segments, and information to allow comparison of the tests across several key parameters. We then conducted a before-after uncontrolled trial of 80 patients 50–75 years old recruited from an academic internal medicine practice. Results Mean viewing time was 19 minutes. The decision aid improved patients' intent to ask providers for screening from a mean score of 2.8 (1 = not at all likely to ask, 4 = very likely to ask before viewing the decision aid to 3.2 afterwards (difference, 0.4; p Conclusion We conclude that a computer-based decision aid can increase patient intent to be screened and increase interest in screening. Practice Implications: This decision aid can be viewed by patients prior to provider appointments to increase motivation to be screened and to help them decide about which modality to use for screening. Further work is required to integrate the decision aid with other practice change strategies to raise screening rates to target levels.

High content screening for G protein-coupled receptors using cell-based protein translocation assays

DEFF Research Database (Denmark)

Grånäs, Charlotta; Lundholt, Betina Kerstin; Heydorn, Arne

2005-01-01

G protein-coupled receptors (GPCRs) have been one of the most productive classes of drug targets for several decades, and new technologies for GPCR-based discovery promise to keep this field active for years to come. While molecular screens for GPCR receptor agonist- and antagonist-based drugs...... will continue to be valuable discovery tools, the most exciting developments in the field involve cell-based assays for GPCR function. Some cell-based discovery strategies, such as the use of beta-arrestin as a surrogate marker for GPCR function, have already been reduced to practice, and have been used...... as valuable discovery tools for several years. The application of high content cell-based screening to GPCR discovery has opened up additional possibilities, such as direct tracking of GPCRs, G proteins and other signaling pathway components using intracellular translocation assays. These assays provide...

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

Science.gov (United States)

Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Duvenaud, David; MacLaurin, Dougal; Blood-Forsythe, Martin A.; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P.; Aspuru-Guzik, Alán

2016-10-01

Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.

Scenario Educational Software: Design and Development of Discovery Learning.

Science.gov (United States)

Keegan, Mark

This book shows how and why the computer is so well suited to producing discovery learning environments. An examination of the literature outlines four basic modes of instruction: didactic, Socratic, inquiry, and discovery. Research from the fields of education, psychology, and physiology is presented to demonstrate the many strengths of…

Of minerals and men. [Discovery of new mineral species

Energy Technology Data Exchange (ETDEWEB)

De Waal, S.W. (Council for Mineral Technology, Randburg (South Africa))

1983-01-01

The rate of discovery of new mineral species appears to be on the increase in Southern Africa and classification and nomenclature, once haphazard, are now subject to international scientific screening and rules. Earlier names entrenched in the literature provide a fascinating background to the minerals scene.

Discovery and annotation of small proteins using genomics, proteomics and computational approaches

Energy Technology Data Exchange (ETDEWEB)

Yang, Xiaohan; Tschaplinski, Timothy J.; Hurst, Gregory B.; Jawdy, Sara; Abraham, Paul E.; Lankford, Patricia K.; Adams, Rachel M.; Shah, Manesh B.; Hettich, Robert L.; Lindquist, Erika; Kalluri, Udaya C.; Gunter, Lee E.; Pennacchio, Christa; Tuskan, Gerald A.

2011-03-02

Small proteins (10 200 amino acids aa in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained 2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts from the EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10 200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) codingpotential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene family clustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were new to the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.

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.

Performance of computer-aided detection in false-negative screening mammograms of breast cancers

International Nuclear Information System (INIS)

Han, Boo Kyung; Kim, Ji Young; Shin, Jung Hee; Choe, Yeon Hyeon

2004-01-01

To analyze retrospectively the abnormalities visible on the false-negative screening mammograms of patients with breast cancer and to determine the performance of computer-aided detection (CAD) in the detection of cancers. Of 108 consecutive cases of breast cancer diagnosed over a period of 6 years, of which previous screening mammograms were available, 32 retrospectively visible abnormalities (at which locations cancer later developed) were found in the previous mammograms, and which were originally reported as negative. These 32 patients ranged in age from 38 to 72 years (mean 52 years). We analyzed their previous mammographic findings, and assessed the ability of CAD to mark cancers in previous mammograms, according to the clinical presentation, the type of abnormalities and the mammographic parenchymal density. In these 32 previous mammograms of breast cancers (20 asymptomatic, 12 symptomatic), the retrospectively visible abnormalities were identified as densities in 22, calcifications in 8, and densities with calcifications in 2. CAD marked abnormalities in 20 (63%) of the 32 cancers with false-negative screening mammograms; 14 (70%) of the 20 subsequent screening-detected cancers, 5 (50%) of the 10 interval cancers, and 1 (50%) of the 2 cancers palpable after the screening interval. CAD marked 12 (50%) of the 24 densities and 9 (90%) of the 10 calcifications. CAD marked abnormalities in 7 (50%) of the 14 predominantly fatty breasts, and 13 (72%) of the 18 dense breasts. CAD-assisted diagnosis could potentially decrease the number of false-negative mammograms caused by the failure to recognize the cancer in the screening program, although its usefulness in the prevention of interval cancers appears to be limited

Discovery of selective inhibitors against EBNA1 via high throughput in silico virtual screening.

Directory of Open Access Journals (Sweden)

Ning Li

2010-04-01

Full Text Available Epstein-Barr Virus (EBV latent infection is associated with several human malignancies and is a causal agent of lymphoproliferative diseases during immunosuppression. While inhibitors of herpesvirus DNA polymerases, like gancyclovir, reduce EBV lytic cycle infection, these treatments have limited efficacy for treating latent infection. EBNA1 is an EBV-encoded DNA-binding protein required for viral genome maintenance during latent infection.Here, we report the identification of a new class of small molecules that inhibit EBNA1 DNA binding activity. These compounds were identified by virtual screening of 90,000 low molecular mass compounds using computational docking programs with the solved crystal structure of EBNA1. Four structurally related compounds were found to inhibit EBNA1-DNA binding in biochemical assays with purified EBNA1 protein. Compounds had a range of 20-100 microM inhibition of EBNA1 in fluorescence polarization assays and were further validated for inhibition using electrophoresis mobility shift assays. These compounds exhibited no significant inhibition of an unrelated DNA binding protein. Three of these compounds inhibited EBNA1 transcription activation function in cell-based assays and reduced EBV genome copy number when incubated with a Burkitt lymphoma cell line.These experiments provide a proof-of-principle that virtual screening can be used to identify specific inhibitors of EBNA1 that may have potential for treatment of EBV latent infection.

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.

Predicting future discoveries from current scientific literature.

Science.gov (United States)

Petrič, Ingrid; Cestnik, Bojan

2014-01-01

Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

Discovery Monday - Behind the plug: communication networks

CERN Multimedia

2004-01-01

Ever wondered what happens to your email when you click "send"? And when you make a phone call, how does your voice travel down the wire? Find out more about communication networks and their applications at the next Discovery Monday in Microcosm on 1 March. At CERN, networks are used for a multitude of reasons. Mobile phones, for example, are used in the laboratory's underground areas. Optical fibre cabling ensures that CERN's computers are connected to the rest of the world. But how do optical fibres work and what does the future have in store? CERN's experiments also need networks. Particle detectors are made of many layers, each relays complex information to a computer analysis centre which reconstitutes the passage of the particles resulting from collisions. Many billions of bytes are transmitted every second from a multitude of sources, to many computers.  No single computer can handle such a huge flow of information. The next Discovery Monday is your chance to find out how this works.  Participate i...

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description.

Science.gov (United States)

Spyrakis, Francesca; Cavasotto, Claudio N

2015-10-01

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical "structural" issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. Copyright © 2015 Elsevier Inc. All rights reserved.

Computer-Aided Solvent Screening for Biocatalysis

DEFF Research Database (Denmark)

Abildskov, Jens; Leeuwen, M.B. van; Boeriu, C.G.

2013-01-01

constrained properties related to chemical reaction equilibrium, substrate and product solubility, water solubility, boiling points, toxicity and others. Two examples are provided, covering the screening of solvents for lipase-catalyzed transesterification of octanol and inulin with vinyl laurate....... Esterification of acrylic acid with octanol is also addressed. Solvents are screened and candidates identified, confirming existing experimental results. Although the examples involve lipases, the method is quite general, so there seems to be no preclusion against application to other biocatalysts....

Drug discovery for Duchenne muscular dystrophy via utrophin promoter activation screening.

Directory of Open Access Journals (Sweden)

Catherine Moorwood

Full Text Available Duchenne muscular dystrophy (DMD is a devastating muscle wasting disease caused by mutations in dystrophin, a muscle cytoskeletal protein. Utrophin is a homologue of dystrophin that can functionally compensate for its absence when expressed at increased levels in the myofibre, as shown by studies in dystrophin-deficient mice. Utrophin upregulation is therefore a promising therapeutic approach for DMD. The use of a small, drug-like molecule to achieve utrophin upregulation offers obvious advantages in terms of delivery and bioavailability. Furthermore, much of the time and expense involved in the development of a new drug can be eliminated by screening molecules that are already approved for clinical use.We developed and validated a cell-based, high-throughput screening assay for utrophin promoter activation, and used it to screen the Prestwick Chemical Library of marketed drugs and natural compounds. Initial screening produced 20 hit molecules, 14 of which exhibited dose-dependent activation of the utrophin promoter and were confirmed as hits. Independent validation demonstrated that one of these compounds, nabumetone, is able to upregulate endogenous utrophin mRNA and protein, in C2C12 muscle cells.We have developed a cell-based, high-throughput screening utrophin promoter assay. Using this assay, we identified and validated a utrophin promoter-activating drug, nabumetone, for which pharmacokinetics and safety in humans are already well described, and which represents a lead compound for utrophin upregulation as a therapy for DMD.

Berkeley Lab Computing Sciences: Accelerating Scientific Discovery

International Nuclear Information System (INIS)

Hules, John A.

2008-01-01

Scientists today rely on advances in computer science, mathematics, and computational science, as well as large-scale computing and networking facilities, to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences organization researches, develops, and deploys new tools and technologies to meet these needs and to advance research in such areas as global climate change, combustion, fusion energy, nanotechnology, biology, and astrophysics

Physics in Screening Environments

Science.gov (United States)

Certik, Ondrej

In the current study, we investigated atoms in screening environments like plasmas. It is common practice to extract physical data, such as temperature and electron densities, from plasma experiments. We present results that address inherent computational difficulties that arise when the screening approach is extended to include the interaction between the atomic electrons. We show that there may arise an ambiguity in the interpretation of physical properties, such as temperature and charge density, from experimental data due to the opposing effects of electron-nucleus screening and electron-electron screening. The focus of the work, however, is on the resolution of inherent computational challenges that appear in the computation of two-particle matrix elements. Those enter already at the Hartree-Fock level. Furthermore, as examples of post Hartree-Fock calculations, we show second-order Green's function results and many body perturbation theory results of second order. A self-contained derivation of all necessary equations has been included. The accuracy of the implementation of the method is established by comparing standard unscreened results for various atoms and molecules against literature for Hartree-Fock as well as Green's function and many body perturbation theory. The main results of the thesis are presented in the chapter called Screened Results, where the behavior of several atomic systems depending on electron-electron and electron-nucleus Debye screening was studied. The computer code that we have developed has been made available for anybody to use. Finally, we present and discuss results obtained for screened interactions. We also examine thoroughly the computational details of the calculations and particular implementations of the method.

Binary Decision Trees for Preoperative Periapical Cyst Screening Using Cone-beam Computed Tomography.

Science.gov (United States)

Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa

2017-03-01

Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.

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

Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings

NARCIS (Netherlands)

Mordang, Jan-Jurre; Gubern-Merida, Albert; Bria, Alessandro; Tortorella, Francesco; den Heeten, Gerard; Karssemeijer, Nico

2017-01-01

Purpose: Computer-aided detection (CADe) systems for mammography screening still mark many false positives. This can cause radiologists to lose confidence in CADe, especially when many false positives are obviously not suspicious to them. In this study, we focus on obvious false positives generated

Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings

NARCIS (Netherlands)

Mordang, J.J.; Gubern Merida, A.; Bria, A.; Tortorella, F.; Heeten, G.; Karssemeijer, N.

2017-01-01

PURPOSE: Computer-aided detection (CADe) systems for mammography screening still mark many false positives. This can cause radiologists to lose confidence in CADe, especially when many false positives are obviously not suspicious to them. In this study, we focus on obvious false positives generated

The history of computed tomography

International Nuclear Information System (INIS)

Bull, J.

1980-01-01

New scientific discoveries are often made by the synthetising of other discoveries. Computed tomography is such an example. The three necessary elements were: 1/ the fact that certain simple crystals scintillate when exposed to X-rays, 2/ the advent of electronics and 3/ that of computers. The fact that X-rays cause crystals to scintillate was learnt very shortly after Roentgen's discovery, electronics and computers coming very much later. To put all these together and apply them to diagnostic radiology, and at the same time dismiss the concept so firmly ingrained in everyone's mind that an X-ray picture must be produced on photographic film, required a genius. (orig./VJ) [de

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

Science.gov (United States)

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

Free Energy-Based Virtual Screening and Optimization of RNase H Inhibitors of HIV-1 Reverse Transcriptase.

Science.gov (United States)

Zhang, Baofeng; D'Erasmo, Michael P; Murelli, Ryan P; Gallicchio, Emilio

2016-09-30

We report the results of a binding free energy-based virtual screening campaign of a library of 77 α-hydroxytropolone derivatives against the challenging RNase H active site of the reverse transcriptase (RT) enzyme of human immunodeficiency virus-1. Multiple protonation states, rotamer states, and binding modalities of each compound were individually evaluated. The work involved more than 300 individual absolute alchemical binding free energy parallel molecular dynamics calculations and over 1 million CPU hours on national computing clusters and a local campus computational grid. The thermodynamic and structural measures obtained in this work rationalize a series of characteristics of this system useful for guiding future synthetic and biochemical efforts. The free energy model identified key ligand-dependent entropic and conformational reorganization processes difficult to capture using standard docking and scoring approaches. Binding free energy-based optimization of the lead compounds emerging from the virtual screen has yielded four compounds with very favorable binding properties, which will be the subject of further experimental investigations. This work is one of the few reported applications of advanced-binding free energy models to large-scale virtual screening and optimization projects. It further demonstrates that, with suitable algorithms and automation, advanced-binding free energy models can have a useful role in early-stage drug-discovery programs.

Discovery of Cationic Polymers for Non-viral Gene Delivery using Combinatorial Approaches

Science.gov (United States)

Barua, Sutapa; Ramos, James; Potta, Thrimoorthy; Taylor, David; Huang, Huang-Chiao; Montanez, Gabriela; Rege, Kaushal

2015-01-01

Gene therapy is an attractive treatment option for diseases of genetic origin, including several cancers and cardiovascular diseases. While viruses are effective vectors for delivering exogenous genes to cells, concerns related to insertional mutagenesis, immunogenicity, lack of tropism, decay and high production costs necessitate the discovery of non-viral methods. Significant efforts have been focused on cationic polymers as non-viral alternatives for gene delivery. Recent studies have employed combinatorial syntheses and parallel screening methods for enhancing the efficacy of gene delivery, biocompatibility of the delivery vehicle, and overcoming cellular level barriers as they relate to polymer-mediated transgene uptake, transport, transcription, and expression. This review summarizes and discusses recent advances in combinatorial syntheses and parallel screening of cationic polymer libraries for the discovery of efficient and safe gene delivery systems. PMID:21843141

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.

Combinatorial materials synthesis and high-throughput screening: an integrated materials chip approach to mapping phase diagrams and discovery and optimization of functional materials.

Science.gov (United States)

Xiang, X D

Combinatorial materials synthesis methods and high-throughput evaluation techniques have been developed to accelerate the process of materials discovery and optimization and phase-diagram mapping. Analogous to integrated circuit chips, integrated materials chips containing thousands of discrete different compositions or continuous phase diagrams, often in the form of high-quality epitaxial thin films, can be fabricated and screened for interesting properties. Microspot x-ray method, various optical measurement techniques, and a novel evanescent microwave microscope have been used to characterize the structural, optical, magnetic, and electrical properties of samples on the materials chips. These techniques are routinely used to discover/optimize and map phase diagrams of ferroelectric, dielectric, optical, magnetic, and superconducting materials.

An eye movement study for identification of suitable font characters for presentation on a computer screen.

Science.gov (United States)

Banerjee, Jayeeta; Majumdar, Dhurjati; Majumdar, Deepti; Pal, Madhu Sudan

2010-06-01

We are experiencing a shifting of media: from the printed paper to the computer screen. This transition is modifying the process of how we read and understand a text. It is very difficult to conclude on suitability of font characters based upon subjective evaluation method only. Present study evaluates the effect of font type on human cognitive workload during perception of individual alphabets on a computer screen. Twenty six young subjects volunteered for this study. Here, subjects have been shown individual characters of different font types and their eye movements have been recorded. A binocular eye movement recorder was used for eye movement recording. The results showed that different eye movement parameters such as pupil diameter, number of fixations, fixation duration were less for font type Verdana. The present study recommends the use of font type Verdana for presentation of individual alphabets on various electronic displays in order to reduce cognitive workload.

Implementing a computer-assisted telephone interview (CATI) system to increase colorectal cancer screening: a process evaluation.

Science.gov (United States)

White, Mary Jo; Stark, Jennifer R; Luckmann, Roger; Rosal, Milagros C; Clemow, Lynn; Costanza, Mary E

2006-06-01

Computer-assisted telephone interviewing (CATI) systems used by telephone counselors (TCs) may be efficient mechanisms to counsel patients on cancer and recommended preventive screening tests in order to extend a primary care provider's reach to his/her patients. The implementation process of such a system for promoting colorectal (CRC) cancer screening using a computer-assisted telephone interview (CATI) system is reported in this paper. The process evaluation assessed three components of the intervention: message production, program implementation and audience reception. Of 1181 potentially eligible patients, 1025 (87%) patients were reached by the TCs and 725 of those patients (71%) were eligible to receive counseling. Five hundred eighty-two (80%) patients agreed to counseling. It is feasible to design and use CATI systems for prevention counseling of patients in primary care practices. CATI systems have the potential of being used as a referral service by primary care providers and health care organizations for patient education.

Value of three-dimensional computed tomography in screening cerebral aneurysms

Energy Technology Data Exchange (ETDEWEB)

Yamaguchi, Tamaki; Sugiura, Yusuke; Suzuki, Atsushi; Yamagata, Yoshitaka [Hyogo Medical Coll. (Japan)

1997-10-01

We performed three-dimensional computed tomography (3D-CT) in 6 patients of cerebral aneurysm. Prior cerebral angiography showed a total of 17 aneurysms. 3D-CT alone detected 10 cerebral aneurysm (59%). It was possible to identify aneurysms larger than 10 mm even when located near the circle of Willis. It was difficult to identify aneurysms when smaller than 7 mm regardless of their location. 3D-CT was of limited value in detecting cerebral aneurysms, particularly when located near the circle of Willis with complex vascular network. As cases of oculomotor palsy may be caused by lesions other than cerebral aneurysm, we advocate that 3D-CT be performed after magnetic resonance imaging (MRI) in screening cases of suspected cerebral aneurysm. (author)

A comparison of symptoms after viewing text on a computer screen and hardcopy.

Science.gov (United States)

Chu, Christina; Rosenfield, Mark; Portello, Joan K; Benzoni, Jaclyn A; Collier, Juanita D

2011-01-01

Computer vision syndrome (CVS) is a complex of eye and vision problems experienced during or related to computer use. Ocular symptoms may include asthenopia, accommodative and vergence difficulties and dry eye. CVS occurs in up to 90% of computer workers, and given the almost universal use of these devices, it is important to identify whether these symptoms are specific to computer operation, or are simply a manifestation of performing a sustained near-vision task. This study compared ocular symptoms immediately following a sustained near task. 30 young, visually-normal subjects read text aloud either from a desktop computer screen or a printed hardcopy page at a viewing distance of 50 cm for a continuous 20 min period. Identical text was used in the two sessions, which was matched for size and contrast. Target viewing angle and luminance were similar for the two conditions. Immediately following completion of the reading task, subjects completed a written questionnaire asking about their level of ocular discomfort during the task. When comparing the computer and hardcopy conditions, significant differences in median symptom scores were reported with regard to blurred vision during the task (t = 147.0; p = 0.03) and the mean symptom score (t = 102.5; p = 0.04). In both cases, symptoms were higher during computer use. Symptoms following sustained computer use were significantly worse than those reported after hard copy fixation under similar viewing conditions. A better understanding of the physiology underlying CVS is critical to allow more accurate diagnosis and treatment. This will allow practitioners to optimize visual comfort and efficiency during computer operation.

Discovery of pyridine-based agrochemicals by using Intermediate Derivatization Methods.

Science.gov (United States)

Guan, Ai-Ying; Liu, Chang-Ling; Sun, Xu-Feng; Xie, Yong; Wang, Ming-An

2016-02-01

Pyridine-based compounds have been playing a crucial role as agrochemicals or pesticides including fungicides, insecticides/acaricides and herbicides, etc. Since most of the agrochemicals listed in the Pesticide Manual were discovered through screening programs that relied on trial-and-error testing and new agrochemical discovery is not benefiting as much from the in silico new chemical compound identification/discovery techniques used in pharmaceutical research, it has become more important to find new methods to enhance the efficiency of discovering novel lead compounds in the agrochemical field to shorten the time of research phases in order to meet changing market requirements. In this review, we selected 18 representative known agrochemicals containing a pyridine moiety and extrapolate their discovery from the perspective of Intermediate Derivatization Methods in the hope that this approach will have greater appeal to researchers engaged in the discovery of agrochemicals and/or pharmaceuticals. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Adverse Effect Predictions Based on Computational Toxicology Techniques and Large-scale Databases].

Science.gov (United States)

Uesawa, Yoshihiro

2018-01-01

　Understanding the features of chemical structures related to the adverse effects of drugs is useful for identifying potential adverse effects of new drugs. This can be based on the limited information available from post-marketing surveillance, assessment of the potential toxicities of metabolites and illegal drugs with unclear characteristics, screening of lead compounds at the drug discovery stage, and identification of leads for the discovery of new pharmacological mechanisms. This present paper describes techniques used in computational toxicology to investigate the content of large-scale spontaneous report databases of adverse effects, and it is illustrated with examples. Furthermore, volcano plotting, a new visualization method for clarifying the relationships between drugs and adverse effects via comprehensive analyses, will be introduced. These analyses may produce a great amount of data that can be applied to drug repositioning.

Computer/Mobile Device Screen Time of Children and Their Eye Care Behavior: The Roles of Risk Perception and Parenting.

Science.gov (United States)

Chang, Fong-Ching; Chiu, Chiung-Hui; Chen, Ping-Hung; Miao, Nae-Fang; Chiang, Jeng-Tung; Chuang, Hung-Yi

2018-03-01

This study assessed the computer/mobile device screen time and eye care behavior of children and examined the roles of risk perception and parental practices. Data were obtained from a sample of 2,454 child-parent dyads recruited from 30 primary schools in Taipei city and New Taipei city, Taiwan, in 2016. Self-administered questionnaires were collected from students and parents. Fifth-grade students spend more time on new media (computer/smartphone/tablet: 16 hours a week) than on traditional media (television: 10 hours a week). The average daily screen time (3.5 hours) for these children exceeded the American Academy of Pediatrics recommendations (≤2 hours). Multivariate analysis results showed that after controlling for demographic factors, the parents with higher levels of risk perception and parental efficacy were more likely to mediate their child's eye care behavior. Children who reported lower academic performance, who were from non-intact families, reported lower levels of risk perception of mobile device use, had parents who spent more time using computers and mobile devices, and had lower levels of parental mediation were more likely to spend more time using computers and mobile devices; whereas children who reported higher academic performance, higher levels of risk perception, and higher levels of parental mediation were more likely to engage in higher levels of eye care behavior. Risk perception by children and parental practices are associated with the amount of screen time that children regularly engage in and their level of eye care behavior.

Discovery and study of novel protein tyrosine phosphatase 1B inhibitors

Science.gov (United States)

Zhang, Qian; Chen, Xi; Feng, Changgen

2017-10-01

Protein tyrosine phosphatase 1B (PTP1B) is considered to be a target for therapy of type II diabetes and obesity. So it is of great significance to take advantage of a computer aided drug design protocol involving the structured-based virtual screening with docking simulations for fast searching small molecule PTP1B inhibitors. Based on optimized complex structure of PTP1B bound with specific inhibitor of IX1, structured-based virtual screening against a library of natural products containing 35308 molecules, which was constructed based on Traditional Chinese Medicine database@ Taiwan (TCM database@ Taiwan), was conducted to determine the occurrence of PTP1B inhibitors using the Lubbock module and CDOCKER module from Discovery Studio 3.1 software package. The results were further filtered by predictive ADME simulation and predictive toxic simulation. As a result, 2 good drug-like molecules, namely para-benzoquinone compound 1 and Clavepictine analogue 2 were identified ultimately with the dock score of original inhibitor (IX1) and the receptor as a threshold. Binding model analyses revealed that these two candidate compounds have good interactions with PTP1B. The PTP1B inhibitory activity of compound 2 hasn't been reported before. The optimized compound 2 has higher scores and deserves further study.

Density functional theory based screening of ternary alkali-transition metal borohydrides: A computational material design project

DEFF Research Database (Denmark)

Hummelshøj, Jens Strabo; Landis, David; Voss, Johannes

2009-01-01

We present a computational screening study of ternary metal borohydrides for reversible hydrogen storage based on density functional theory. We investigate the stability and decomposition of alloys containing 1 alkali metal atom, Li, Na, or K (M1); and 1 alkali, alkaline earth or 3d/4d transition...

[Patient's Autonomy and Information in Psycho-Oncology: Computer Based Distress Screening for an Interactive Treatment Planning (ePOS-react)].

Science.gov (United States)

Schäffeler, Norbert; Sedelmaier, Jana; Möhrer, Hannah; Ziser, Katrin; Ringwald, Johanna; Wickert, Martin; Brucker, Sara; Junne, Florian; Zipfel, Stephan; Teufel, Martin

2017-07-01

To identify distressed patients in oncology using screening questionnaires is quite challenging in clinical routine. Up to now there is no evidence based recommendation which instrument is most suitable and how to put a screening to practice. Using computer based screening tools offers the possibility to automatically analyse patient's data, inform psycho-oncological and medical staff about the results, and use reactive questionnaires. Studies on how to empower patients in decision making in psycho-oncology are rare.Methods Women with breast and gynaecological cancer have been consecutively included in this study (n=103) at time of inpatient surgical treatment in a gynaecological clinic. They answered the computer based screening questionnaire (ePOS-react) for routine distress screening at time of admission. At the end of the tool an individual recommendation concerning psycho-oncological treatment is given ( i) psycho-oncological counselling, ii) brief psycho-oncological contact, iii) no treatment suggestion). The informed patients could choose autonomously either the recommended treatment or an individually more favoured alternative possibility. Additionally, a clinical interview (approx. 30 min) based on the "Psychoonkologische Basisdiagnostik (PO-Bado)" has been carried out for a third-party assessment of patients' need for treatment.Results 68.9% followed the treatment recommendation. 22.3% asked for a more "intense" (e. g. counselling instead of recommended brief contact) and 8,7% for a "less intense" intervention than recommended. The accordance of third-party assessment (clinical interview "PO-Bado") and treatment recommendation is about 72.8%. The accordance of third-party assessment and patient's choice (ePOS-react) is about 58.3%. The latter is smaller because 29.1% asked for a brief psycho-oncological contact for whom from the third-party assessment's perspective no indication for treatment has been existent.Discussion A direct response of the

Computer aided drug discovery of highly ligand efficient, low molecular weight imidazopyridine analogs as FLT3 inhibitors.

Science.gov (United States)

Frett, Brendan; McConnell, Nick; Smith, Catherine C; Wang, Yuanxiang; Shah, Neil P; Li, Hong-yu

2015-04-13

The FLT3 kinase represents an attractive target to effectively treat AML. Unfortunately, no FLT3 targeted therapeutic is currently approved. In line with our continued interests in treating kinase related disease for anti-FLT3 mutant activity, we utilized pioneering synthetic methodology in combination with computer aided drug discovery and identified low molecular weight, highly ligand efficient, FLT3 kinase inhibitors. Compounds were analyzed for biochemical inhibition, their ability to selectively inhibit cell proliferation, for FLT3 mutant activity, and preliminary aqueous solubility. Validated hits were discovered that can serve as starting platforms for lead candidates. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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.

Intelligent Screening Systems for Cervical Cancer

Directory of Open Access Journals (Sweden)

Yessi Jusman

2014-01-01

Full Text Available Advent of medical image digitalization leads to image processing and computer-aided diagnosis systems in numerous clinical applications. These technologies could be used to automatically diagnose patient or serve as second opinion to pathologists. This paper briefly reviews cervical screening techniques, advantages, and disadvantages. The digital data of the screening techniques are used as data for the computer screening system as replaced in the expert analysis. Four stages of the computer system are enhancement, features extraction, feature selection, and classification reviewed in detail. The computer system based on cytology data and electromagnetic spectra data achieved better accuracy than other data.

Fragment informatics and computational fragment-based drug design: an overview and update.

Science.gov (United States)

Sheng, Chunquan; Zhang, Wannian

2013-05-01

Fragment-based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment-based cheminformatics tools, high-throughput fragment docking, and fragment-based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research. © 2012 Wiley Periodicals, Inc.

Exploring Natural Products from the Biodiversity of Pakistan for Computational Drug Discovery Studies: Collection, Optimization, Design and Development of A Chemical Database (ChemDP).

Science.gov (United States)

Mirza, Shaher Bano; Bokhari, Habib; Fatmi, Muhammad Qaiser

2015-01-01

Pakistan possesses a rich and vast source of natural products (NPs). Some of these secondary metabolites have been identified as potent therapeutic agents. However, the medicinal usage of most of these compounds has not yet been fully explored. The discoveries for new scaffolds of NPs as inhibitors of certain enzymes or receptors using advanced computational drug discovery approaches are also limited due to the unavailability of accurate 3D structures of NPs. An organized database incorporating all relevant information, therefore, can facilitate to explore the medicinal importance of the metabolites from Pakistani Biodiversity. The Chemical Database of Pakistan (ChemDP; release 01) is a fully-referenced, evolving, web-based, virtual database which has been designed and developed to introduce natural products (NPs) and their derivatives from the biodiversity of Pakistan to Global scientific communities. The prime aim is to provide quality structures of compounds with relevant information for computer-aided drug discovery studies. For this purpose, over 1000 NPs have been identified from more than 400 published articles, for which 2D and 3D molecular structures have been generated with a special focus on their stereochemistry, where applicable. The PM7 semiempirical quantum chemistry method has been used to energy optimize the 3D structure of NPs. The 2D and 3D structures can be downloaded as .sdf, .mol, .sybyl, .mol2, and .pdb files - readable formats by many chemoinformatics/bioinformatics software packages. Each entry in ChemDP contains over 100 data fields representing various molecular, biological, physico-chemical and pharmacological properties, which have been properly documented in the database for end users. These pieces of information have been either manually extracted from the literatures or computationally calculated using various computational tools. Cross referencing to a major data repository i.e. ChemSpider has been made available for overlapping

Physicochemical Profiles of the Marketed Agrochemicals and Clues for Agrochemical Lead Discovery and Screening Library Development.

Science.gov (United States)

Rao, Hanbing; Huangfu, Changxin; Wang, Yanying; Wang, Xianxiang; Tang, Tiansheng; Zeng, Xianyin; Li, Zerong; Chen, Yuzong

2015-05-01

Combinatorial chemistry, high-throughput and virtual screening technologies have been extensively used for discovering agrochemical leads from chemical libraries. The knowledge of the physicochemical properties of the marketed agrochemicals is useful for guiding the design and selection of such libraries. Since the earlier profiling of marketed agrochemicals, the number and types of marketed agrochemicals have significantly increased. Recent studies have shown the change of some physicochemical properties of oral drugs with time. There is a need to also profile the physicochemical properties of the marketed agrochemicals. In this work, we analyzed the key physicochemical properties of 1751 marketed agrochemicals in comparison with the previously-analyzed herbicides and insecticides, 106 391 natural products and 57 548 diverse synthetic libraries compounds. Our study revealed the distribution profiles and evolution trend of different types of agrochemicals that in many respects are broadly similar to the reported profiles for oral drugs, with the most marked difference being that agrochemicals have a lower number of hydrogen bond donors. The derived distribution patterns provided the rule of thumb guidelines for selecting potential agrochemical leads and also provided clues for further improving the libraries for agrochemical lead discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drug and bioactive molecule screening based on a bioelectrical impedance cell culture platform

Directory of Open Access Journals (Sweden)

Ramasamy S

2014-12-01

Full Text Available Sakthivel Ramasamy,1 Devasier Bennet,1 Sanghyo Kim1,2 1Department of Bionanotechnology, Gachon University, Gyeonggi-Do, Republic of Korea; 2Graduate Gachon Medical Research Institute, Gil Medical Center, Incheon, Republic of Korea Abstract: This review will present a brief discussion on the recent advancements of bioelectrical impedance cell-based biosensors, especially the electric cell-substrate impedance sensing (ECIS system for screening of various bioactive molecules. The different technical integrations of various chip types, working principles, measurement systems, and applications for drug targeting of molecules in cells are highlighted in this paper. Screening of bioactive molecules based on electric cell-substrate impedance sensing is a trial-and-error process toward the development of therapeutically active agents for drug discovery and therapeutics. In general, bioactive molecule screening can be used to identify active molecular targets for various diseases and toxicity at the cellular level with nanoscale resolution. In the innovation and screening of new drugs or bioactive molecules, the activeness, the efficacy of the compound, and safety in biological systems are the main concerns on which determination of drug candidates is based. Further, drug discovery and screening of compounds are often performed in cell-based test systems in order to reduce costs and save time. Moreover, this system can provide more relevant results in in vivo studies, as well as high-throughput drug screening for various diseases during the early stages of drug discovery. Recently, MEMS technologies and integration with image detection techniques have been employed successfully. These new technologies and their possible ongoing transformations are addressed. Select reports are outlined, and not all the work that has been performed in the field of drug screening and development is covered. Keywords: screening of bioactive agents, impedance-based cell

Feedback-Driven Dynamic Invariant Discovery

Science.gov (United States)

Zhang, Lingming; Yang, Guowei; Rungta, Neha S.; Person, Suzette; Khurshid, Sarfraz

2014-01-01

Program invariants can help software developers identify program properties that must be preserved as the software evolves, however, formulating correct invariants can be challenging. In this work, we introduce iDiscovery, a technique which leverages symbolic execution to improve the quality of dynamically discovered invariants computed by Daikon. Candidate invariants generated by Daikon are synthesized into assertions and instrumented onto the program. The instrumented code is executed symbolically to generate new test cases that are fed back to Daikon to help further re ne the set of candidate invariants. This feedback loop is executed until a x-point is reached. To mitigate the cost of symbolic execution, we present optimizations to prune the symbolic state space and to reduce the complexity of the generated path conditions. We also leverage recent advances in constraint solution reuse techniques to avoid computing results for the same constraints across iterations. Experimental results show that iDiscovery converges to a set of higher quality invariants compared to the initial set of candidate invariants in a small number of iterations.

Anthelmintics: From discovery to resistance II (San Diego, 2016

Directory of Open Access Journals (Sweden)

Richard J. Martin

2016-12-01

Full Text Available The second scientific meeting in the series: “Anthelmintics: From Discovery to Resistance” was held in San Diego in February, 2016. The focus topics of the meeting, related to anthelmintic discovery and resistance, were novel technologies, bioinformatics, commercial interests, anthelmintic modes of action and anthelmintic resistance. Basic scientific, human and veterinary interests were addressed in oral and poster presentations. The delegates were from universities and industries in the US, Europe, Australia and New Zealand. The papers were a great representation of the field, and included the use of C. elegans for lead discovery, mechanisms of anthelmintic resistance, nematode neuropeptides, proteases, B. thuringiensis crystal protein, nicotinic receptors, emodepside, benzimidazoles, P-glycoproteins, natural products, microfluidic techniques and bioinformatics approaches. The NIH also presented NIAID-specific parasite genomic priorities and initiatives. From these papers we introduce below selected papers with a focus on anthelmintic drug screening and development.

Feasibility of a computer-delivered driver safety behavior screening and intervention program initiated during an emergency department visit.

Science.gov (United States)

Murphy, Mary; Smith, Lucia; Palma, Anton; Lounsbury, David; Bijur, Polly; Chambers, Paul; Gallagher, E John

2013-01-01

Injuries from motor vehicle crashes are a significant public health problem. The emergency department (ED) provides a setting that may be used to screen for behaviors that increase risk for motor vehicle crashes and provide brief interventions to people who might otherwise not have access to screening and intervention. The purpose of the present study was to (1) assess the feasibility of using a computer-assisted screening program to educate ED patients about risky driving behaviors, (2) evaluate patient acceptance of the computer-based traffic safety educational intervention during an ED visit, and (3) assess postintervention changes in risky driving behaviors. Pre/posteducational intervention involving medically stable adult ED patients in a large urban academic ED serving over 100,000 patients annually. Patients completed a self-administered, computer-based program that queried patients on risky driving behaviors (texting, talking, and other forms of distracted driving) and alcohol use. The computer provided patients with educational information on the dangers of these behaviors and data were collected on patient satisfaction with the program. Staff called patients 1 month post-ED visit for a repeat query. One hundred forty-nine patients participated, and 111 completed 1-month follow up (75%); the mean age was 39 (range: 21-70), 59 percent were Hispanic, and 52 percent were male. Ninety-seven percent of patients reported that the program was easy to use and that they were comfortable receiving this education via computer during their ED visit. All driving behaviors significantly decreased in comparison to baseline with the following reductions reported: talking on the phone, 30 percent; aggressive driving, 30 percent; texting while driving, 19 percent; drowsy driving, 16 percent; driving while multitasking, 12 percent; and drinking and driving, 9 percent. Overall, patients were very satisfied receiving educational information about these behaviors via computer

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

Children's accuracy of portion size estimation using digital food images: effects of interface design and size of image on computer screen.

Science.gov (United States)

Baranowski, Tom; Baranowski, Janice C; Watson, Kathleen B; Martin, Shelby; Beltran, Alicia; Islam, Noemi; Dadabhoy, Hafza; Adame, Su-heyla; Cullen, Karen; Thompson, Debbe; Buday, Richard; Subar, Amy

2011-03-01

To test the effect of image size and presence of size cues on the accuracy of portion size estimation by children. Children were randomly assigned to seeing images with or without food size cues (utensils and checked tablecloth) and were presented with sixteen food models (foods commonly eaten by children) in varying portion sizes, one at a time. They estimated each food model's portion size by selecting a digital food image. The same food images were presented in two ways: (i) as small, graduated portion size images all on one screen or (ii) by scrolling across large, graduated portion size images, one per sequential screen. Laboratory-based with computer and food models. Volunteer multi-ethnic sample of 120 children, equally distributed by gender and ages (8 to 13 years) in 2008-2009. Average percentage of correctly classified foods was 60·3 %. There were no differences in accuracy by any design factor or demographic characteristic. Multiple small pictures on the screen at once took half the time to estimate portion size compared with scrolling through large pictures. Larger pictures had more overestimation of size. Multiple images of successively larger portion sizes of a food on one computer screen facilitated quicker portion size responses with no decrease in accuracy. This is the method of choice for portion size estimation on a computer.

Novel Data Mining Methods for Virtual Screening of Biological Active Chemical Compounds

KAUST Repository

Soufan, Othman M.

2016-11-23

Drug discovery is a process that takes many years and hundreds of millions of dollars to reveal a confident conclusion about a specific treatment. Part of this sophisticated process is based on preliminary investigations to suggest a set of chemical compounds as candidate drugs for the treatment. Computational resources have been playing a significant role in this part through a step known as virtual screening. From a data mining perspective, availability of rich data resources is key in training prediction models. Yet, the difficulties imposed by big expansion in data and its dimensionality are inevitable. In this thesis, I address the main challenges that come when data mining techniques are used for virtual screening. In order to achieve an efficient virtual screening using data mining, I start by addressing the problem of feature selection and provide analysis of best ways to describe a chemical compound for an enhanced screening performance. High-throughput screening (HTS) assays data used for virtual screening are characterized by a great class imbalance. To handle this problem of class imbalance, I suggest using a novel algorithm called DRAMOTE to narrow down promising candidate chemicals aimed at interaction with specific molecular targets before they are experimentally evaluated. Existing works are mostly proposed for small-scale virtual screening based on making use of few thousands of interactions. Thus, I propose enabling large-scale (or big) virtual screening through learning millions of interaction while exploiting any relevant dependency for a better accuracy. A novel solution called DRABAL that incorporates structure learning of a Bayesian Network as a step to model dependency between the HTS assays, is showed to achieve significant improvements over existing state-of-the-art approaches.

Applications of ambient mass spectrometry in high-throughput screening.

Science.gov (United States)

Li, Li-Ping; Feng, Bao-Sheng; Yang, Jian-Wang; Chang, Cui-Lan; Bai, Yu; Liu, Hu-Wei

2013-06-07

The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

Network-based approaches to climate knowledge discovery

Science.gov (United States)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

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.

Automated Cervical Screening and Triage, Based on HPV Testing and Computer-Interpreted Cytology.

Science.gov (United States)

Yu, Kai; Hyun, Noorie; Fetterman, Barbara; Lorey, Thomas; Raine-Bennett, Tina R; Zhang, Han; Stamps, Robin E; Poitras, Nancy E; Wheeler, William; Befano, Brian; Gage, Julia C; Castle, Philip E; Wentzensen, Nicolas; Schiffman, Mark

2018-04-11

State-of-the-art cervical cancer prevention includes human papillomavirus (HPV) vaccination among adolescents and screening/treatment of cervical precancer (CIN3/AIS and, less strictly, CIN2) among adults. HPV testing provides sensitive detection of precancer but, to reduce overtreatment, secondary "triage" is needed to predict women at highest risk. Those with the highest-risk HPV types or abnormal cytology are commonly referred to colposcopy; however, expert cytology services are critically lacking in many regions. To permit completely automatable cervical screening/triage, we designed and validated a novel triage method, a cytologic risk score algorithm based on computer-scanned liquid-based slide features (FocalPoint, BD, Burlington, NC). We compared it with abnormal cytology in predicting precancer among 1839 women testing HPV positive (HC2, Qiagen, Germantown, MD) in 2010 at Kaiser Permanente Northern California (KPNC). Precancer outcomes were ascertained by record linkage. As additional validation, we compared the algorithm prospectively with cytology results among 243 807 women screened at KPNC (2016-2017). All statistical tests were two-sided. Among HPV-positive women, the algorithm matched the triage performance of abnormal cytology. Combined with HPV16/18/45 typing (Onclarity, BD, Sparks, MD), the automatable strategy referred 91.7% of HPV-positive CIN3/AIS cases to immediate colposcopy while deferring 38.4% of all HPV-positive women to one-year retesting (compared with 89.1% and 37.4%, respectively, for typing and cytology triage). In the 2016-2017 validation, the predicted risk scores strongly correlated with cytology (P < .001). High-quality cervical screening and triage performance is achievable using this completely automated approach. Automated technology could permit extension of high-quality cervical screening/triage coverage to currently underserved regions.

The discovery of the benzazepine class of histamine H3 receptor antagonists.

Science.gov (United States)

Wilson, David M; Apps, James; Bailey, Nicholas; Bamford, Mark J; Beresford, Isabel J; Briggs, Michael A; Calver, Andrew R; Crook, Barry; Davis, Robert P; Davis, Susannah; Dean, David K; Harris, Leanne; Heightman, Tom D; Panchal, Terry; Parr, Christopher A; Quashie, Nigel; Steadman, Jon G A; Schogger, Joanne; Sehmi, Sanjeet S; Stean, Tania O; Takle, Andrew K; Trail, Brenda K; White, Trevor; Witherington, Jason; Worby, Angela; Medhurst, Andrew D

2013-12-15

This Letter describes the discovery of a novel series of H3 receptor antagonists. The initial medicinal chemistry strategy focused on deconstructing and simplifying an early screening hit which rapidly led to the discovery of a novel series of H3 receptor antagonists based on the benzazepine core. Employing an H3 driven pharmacodynamic model, the series was then further optimised through to a lead compound that showed robust in vivo functional activity and possessed overall excellent developability properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prioritizing multiple therapeutic targets in parallel using automated DNA-encoded library screening

Science.gov (United States)

Machutta, Carl A.; Kollmann, Christopher S.; Lind, Kenneth E.; Bai, Xiaopeng; Chan, Pan F.; Huang, Jianzhong; Ballell, Lluis; Belyanskaya, Svetlana; Besra, Gurdyal S.; Barros-Aguirre, David; Bates, Robert H.; Centrella, Paolo A.; Chang, Sandy S.; Chai, Jing; Choudhry, Anthony E.; Coffin, Aaron; Davie, Christopher P.; Deng, Hongfeng; Deng, Jianghe; Ding, Yun; Dodson, Jason W.; Fosbenner, David T.; Gao, Enoch N.; Graham, Taylor L.; Graybill, Todd L.; Ingraham, Karen; Johnson, Walter P.; King, Bryan W.; Kwiatkowski, Christopher R.; Lelièvre, Joël; Li, Yue; Liu, Xiaorong; Lu, Quinn; Lehr, Ruth; Mendoza-Losana, Alfonso; Martin, John; McCloskey, Lynn; McCormick, Patti; O'Keefe, Heather P.; O'Keeffe, Thomas; Pao, Christina; Phelps, Christopher B.; Qi, Hongwei; Rafferty, Keith; Scavello, Genaro S.; Steiginga, Matt S.; Sundersingh, Flora S.; Sweitzer, Sharon M.; Szewczuk, Lawrence M.; Taylor, Amy; Toh, May Fern; Wang, Juan; Wang, Minghui; Wilkins, Devan J.; Xia, Bing; Yao, Gang; Zhang, Jean; Zhou, Jingye; Donahue, Christine P.; Messer, Jeffrey A.; Holmes, David; Arico-Muendel, Christopher C.; Pope, Andrew J.; Gross, Jeffrey W.; Evindar, Ghotas

2017-07-01

The identification and prioritization of chemically tractable therapeutic targets is a significant challenge in the discovery of new medicines. We have developed a novel method that rapidly screens multiple proteins in parallel using DNA-encoded library technology (ELT). Initial efforts were focused on the efficient discovery of antibacterial leads against 119 targets from Acinetobacter baumannii and Staphylococcus aureus. The success of this effort led to the hypothesis that the relative number of ELT binders alone could be used to assess the ligandability of large sets of proteins. This concept was further explored by screening 42 targets from Mycobacterium tuberculosis. Active chemical series for six targets from our initial effort as well as three chemotypes for DHFR from M. tuberculosis are reported. The findings demonstrate that parallel ELT selections can be used to assess ligandability and highlight opportunities for successful lead and tool discovery.

Initial screening test for blunt cerebrovascular injury: Validity assessment of whole-body computed tomography.

Science.gov (United States)

Laser, Adriana; Kufera, Joseph A; Bruns, Brandon R; Sliker, Clint W; Tesoriero, Ronald B; Scalea, Thomas M; Stein, Deborah M

2015-09-01

Our whole-body computed tomography protocol (WBCT), used to image patients with polytrauma, consists of a noncontrast head computed tomography (CT) followed by a multidetector computed tomography (40- or 64- slice) that includes an intravenous, contrast-enhanced scan from the face through the pelvis. WBCT is used to screen for blunt cerebrovascular injury (BCVI) during initial CT imaging of the patient with polytrauma and allows for early initiation of therapy with the goal of avoiding stroke. WBCT has not been directly compared with CT angiography (CTA) of the neck as a screening tool for BCVI. We hypothesize that WBCT is a valid modality to diagnose BCVI compared with neck CTA, thus screening patients with polytrauma for BCVI and limiting the need for subsequent CTA. A retrospective review of the trauma registry was conducted for all patients diagnosed with BCVI from June 2009 to June 2013 at our institution. All injuries, identified and graded on initial WBCT, were compared with neck CTA imaging performed within the first 72 hours. Sensitivity was calculated for WBCT by the use of CTA as the reference standard. Proportions of agreement also were calculated between the grades of injury for both imaging modalities. A total of 319 injured vessels were identified in 227 patients. On initial WBCT 80 (25%) of the injuries were grade I, 75 (24%) grade II, 45 (14%) grade III, 41 (13%) grade IV, and 58 (18%) were classified as indeterminate: 27 vertebral and 31 carotid lesions. Twenty (6%) of the 319 injuries were not detected on WBCT but identified on subsequent CTA (9 grade I, 7 grade II, 4 grade III); 6 vertebral and 14 carotid. For each vessel type and for all vessels combined, WBCT demonstrated sensitivity rates of over 90% to detect BCVI among the population of patients with at least one vessel injured. There was concordant grading of injuries between WBCT and initial diagnostic CTA in 154 (48% of all injuries). Lower grade injures were more discordant than higher

High-Throughput Screening by Nuclear Magnetic Resonance (HTS by NMR) for the Identification of PPIs Antagonists.

Science.gov (United States)

Wu, Bainan; Barile, Elisa; De, Surya K; Wei, Jun; Purves, Angela; Pellecchia, Maurizio

2015-01-01

In recent years the ever so complex field of drug discovery has embraced novel design strategies based on biophysical fragment screening (fragment-based drug design; FBDD) using nuclear magnetic resonance spectroscopy (NMR) and/or structure-guided approaches, most often using X-ray crystallography and computer modeling. Experience from recent years unveiled that these methods are more effective and less prone to artifacts compared to biochemical high-throughput screening (HTS) of large collection of compounds in designing protein inhibitors. Hence these strategies are increasingly becoming the most utilized in the modern pharmaceutical industry. Nonetheless, there is still an impending need to develop innovative and effective strategies to tackle other more challenging targets such as those involving protein-protein interactions (PPIs). While HTS strategies notoriously fail to identify viable hits against such targets, few successful examples of PPIs antagonists derived by FBDD strategies exist. Recently, we reported on a new strategy that combines some of the basic principles of fragment-based screening with combinatorial chemistry and NMR-based screening. The approach, termed HTS by NMR, combines the advantages of combinatorial chemistry and NMR-based screening to rapidly and unambiguously identify bona fide inhibitors of PPIs. This review will reiterate the critical aspects of the approach with examples of possible applications.

Implementation of depression screening in antenatal clinics through tablet computers: results of a feasibility study.

Science.gov (United States)

Marcano-Belisario, José S; Gupta, Ajay K; O'Donoghue, John; Ramchandani, Paul; Morrison, Cecily; Car, Josip

2017-05-10

Mobile devices may facilitate depression screening in the waiting area of antenatal clinics. This can present implementation challenges, of which we focused on survey layout and technology deployment. We assessed the feasibility of using tablet computers to administer a socio-demographic survey, the Whooley questions and the Edinburgh Postnatal Depression Scale (EPDS) to 530 pregnant women attending National Health Service (NHS) antenatal clinics across England. We randomised participants to one of two layout versions of these surveys: (i) a scrolling layout where each survey was presented on a single screen; or (ii) a paging layout where only one question appeared on the screen at any given time. Overall, 85.10% of eligible pregnant women agreed to take part. Of these, 90.95% completed the study procedures. Approximately 23% of participants answered Yes to at least one Whooley question, and approximately 13% of them scored 10 points of more on the EPDS. We observed no association between survey layout and the responses given to the Whooley questions, the median EPDS scores, the number of participants at increased risk of self-harm, and the number of participants asking for technical assistance. However, we observed a difference in the number of participants at each EPDS scoring interval (p = 0.008), which provide an indication of a woman's risk of depression. A scrolling layout resulted in faster completion times (median = 4 min 46 s) than a paging layout (median = 5 min 33 s) (p = 0.024). However, the clinical significance of this difference (47.5 s) is yet to be determined. Tablet computers can be used for depression screening in the waiting area of antenatal clinics. This requires the careful consideration of clinical workflows, and technology-related issues such as connectivity and security. An association between survey layout and EPDS scoring intervals needs to be explored further to determine if it corresponds to a survey layout effect

Virtual screening methods as tools for drug lead discovery from large chemical libraries.

Science.gov (United States)

Ma, X H; Zhu, F; Liu, X; Shi, Z; Zhang, J X; Yang, S Y; Wei, Y Q; Chen, Y Z

2012-01-01

Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ~ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

Denver screening protocol for blunt cerebrovascular injury reduces the use of multi-detector computed tomography angiography.

Science.gov (United States)

Beliaev, Andrei M; Barber, P Alan; Marshall, Roger J; Civil, Ian

2014-06-01

Blunt cerebrovascular injury (BCVI) occurs in 0.2-2.7% of blunt trauma patients and has up to 30% mortality. Conventional screening does not recognize up to 20% of BCVI patients. To improve diagnosis of BCVI, both an expanded battery of screening criteria and a multi-detector computed tomography angiography (CTA) have been suggested. The aim of this study is to investigate whether the use of CTA restricted to the Denver protocol screen-positive patients would reduce the unnecessary use of CTA as a pre-emptive screening tool. This is a registry-based study of blunt trauma patients admitted to Auckland City Hospital from 1998 to 2012. The diagnosis of BCVI was confirmed or excluded with CTA, magnetic resonance angiography and, if these imaging were non-conclusive, four-vessel digital subtraction angiography. Thirty (61%) BCVI and 19 (39%) non-BCVI patients met eligibility criteria. The Denver protocol applied to our cohort of patients had a sensitivity of 97% (95% confidence interval (CI): 83-100%) and a specificity of 42% (95% CI: 20-67%). With a prevalence of BCVI in blunt trauma patients of 0.2% and 2.7%, post-test odds of a screen-positive test were 0.03 (95% CI: 0.002-0.005) and 0.046 (95% CI: 0.314-0.068), respectively. Application of the CTA to the Denver protocol screen-positive trauma patients can decrease the use of CTA as a pre-emptive screening tool by 95-97% and reduces its hazards. © 2013 Royal Australasian College of Surgeons.

Pattern Discovery in Time-Ordered Data; TOPICAL

International Nuclear Information System (INIS)

CONRAD, GREGORY N.; BRITANIK, JOHN M.; DELAND, SHARON M.; JENKIN, CHRISTINA L.

2002-01-01

This report describes the results of a Laboratory-Directed Research and Development project on techniques for pattern discovery in discrete event time series data. In this project, we explored two different aspects of the pattern matching/discovery problem. The first aspect studied was the use of Dynamic Time Warping for pattern matching in continuous data. In essence, DTW is a technique for aligning time series along the time axis to optimize the similarity measure. The second aspect studied was techniques for discovering patterns in discrete event data. We developed a pattern discovery tool based on adaptations of the A-priori and GSP (Generalized Sequential Pattern mining) algorithms. We then used the tool on three different application areas-unattended monitoring system data from a storage magazine, computer network intrusion detection, and analysis of robot training data

Colorectal Cancer Screening

OpenAIRE

Quintero, Enrique; Saito, Yutaka; Hassan, Cessare; Senore, Carlo

2012-01-01

Colorectal cancer, which is the leading cancer in Singapore, can be prevented by increased use of screening and polypectomy. A range of screening strategies such as stool-based tests, flexible sigmoidoscopy, colonoscopy and computed tomography colonography are available, each with different strengths and limitations. Primary care physicians should discuss appropriate screening modalities with their patients, tailored to their individual needs. Physicians, patients and the government should wo...

High Content Screening: Understanding Cellular Pathway

International Nuclear Information System (INIS)

Mohamed Zaffar Ali Mohamed Amiroudine; Daryl Jesus Arapoc; Zainah Adam; Shafii Khamis

2015-01-01

High content screening (HCS) is the convergence between cell-based assays, high-resolution fluorescence imaging, phase-contrast imaging of fixed- or live-cell assays, tissues and small organisms. It has been widely adopted in the pharmaceutical and biotech industries for target identification and validation and as secondary screens to reveal potential toxicities or to elucidate a drugs mechanism of action. By using the ImageXpress® Micro XLS System HCS, the complex network of key players controlling proliferation and apoptosis can be reduced to several sentinel markers for analysis. Cell proliferation and apoptosis are two key areas in cell biology and drug discovery research. Understanding the signaling pathways in cell proliferation and apoptosis is important for new therapeutic discovery because the imbalance between these two events is predominant in the progression of many human diseases, including cancer. The DNA binding dye DAPI is used to determine the nuclear size and nuclear morphology as well as cell cycle phases by DNA content. Images together with MetaXpress® analysis results provide a convenient and easy to use solution to high volume image management. In particular, HCS platform is beginning to have an important impact on early drug discovery, basic research in systems cell biology, and is expected to play a role in personalized medicine or revealing off-target drug effects. (author)

Computer Vision Tool and Technician as First Reader of Lung Cancer Screening CT Scans.

Science.gov (United States)

Ritchie, Alexander J; Sanghera, Calvin; Jacobs, Colin; Zhang, Wei; Mayo, John; Schmidt, Heidi; Gingras, Michel; Pasian, Sergio; Stewart, Lori; Tsai, Scott; Manos, Daria; Seely, Jean M; Burrowes, Paul; Bhatia, Rick; Atkar-Khattra, Sukhinder; van Ginneken, Bram; Tammemagi, Martin; Tsao, Ming Sound; Lam, Stephen

2016-05-01

To implement a cost-effective low-dose computed tomography (LDCT) lung cancer screening program at the population level, accurate and efficient interpretation of a large volume of LDCT scans is needed. The objective of this study was to evaluate a workflow strategy to identify abnormal LDCT scans in which a technician assisted by computer vision (CV) software acts as a first reader with the aim to improve speed, consistency, and quality of scan interpretation. Without knowledge of the diagnosis, a technician reviewed 828 randomly batched scans (136 with lung cancers, 556 with benign nodules, and 136 without nodules) from the baseline Pan-Canadian Early Detection of Lung Cancer Study that had been annotated by the CV software CIRRUS Lung Screening (Diagnostic Image Analysis Group, Nijmegen, The Netherlands). The scans were classified as either normal (no nodules ≥1 mm or benign nodules) or abnormal (nodules or other abnormality). The results were compared with the diagnostic interpretation by Pan-Canadian Early Detection of Lung Cancer Study radiologists. The overall sensitivity and specificity of the technician in identifying an abnormal scan were 97.8% (95% confidence interval: 96.4-98.8) and 98.0% (95% confidence interval: 89.5-99.7), respectively. Of the 112 prevalent nodules that were found to be malignant in follow-up, 92.9% were correctly identified by the technician plus CV compared with 84.8% by the study radiologists. The average time taken by the technician to review a scan after CV processing was 208 ± 120 seconds. Prescreening CV software and a technician as first reader is a promising strategy for improving the consistency and quality of screening interpretation of LDCT scans. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

Romasanta, Angelo K S; van der Sijde, Peter; Hellsten, Iina; Hubbard, Roderick E; Keseru, Gyorgy M; van Muijlwijk-Koezen, Jacqueline; de Esch, Iwan J P

2018-05-05

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 FBDD, complementing accounts by key practitioners. Mapping its core papers, we found the transfer of knowledge from academia to industry. Co-authorship analysis showed that university-industry collaboration has grown over time. Moreover, we show how ideas from other scientific disciplines have been integrated into the FBDD paradigm. Keyword analysis showed that the field is organized into four interconnected practices: library design, fragment screening, computational methods, and optimization. This study highlights the importance of interactions among various individuals and institutions from diverse disciplines in newly emerging scientific fields. Copyright © 2018. Published by Elsevier Ltd.

Redesign of a computerized clinical reminder for colorectal cancer screening: a human-computer interaction evaluation

Directory of Open Access Journals (Sweden)

Saleem Jason J

2011-11-01

Full Text Available Abstract Background Based on barriers to the use of computerized clinical decision support (CDS learned in an earlier field study, we prototyped design enhancements to the Veterans Health Administration's (VHA's colorectal cancer (CRC screening clinical reminder to compare against the VHA's current CRC reminder. Methods In a controlled simulation experiment, 12 primary care providers (PCPs used prototypes of the current and redesigned CRC screening reminder in a within-subject comparison. Quantitative measurements were based on a usability survey, workload assessment instrument, and workflow integration survey. We also collected qualitative data on both designs. Results Design enhancements to the VHA's existing CRC screening clinical reminder positively impacted aspects of usability and workflow integration but not workload. The qualitative analysis revealed broad support across participants for the design enhancements with specific suggestions for improving the reminder further. Conclusions This study demonstrates the value of a human-computer interaction evaluation in informing the redesign of information tools to foster uptake, integration into workflow, and use in clinical practice.

Quantitative structure-activity relationship analysis and virtual screening studies for identifying HDAC2 inhibitors from known HDAC bioactive chemical libraries.

Science.gov (United States)

Pham-The, H; Casañola-Martin, G; Diéguez-Santana, K; Nguyen-Hai, N; Ngoc, N T; Vu-Duc, L; Le-Thi-Thu, H

2017-03-01

Histone deacetylases (HDAC) are emerging as promising targets in cancer, neuronal diseases and immune disorders. Computational modelling approaches have been widely applied for the virtual screening and rational design of novel HDAC inhibitors. In this study, different machine learning (ML) techniques were applied for the development of models that accurately discriminate HDAC2 inhibitors form non-inhibitors. The obtained models showed encouraging results, with the global accuracy in the external set ranging from 0.83 to 0.90. Various aspects related to the comparison of modelling techniques, applicability domain and descriptor interpretations were discussed. Finally, consensus predictions of these models were used for screening HDAC2 inhibitors from four chemical libraries whose bioactivities against HDAC1, HDAC3, HDAC6 and HDAC8 have been known. According to the results of virtual screening assays, structures of some hits with pair-isoform-selective activity (between HDAC2 and other HDACs) were revealed. This study illustrates the power of ML-based QSAR approaches for the screening and discovery of potent, isoform-selective HDACIs.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

Directory of Open Access Journals (Sweden)

Qian Li

Full Text Available BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671 between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

Science.gov (United States)

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by

"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.

Computer Simulation of Breast Cancer Screening

National Research Council Canada - National Science Library

Boone, John

1999-01-01

Breast cancer will affect approximately 12.5% of the women in the United States, and currently mammographic screening is considered the best way to reduce mortality from this disease through early detection...

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.

Computationally assisted screening and design of cell-interactive peptides by a cell-based assay using peptide arrays and a fuzzy neural network algorithm.

Science.gov (United States)

Kaga, Chiaki; Okochi, Mina; Tomita, Yasuyuki; Kato, Ryuji; Honda, Hiroyuki

2008-03-01

We developed a method of effective peptide screening that combines experiments and computational analysis. The method is based on the concept that screening efficiency can be enhanced from even limited data by use of a model derived from computational analysis that serves as a guide to screening and combining the model with subsequent repeated experiments. Here we focus on cell-adhesion peptides as a model application of this peptide-screening strategy. Cell-adhesion peptides were screened by use of a cell-based assay of a peptide array. Starting with the screening data obtained from a limited, random 5-mer library (643 sequences), a rule regarding structural characteristics of cell-adhesion peptides was extracted by fuzzy neural network (FNN) analysis. According to this rule, peptides with unfavored residues in certain positions that led to inefficient binding were eliminated from the random sequences. In the restricted, second random library (273 sequences), the yield of cell-adhesion peptides having an adhesion rate more than 1.5-fold to that of the basal array support was significantly high (31%) compared with the unrestricted random library (20%). In the restricted third library (50 sequences), the yield of cell-adhesion peptides increased to 84%. We conclude that a repeated cycle of experiments screening limited numbers of peptides can be assisted by the rule-extracting feature of FNN.

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.

Evidence-based investigation of the influence of computer-aided detection of polyps on screening of colon cancer with CT colonography

International Nuclear Information System (INIS)

Yoshida, Hiroyuki

2008-01-01

Computed tomographic colonography (CTC), also known as virtual colonoscopy, is a CT examination of the colon for colorectal neoplasms. Recent large-scale clinical trials have demonstrated that CTC yields sensitivity comparable to optical colonoscopy in the detection of clinically significant polyps in a screening population, making CTC a promising technique for screening of colon cancer. For CTC to be a clinically practical means of screening, it must reliably and consistently detect polyps with high accuracy. However, high-level expertise is required to interpret the resulting CT images to find polyps, resulting in variable diagnostic accuracy among radiologists in the detection of polyps. A key technology to overcome this problem and to bring CTC to prime time for screening of colorectal cancer is computer-aided detection (CAD) of polyps. CAD automatically detects the locations of suspicious polyps in CTC images and presents them to radiologists. CAD has the potential to increase diagnostic performance in the detection of polyps as well as to reduce variability of the diagnostic accuracy among radiologists. This paper presents an evidence-based investigation of the influence of CAD on screening of colon cancer with CTC by describing the benefits of using CAD in the diagnosis of CTC, the fundamental CAD scheme for the detection of polyps in CTC, its detection performance, the effect on the improvement of detection performance, as well as the current and future challenges in CAD. (author)

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.

Quality study of portal images acquired by computed radiography and screen-film system under megavoltage ray

International Nuclear Information System (INIS)

Cao Guoquan; Jin Xiance; Wu Shixiu; Xie Congying; Zhang Li; Yu Jianyi; Li Yueqing

2007-01-01

Objective: To evaluate the quality of the portal images acquired by computed radiography (CR) system and conventional screen-film system, respectively. Methods: Imaging plates (IP) and X-ray films ora home-devised lead phantom with a leakage of 6.45% were acquired, and modulation transfer function (MTF) curves of the both images were measured using edge method. Portal images of 40 nasopharyngeal cancer patients were acquired by IP and screen-film system respectively. Two doctors with similar experience evaluated the damage degree of petrosal bone, the receiver operating characteristic (ROC) curve of CR images and general images were drawn according to two doctors evaluation results. Results: The identification frequency of CR system and screen-film system were 1.159 and 0.806 Lp/mm respectively. For doctor one, the area under ROC curve of CR images and general images were 0.802 and 0.742 respectively. For doctor two, the area under ROC curve of CR images and general images were 0.751 and 0.600 respectively. The MTF curve and ROC curve of CR are both better than those of screen-film system. Conclusion: The image quality of CR portal imaging is much better than that of screen-film system. The utility of CR in linear accelerator for portal imaging is promising in clinic. (authors)

Discovery of novel inhibitors for DHODH via virtual screening and X-ray crystallographic structures

Energy Technology Data Exchange (ETDEWEB)

McLean, Larry R.; Zhang, Ying; Degnen, William; Peppard, Jane; Cabel, Dasha; Zou, Chao; Tsay, Joseph T.; Subramaniam, Arun; Vaz, Roy J.; Li, Yi (Sanofi)

2010-10-28

Amino-benzoic acid derivatives 1-4 were found to be inhibitors for DHODH by virtual screening, biochemical, and X-ray crystallographic studies. X-ray structures showed that 1 and 2 bind to DHODH as predicted by virtual screening, but 3 and 4 were found to be structurally different from the corresponding compounds initially identified by virtual screening.

promoting self directed learning in simulation based discovery learning environments through intelligent support.

NARCIS (Netherlands)

Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter

2000-01-01

Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for

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.

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.

Computer-aided diagnostics of screening mammography using content-based image retrieval

Science.gov (United States)

Deserno, Thomas M.; Soiron, Michael; de Oliveira, Júlia E. E.; de A. Araújo, Arnaldo

2012-03-01

Breast cancer is one of the main causes of death among women in occidental countries. In the last years, screening mammography has been established worldwide for early detection of breast cancer, and computer-aided diagnostics (CAD) is being developed to assist physicians reading mammograms. A promising method for CAD is content-based image retrieval (CBIR). Recently, we have developed a classification scheme of suspicious tissue pattern based on the support vector machine (SVM). In this paper, we continue moving towards automatic CAD of screening mammography. The experiments are based on in total 10,509 radiographs that have been collected from different sources. From this, 3,375 images are provided with one and 430 radiographs with more than one chain code annotation of cancerous regions. In different experiments, this data is divided into 12 and 20 classes, distinguishing between four categories of tissue density, three categories of pathology and in the 20 class problem two categories of different types of lesions. Balancing the number of images in each class yields 233 and 45 images remaining in each of the 12 and 20 classes, respectively. Using a two-dimensional principal component analysis, features are extracted from small patches of 128 x 128 pixels and classified by means of a SVM. Overall, the accuracy of the raw classification was 61.6 % and 52.1 % for the 12 and the 20 class problem, respectively. The confusion matrices are assessed for detailed analysis. Furthermore, an implementation of a SVM-based CBIR system for CADx in screening mammography is presented. In conclusion, with a smarter patch extraction, the CBIR approach might reach precision rates that are helpful for the physicians. This, however, needs more comprehensive evaluation on clinical data.

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.

Native State Mass Spectrometry, Surface Plasmon Resonance, and X-ray Crystallography Correlate Strongly as a Fragment Screening Combination.

Science.gov (United States)

Woods, Lucy A; Dolezal, Olan; Ren, Bin; Ryan, John H; Peat, Thomas S; Poulsen, Sally-Ann

2016-03-10

Fragment-based drug discovery (FBDD) is contingent on the development of analytical methods to identify weak protein-fragment noncovalent interactions. Herein we have combined an underutilized fragment screening method, native state mass spectrometry, together with two proven and popular fragment screening methods, surface plasmon resonance and X-ray crystallography, in a fragment screening campaign against human carbonic anhydrase II (CA II). In an initial fragment screen against a 720-member fragment library (the "CSIRO Fragment Library") seven CA II binding fragments, including a selection of nonclassical CA II binding chemotypes, were identified. A further 70 compounds that comprised the initial hit chemotypes were subsequently sourced from the full CSIRO compound collection and screened. The fragment results were extremely well correlated across the three methods. Our findings demonstrate that there is a tremendous opportunity to apply native state mass spectrometry as a complementary fragment screening method to accelerate drug discovery.

Using label-free screening technology to improve efficiency in drug discovery.

Science.gov (United States)

Halai, Reena; Cooper, Matthew A

2012-02-01

Screening assays have traditionally utilized reporter labels to quantify biological responses relevant to the disease state of interest. However, there are limitations associated with the use of labels that may be overcome with temporal measurements possible with label-free. This review comprises general and system-specific information from literature searches using PubMed, published books and the authors' personal experience. This review highlights the label-free approaches in the context of various applications. The authors also note technical issues relevant to the development of label-free assays and their application to HTS. The limitations associated with the use of transfected cell lines and the use of label-based assays are gradually being realized. As such, greater emphasis is being placed on label-free biophysical techniques using native cell lines. The introduction of 96- and 384-well plate label-free systems is helping to broker a wider acceptance of these approaches in high-throughput screening. However, potential users of the technologies remain skeptical, primarily because the physical basis of the signals generated, and their contextual relevance to cell biology and signal transduction, has not been fully elucidated. Until this is done, these new technology platforms are more likely to complement, rather than replace, traditional screening platforms.

A brief measure of Smokers' knowledge of lung cancer screening with low-dose computed tomography

Directory of Open Access Journals (Sweden)

Lisa M. Lowenstein

2016-12-01

Full Text Available We describe the development and psychometric properties of a new, brief measure of smokers' knowledge of lung cancer screening with low-dose computed tomography (LDCT. Content experts identified key facts smokers should know in making an informed decision about lung cancer screening. Sample questions were drafted and iteratively refined based on feedback from content experts and cognitive testing with ten smokers. The resulting 16-item knowledge measure was completed by 108 heavy smokers in Houston, Texas, recruited from 12/2014 to 09/2015. Item difficulty, item discrimination, internal consistency and test-retest reliability were assessed. Group differences based upon education levels and smoking history were explored. Several items were dropped due to ceiling effects or overlapping constructs, resulting in a 12-item knowledge measure. Additional items with high item uncertainty were retained because of their importance in informed decision making about lung cancer screening. Internal consistency reliability of the final scale was acceptable (KR-20 = 0.66 and test-retest reliability of the overall scale was 0.84 (intraclass correlation. Knowledge scores differed across education levels (F = 3.36, p = 0.04, while no differences were observed between current and former smokers (F = 1.43, p = 0.24 or among participants who met or did not meet the 30-pack-year screening eligibility criterion (F = 0.57, p = 0.45. The new measure provides a brief, valid and reliable indicator of smokers' knowledge of key concepts central to making an informed decision about lung cancer screening with LDCT, and can be part of a broader assessment of the quality of smokers' decision making about lung cancer screening.

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.

Automated Groundwater Screening

International Nuclear Information System (INIS)

Taylor, Glenn A.; Collard, Leonard B.

2005-01-01

The Automated Intruder Analysis has been extended to include an Automated Ground Water Screening option. This option screens 825 radionuclides while rigorously applying the National Council on Radiation Protection (NCRP) methodology. An extension to that methodology is presented to give a more realistic screening factor for those radionuclides which have significant daughters. The extension has the promise of reducing the number of radionuclides which must be tracked by the customer. By combining the Automated Intruder Analysis with the Automated Groundwater Screening a consistent set of assumptions and databases is used. A method is proposed to eliminate trigger values by performing rigorous calculation of the screening factor thereby reducing the number of radionuclides sent to further analysis. Using the same problem definitions as in previous groundwater screenings, the automated groundwater screening found one additional nuclide, Ge-68, which failed the screening. It also found that 18 of the 57 radionuclides contained in NCRP Table 3.1 failed the screening. This report describes the automated groundwater screening computer application

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling | Office of Cancer Genomics

Science.gov (United States)

Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives.

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling.

Science.gov (United States)

Yu, Jiyang; Silva, Jose; Califano, Andrea

2016-01-15

Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives. Indeed, rigorous statistical analysis of high-throughput FG screening data remains challenging, particularly when integrative analyses are used to combine multiple sh/sgRNAs targeting the same gene in the library. We use large RNAi and CRISPR repositories that are publicly available to evaluate a novel meta-analysis approach for FG screens via Bayesian hierarchical modeling, Screening Bayesian Evaluation and Analysis Method (ScreenBEAM). Results from our analysis show that the proposed strategy, which seamlessly combines all available data, robustly outperforms classical algorithms developed for microarray data sets as well as recent approaches designed for next generation sequencing technologies. Remarkably, the ScreenBEAM algorithm works well even when the quality of FG screens is relatively low, which accounts for about 80-95% of the public datasets. R package and source code are available at: https://github.com/jyyu/ScreenBEAM. ac2248@columbia.edu, jose.silva@mssm.edu, yujiyang@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Fragment screening of cyclin G-associated kinase by weak affinity chromatography.

Science.gov (United States)

Meiby, Elinor; Knapp, Stefan; Elkins, Jonathan M; Ohlson, Sten

2012-11-01

Fragment-based drug discovery (FBDD) has become a new strategy for drug discovery where lead compounds are evolved from small molecules. These fragments form low affinity interactions (dissociation constant (K(D)) = mM - μM) with protein targets, which require fragment screening methods of sufficient sensitivity. Weak affinity chromatography (WAC) is a promising new technology for fragment screening based on selective retention of fragments by a drug target. Kinases are a major pharmaceutical target, and FBDD has been successfully applied to several of these targets. In this work, we have demonstrated the potential to use WAC in combination with mass spectrometry (MS) detection for fragment screening of a kinase target-cyclin G-associated kinase (GAK). One hundred seventy fragments were selected for WAC screening by virtual screening of a commercial fragment library against the ATP-binding site of five different proteins. GAK protein was immobilized on a capillary HPLC column, and compound binding was characterized by frontal affinity chromatography. Compounds were screened in sets of 13 or 14, in combination with MS detection for enhanced throughput. Seventy-eight fragments (46 %) with K(D) < 200 μM were detected, including a few highly efficient GAK binders (K(D) of 2 μM; ligand efficiency = 0.51). Of special interest is that chiral screening by WAC may be possible, as two stereoisomeric fragments, which both contained one chiral center, demonstrated twin peaks. This ability, in combination with the robustness, sensitivity, and simplicity of WAC makes it a new method for fragment screening of considerable potential.

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.

AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening

Directory of Open Access Journals (Sweden)

Pajeva Ilza

2008-10-01

Full Text Available Abstract Background Virtual or in silico ligand screening combined with other computational methods is one of the most promising methods to search for new lead compounds, thereby greatly assisting the drug discovery process. Despite considerable progresses made in virtual screening methodologies, available computer programs do not easily address problems such as: structural optimization of compounds in a screening library, receptor flexibility/induced-fit, and accurate prediction of protein-ligand interactions. It has been shown that structural optimization of chemical compounds and that post-docking optimization in multi-step structure-based virtual screening approaches help to further improve the overall efficiency of the methods. To address some of these points, we developed the program AMMOS for refining both, the 3D structures of the small molecules present in chemical libraries and the predicted receptor-ligand complexes through allowing partial to full atom flexibility through molecular mechanics optimization. Results The program AMMOS carries out an automatic procedure that allows for the structural refinement of compound collections and energy minimization of protein-ligand complexes using the open source program AMMP. The performance of our package was evaluated by comparing the structures of small chemical entities minimized by AMMOS with those minimized with the Tripos and MMFF94s force fields. Next, AMMOS was used for full flexible minimization of protein-ligands complexes obtained from a mutli-step virtual screening. Enrichment studies of the selected pre-docked complexes containing 60% of the initially added inhibitors were carried out with or without final AMMOS minimization on two protein targets having different binding pocket properties. AMMOS was able to improve the enrichment after the pre-docking stage with 40 to 60% of the initially added active compounds found in the top 3% to 5% of the entire compound collection

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.

How is adults' screen time behaviour influencing their views on screen time restrictions for children? A cross-sectional study.

Science.gov (United States)

Schoeppe, Stephanie; Rebar, Amanda L; Short, Camille E; Alley, Stephanie; Van Lippevelde, Wendy; Vandelanotte, Corneel

2016-03-01

High screen time in children and its detrimental health effects is a major public health problem. How much screen time adults think is appropriate for children remains little explored, as well as whether adults' screen time behaviour would determine their views on screen time restrictions for children. This study aimed to investigate how adults' screen time behaviour influences their views on screen time restrictions for children, including differences by gender and parental status. In 2013, 2034 Australian adults participated in an online survey conducted by the Population Research Laboratory at Central Queensland University, Rockhampton. Adult screen time behaviour was assessed using the Workforce Sitting Questionnaire. Adults reported the maximum time children aged between 5-12 years should be allowed to spend watching TV and using a computer. Ordinal logistic regression was used to compare adult screen time behaviour with views on screen time restrictions for children. Most adults (68%) held the view that children should be allowed no more than 2 h of TV viewing and computer use on school days, whilst fewer adults (44%) thought this screen time limit is needed on weekend days. Women would impose higher screen time restrictions for children than men (p 2 h on watching TV and using the computer at home on work days (66%) and non-work days (88%). Adults spending ≤ 2 h/day in leisure-related screen time were less likely to permit children > 2 h/day of screen time. These associations did not differ by adult gender and parental status. Most adults think it is appropriate to limit children's screen time to the recommended ≤ 2 h/day but few adults themselves adhere to this screen time limit. Adults with lower screen use may be more inclined to limit children's screen time. Strategies to reduce screen time in children may also need to target adult screen use.

Role of Chemical Reactivity and Transition State Modeling for Virtual Screening.

Science.gov (United States)

Karthikeyan, Muthukumarasamy; Vyas, Renu; Tambe, Sanjeev S; Radhamohan, Deepthi; Kulkarni, Bhaskar D

2015-01-01

Every drug discovery research program involves synthesis of a novel and potential drug molecule utilizing atom efficient, economical and environment friendly synthetic strategies. The current work focuses on the role of the reactivity based fingerprints of compounds as filters for virtual screening using a tool ChemScore. A reactant-like (RLS) and a product- like (PLS) score can be predicted for a given compound using the binary fingerprints derived from the numerous known organic reactions which capture the molecule-molecule interactions in the form of addition, substitution, rearrangement, elimination and isomerization reactions. The reaction fingerprints were applied to large databases in biology and chemistry, namely ChEMBL, KEGG, HMDB, DSSTox, and the Drug Bank database. A large network of 1113 synthetic reactions was constructed to visualize and ascertain the reactant product mappings in the chemical reaction space. The cumulative reaction fingerprints were computed for 4000 molecules belonging to 29 therapeutic classes of compounds, and these were found capable of discriminating between the cognition disorder related and anti-allergy compounds with reasonable accuracy of 75% and AUC 0.8. In this study, the transition state based fingerprints were also developed and used effectively for virtual screening in drug related databases. The methodology presented here provides an efficient handle for the rapid scoring of molecular libraries for virtual screening.

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.

Scientific Grand Challenges: Discovery In Basic Energy Sciences: The Role of Computing at the Extreme Scale - August 13-15, 2009, Washington, D.C.

Energy Technology Data Exchange (ETDEWEB)

Galli, Giulia [Univ. of California, Davis, CA (United States). Workshop Chair; Dunning, Thom [Univ. of Illinois, Urbana, IL (United States). Workshop Chair

2009-08-13

The U.S. Department of Energy’s (DOE) Office of Basic Energy Sciences (BES) and Office of Advanced Scientific Computing Research (ASCR) workshop in August 2009 on extreme-scale computing provided a forum for more than 130 researchers to explore the needs and opportunities that will arise due to expected dramatic advances in computing power over the next decade. This scientific community firmly believes that the development of advanced theoretical tools within chemistry, physics, and materials science—combined with the development of efficient computational techniques and algorithms—has the potential to revolutionize the discovery process for materials and molecules with desirable properties. Doing so is necessary to meet the energy and environmental challenges of the 21^st century as described in various DOE BES Basic Research Needs reports. Furthermore, computational modeling and simulation are a crucial complement to experimental studies, particularly when quantum mechanical processes controlling energy production, transformations, and storage are not directly observable and/or controllable. Many processes related to the Earth’s climate and subsurface need better modeling capabilities at the molecular level, which will be enabled by extreme-scale computing.

Rapid, computer vision-enabled murine screening system identifies neuropharmacological potential of two new mechanisms

Directory of Open Access Journals (Sweden)

Steven L Roberds

2011-09-01

Full Text Available The lack of predictive in vitro models for behavioral phenotypes impedes rapid advancement in neuropharmacology and psychopharmacology. In vivo behavioral assays are more predictive of activity in human disorders, but such assays are often highly resource-intensive. Here we describe the successful application of a computer vision-enabled system to identify potential neuropharmacological activity of two new mechanisms. The analytical system was trained using multiple drugs that are used clinically to treat depression, schizophrenia, anxiety, and other psychiatric or behavioral disorders. During blinded testing the PDE10 inhibitor TP-10 produced a signature of activity suggesting potential antipsychotic activity. This finding is consistent with TP-10’s activity in multiple rodent models that is similar to that of clinically used antipsychotic drugs. The CK1ε inhibitor PF-670462 produced a signature consistent with anxiolytic activity and, at the highest dose tested, behavioral effects similar to that of opiate analgesics. Neither TP-10 nor PF-670462 was included in the training set. Thus, computer vision-based behavioral analysis can facilitate drug discovery by identifying neuropharmacological effects of compounds acting through new mechanisms.

Low-Dose Chest Computed Tomography for Lung Cancer Screening Among Hodgkin Lymphoma Survivors: A Cost-Effectiveness Analysis

International Nuclear Information System (INIS)

Wattson, Daniel A.; Hunink, M.G. Myriam; DiPiro, Pamela J.; Das, Prajnan; Hodgson, David C.; Mauch, Peter M.; Ng, Andrea K.

2014-01-01

Purpose: Hodgkin lymphoma (HL) survivors face an increased risk of treatment-related lung cancer. Screening with low-dose computed tomography (LDCT) may allow detection of early stage, resectable cancers. We developed a Markov decision-analytic and cost-effectiveness model to estimate the merits of annual LDCT screening among HL survivors. Methods and Materials: Population databases and HL-specific literature informed key model parameters, including lung cancer rates and stage distribution, cause-specific survival estimates, and utilities. Relative risks accounted for radiation therapy (RT) technique, smoking status (>10 pack-years or current smokers vs not), age at HL diagnosis, time from HL treatment, and excess radiation from LDCTs. LDCT assumptions, including expected stage-shift, false-positive rates, and likely additional workup were derived from the National Lung Screening Trial and preliminary results from an internal phase 2 protocol that performed annual LDCTs in 53 HL survivors. We assumed a 3% discount rate and a willingness-to-pay (WTP) threshold of $50,000 per quality-adjusted life year (QALY). Results: Annual LDCT screening was cost effective for all smokers. A male smoker treated with mantle RT at age 25 achieved maximum QALYs by initiating screening 12 years post-HL, with a life expectancy benefit of 2.1 months and an incremental cost of $34,841/QALY. Among nonsmokers, annual screening produced a QALY benefit in some cases, but the incremental cost was not below the WTP threshold for any patient subsets. As age at HL diagnosis increased, earlier initiation of screening improved outcomes. Sensitivity analyses revealed that the model was most sensitive to the lung cancer incidence and mortality rates and expected stage-shift from screening. Conclusions: HL survivors are an important high-risk population that may benefit from screening, especially those treated in the past with large radiation fields including mantle or involved-field RT. Screening

Low-Dose Chest Computed Tomography for Lung Cancer Screening Among Hodgkin Lymphoma Survivors: A Cost-Effectiveness Analysis

Energy Technology Data Exchange (ETDEWEB)

Wattson, Daniel A., E-mail: dwattson@partners.org [Harvard Radiation Oncology Program, Boston, Massachusetts (United States); Hunink, M.G. Myriam [Departments of Radiology and Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands and Center for Health Decision Science, Harvard School of Public Health, Boston, Massachusetts (United States); DiPiro, Pamela J. [Department of Imaging, Dana-Farber Cancer Institute, Boston, Massachusetts (United States); Das, Prajnan [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Hodgson, David C. [Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Mauch, Peter M.; Ng, Andrea K. [Department of Radiation Oncology, Brigham and Women' s Hospital and Dana-Farber Cancer Institute, Boston, Massachusetts (United States)

2014-10-01

Purpose: Hodgkin lymphoma (HL) survivors face an increased risk of treatment-related lung cancer. Screening with low-dose computed tomography (LDCT) may allow detection of early stage, resectable cancers. We developed a Markov decision-analytic and cost-effectiveness model to estimate the merits of annual LDCT screening among HL survivors. Methods and Materials: Population databases and HL-specific literature informed key model parameters, including lung cancer rates and stage distribution, cause-specific survival estimates, and utilities. Relative risks accounted for radiation therapy (RT) technique, smoking status (>10 pack-years or current smokers vs not), age at HL diagnosis, time from HL treatment, and excess radiation from LDCTs. LDCT assumptions, including expected stage-shift, false-positive rates, and likely additional workup were derived from the National Lung Screening Trial and preliminary results from an internal phase 2 protocol that performed annual LDCTs in 53 HL survivors. We assumed a 3% discount rate and a willingness-to-pay (WTP) threshold of $50,000 per quality-adjusted life year (QALY). Results: Annual LDCT screening was cost effective for all smokers. A male smoker treated with mantle RT at age 25 achieved maximum QALYs by initiating screening 12 years post-HL, with a life expectancy benefit of 2.1 months and an incremental cost of $34,841/QALY. Among nonsmokers, annual screening produced a QALY benefit in some cases, but the incremental cost was not below the WTP threshold for any patient subsets. As age at HL diagnosis increased, earlier initiation of screening improved outcomes. Sensitivity analyses revealed that the model was most sensitive to the lung cancer incidence and mortality rates and expected stage-shift from screening. Conclusions: HL survivors are an important high-risk population that may benefit from screening, especially those treated in the past with large radiation fields including mantle or involved-field RT. Screening

Low-dose chest computed tomography for lung cancer screening among Hodgkin lymphoma survivors: a cost-effectiveness analysis.

Science.gov (United States)

Wattson, Daniel A; Hunink, M G Myriam; DiPiro, Pamela J; Das, Prajnan; Hodgson, David C; Mauch, Peter M; Ng, Andrea K

2014-10-01

Hodgkin lymphoma (HL) survivors face an increased risk of treatment-related lung cancer. Screening with low-dose computed tomography (LDCT) may allow detection of early stage, resectable cancers. We developed a Markov decision-analytic and cost-effectiveness model to estimate the merits of annual LDCT screening among HL survivors. Population databases and HL-specific literature informed key model parameters, including lung cancer rates and stage distribution, cause-specific survival estimates, and utilities. Relative risks accounted for radiation therapy (RT) technique, smoking status (>10 pack-years or current smokers vs not), age at HL diagnosis, time from HL treatment, and excess radiation from LDCTs. LDCT assumptions, including expected stage-shift, false-positive rates, and likely additional workup were derived from the National Lung Screening Trial and preliminary results from an internal phase 2 protocol that performed annual LDCTs in 53 HL survivors. We assumed a 3% discount rate and a willingness-to-pay (WTP) threshold of $50,000 per quality-adjusted life year (QALY). Annual LDCT screening was cost effective for all smokers. A male smoker treated with mantle RT at age 25 achieved maximum QALYs by initiating screening 12 years post-HL, with a life expectancy benefit of 2.1 months and an incremental cost of $34,841/QALY. Among nonsmokers, annual screening produced a QALY benefit in some cases, but the incremental cost was not below the WTP threshold for any patient subsets. As age at HL diagnosis increased, earlier initiation of screening improved outcomes. Sensitivity analyses revealed that the model was most sensitive to the lung cancer incidence and mortality rates and expected stage-shift from screening. HL survivors are an important high-risk population that may benefit from screening, especially those treated in the past with large radiation fields including mantle or involved-field RT. Screening may be cost effective for all smokers but possibly not

Computational tools for high-throughput discovery in biology

OpenAIRE

Jones, Neil Christopher

2007-01-01

High throughput data acquisition technology has inarguably transformed the landscape of the life sciences, in part by making possible---and necessary---the computational disciplines of bioinformatics and biomedical informatics. These fields focus primarily on developing tools for analyzing data and generating hypotheses about objects in nature, and it is in this context that we address three pressing problems in the fields of the computational life sciences which each require computing capaci...

Developing a novel fiber optic fluorescence device for multiplexed high-throughput cytotoxic screening.

Science.gov (United States)

Lee, Dennis; Barnes, Stephen

2010-01-01

The need for new pharmacological agents is unending. Yet the drug discovery process has changed substantially over the past decade and continues to evolve in response to new technologies. There is presently a high demand to reduce discovery time by improving specific lab disciplines and developing new technology platforms in the area of cell-based assay screening. Here we present the developmental concept and early stage testing of the Ab-Sniffer, a novel fiber optic fluorescence device for high-throughput cytotoxicity screening using an immobilized whole cell approach. The fused silica fibers are chemically functionalized with biotin to provide interaction with fluorescently labeled, streptavidin functionalized alginate-chitosan microspheres. The microspheres are also functionalized with Concanavalin A to facilitate binding to living cells. By using lymphoma cells and rituximab in an adaptation of a well-known cytotoxicity protocol we demonstrate the utility of the Ab-Sniffer for functional screening of potential drug compounds rather than indirect, non-functional screening via binding assay. The platform can be extended to any assay capable of being tied to a fluorescence response including multiple target cells in each well of a multi-well plate for high-throughput screening.

Computational and Biochemical Discovery of RSK2 as a Novel Target for Epigallocatechin Gallate (EGCG.

Directory of Open Access Journals (Sweden)

Hanyong Chen

Full Text Available The most active anticancer component in green tea is epigallocatechin-3-gallate (EGCG. Protein interaction with EGCG is a critical step for mediating the effects of EGCG on the regulation of various key molecules involved in signal transduction. By using computational docking screening methods for protein identification, we identified a serine/threonine kinase, 90-kDa ribosomal S6 kinase (RSK2, as a novel molecular target of EGCG. RSK2 includes two kinase catalytic domains in the N-terminal (NTD and the C-terminal (CTD and RSK2 full activation requires phosphorylation of both terminals. The computer prediction was confirmed by an in vitro kinase assay in which EGCG inhibited RSK2 activity in a dose-dependent manner. Pull-down assay results showed that EGCG could bind with RSK2 at both kinase catalytic domains in vitro and ex vivo. Furthermore, results of an ATP competition assay and a computer-docking model showed that EGCG binds with RSK2 in an ATP-dependent manner. In RSK2+/+ and RSK2-/- murine embryonic fibroblasts, EGCG decreased viability only in the presence of RSK2. EGCG also suppressed epidermal growth factor-induced neoplastic cell transformation by inhibiting phosphorylation of histone H3 at Ser10. Overall, these results indicate that RSK2 is a novel molecular target of EGCG.

Systems Pharmacology in Small Molecular Drug Discovery