Properties of Protein Drug Target Classes

Science.gov (United States)

Bull, Simon C.; Doig, Andrew J.

2015-01-01

Accurate identification of drug targets is a crucial part of any drug development program. We mined the human proteome to discover properties of proteins that may be important in determining their suitability for pharmaceutical modulation. Data was gathered concerning each protein’s sequence, post-translational modifications, secondary structure, germline variants, expression profile and drug target status. The data was then analysed to determine features for which the target and non-target proteins had significantly different values. This analysis was repeated for subsets of the proteome consisting of all G-protein coupled receptors, ion channels, kinases and proteases, as well as proteins that are implicated in cancer. Machine learning was used to quantify the proteins in each dataset in terms of their potential to serve as a drug target. This was accomplished by first inducing a random forest that could distinguish between its targets and non-targets, and then using the random forest to quantify the drug target likeness of the non-targets. The properties that can best differentiate targets from non-targets were primarily those that are directly related to a protein’s sequence (e.g. secondary structure). Germline variants, expression levels and interactions between proteins had minimal discriminative power. Overall, the best indicators of drug target likeness were found to be the proteins’ hydrophobicities, in vivo half-lives, propensity for being membrane bound and the fraction of non-polar amino acids in their sequences. In terms of predicting potential targets, datasets of proteases, ion channels and cancer proteins were able to induce random forests that were highly capable of distinguishing between targets and non-targets. The non-target proteins predicted to be targets by these random forests comprise the set of the most suitable potential future drug targets, and should therefore be prioritised when building a drug development programme. PMID

Protein-Based Drug-Delivery Materials

OpenAIRE

Jao, Dave; Xue, Ye; Medina, Jethro; Hu, Xiao

2017-01-01

There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based pol...

Construction and characterization of a pure protein hydrogel for drug delivery application.

Science.gov (United States)

Xu, Xu; Xu, ZhaoKang; Yang, XiaoFeng; He, YanHao; Lin, Rong

2017-02-01

Injectable hydrogels have a variety of applications, including regenerative medicine, tissue engineering and controlled drug delivery. In this paper, we reported on a pure protein hydrogel based on tetrameric recombinant proteins for the potential drug delivery application. This protein hydrogel was formed instantly by simply mixing two recombinant proteins (ULD-TIP1 and ULD-GGGWRESAI) through the specific protein-peptide interaction. The protein hydrogel was characterized by rheology and scanning electron microscopy (SEM). In vitro cytotoxicity test indicated that the developed protein hydrogel had no apparent cytotoxicity against L-929 cells and HCEC cells after 48h incubation. The formed protein hydrogels was gradually degraded after incubation in phosphate buffered solution (PBS, pH=7.4) for a period of 144h study, as indicated by in vitro degradation test. Encapsulation of model drug (sodium diclofenac; DIC) were achieved by simple mixing of drugs with hydrogelator and the entrapped drugs was almost completely released from hydrogels within 24h via a diffusion manner. As a conclusion, the simple and mild preparation procedure and good biocompatibility of protein hydrogel would render its good promising candidate for drug delivery applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Peptides, proteins and peptide/protein-polymer conjugates as drug delivery system.

Science.gov (United States)

Mukherjee, Biswajit; Karmakar, Swapna D; Hossain, Chowdhury M; Bhattacharya, Sanchari

2014-01-01

In the last few decades, novel drug delivery strategies have been a big priority to the formulation scientists. Peptides and proteins have drawn a special attention for their wide scope in the area. Serum albumin, transferrin, recom- binant proteins, virus capsids etc. are used as carrier for drug and biomolecules. Conjugates of polymers with proteins have also shown strong potency in the field of drug delivery. Polyethylene glycol is one of the most successful polymers that has been used extensively to develop protein conjugated formulations. Besides, polyvinyl pyrrolidone, polylactic-co- glycolic acid, N-(2-hydroxypropyl) methacrylamide copolymer, polyglutamic acid have also been investigated. In this re- view, we will highlight on the most recent overview of various advantages, limitations and marketed products of proteins, peptides and protein/peptide-polymer conjugates as drug carriers, such products in clinical trials and their various uses in the field of modern drug delivery. Understanding the key features of these materials and the vigorous research in this field will develop new drug formulations that will combat various types of life-threatening diseases.

Clinical relevance of drug binding to plasma proteins

Science.gov (United States)

Ascenzi, Paolo; Fanali, Gabriella; Fasano, Mauro; Pallottini, Valentina; Trezza, Viviana

2014-12-01

Binding to plasma proteins highly influences drug efficacy, distribution, and disposition. Serum albumin, the most abundant protein in plasma, is a monomeric multi-domain macromolecule that displays an extraordinary ligand binding capacity, providing a depot and carrier for many endogenous and exogenous compounds, such as fatty acids and most acidic drugs. α-1-Acid glycoprotein, the second main plasma protein, is a glycoprotein physiologically involved in the acute phase reaction and is the main carrier for basic and neutral drugs. High- and low-density lipoproteins play a limited role in drug binding and are natural drug delivery system only for few lipophilic drugs or lipid-based formulations. Several factors influence drug binding to plasma proteins, such as pathological conditions, concurrent administration of drugs, sex, and age. Any of these factors, in turn, influences drug efficacy and toxicity. Here, biochemical, biomedical, and biotechnological aspects of drug binding to plasma proteins are reviewed.

Supplementary Material for: Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

KAUST Repository

Phelan, Jody

2016-01-01

Abstract Background Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. Methods To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. Results The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. Conclusions Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel

Microencapsulation of protein drugs for drug delivery: strategy, preparation, and applications.

Science.gov (United States)

Ma, Guanghui

2014-11-10

Bio-degradable poly(lactide) (PLA)/poly(lactide-glycolide) (PLGA) and chitosan microspheres (or microcapsules) have important applications in Drug Delivery Systems (DDS) of protein/peptide drugs. By encapsulating protein/peptide drugs in the microspheres, the serum drug concentration can be maintained at a higher constant value for a prolonged time, or injection formulation can be changed to orally or mucosally administered formulation. PLA/PLGA and chitosan are most often used in injection formulation and oral formulation. However, in the preparation and applications of PLA/PLGA and chitosan microspheres containing protein/peptide drugs, the problems of broad size distribution and poor reproducibility of microspheres, and deactivation of protein during the preparation, storage and release, are still big challenges. In this article, the techniques for control of the diameter of microspheres and microcapsules will be introduced at first, then the strategies about how to maintain the bioactivity of protein drugs during preparation and drug release will be reviewed and developed in our research group. The membrane emulsification techniques including direct membrane emulsification and rapid membrane emulsification processes were developed to prepare uniform-sized microspheres, the diameter of microspheres can be controlled from submicron to 100μm by these two processes, and the reproducibility of products can be guaranteed. Furthermore, compared with conventional stirring method, the big advantages of membrane emulsification process were that the uniform microspheres with much higher encapsulation efficiency can be obtained, and the release behavior can be adjusted by selecting microsphere size. Mild membrane emulsification condition also can prevent the deactivation of proteins, which frequently occurred under high shear force in mechanical stirring, sonification, and homogenization methods. The strategies for maintaining the bioactivity of protein drug were

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

Science.gov (United States)

Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

Peptide and protein delivery using new drug delivery systems.

Science.gov (United States)

Jain, Ashish; Jain, Aviral; Gulbake, Arvind; Shilpi, Satish; Hurkat, Pooja; Jain, Sanjay K

2013-01-01

Pharmaceutical and biotechnological research sorts protein drug delivery systems by importance based on their various therapeutic applications. The effective and potent action of the proteins/peptides makes them the drugs of choice for the treatment of numerous diseases. Major research issues in protein delivery include the stabilization of proteins in delivery devices and the design of appropriate target-specific protein carriers. Many efforts have been made for effective delivery of proteins/peptidal drugs through various routes of administrations for successful therapeutic effects. Nanoparticles made of biodegradable polymers such as poly lactic acid, polycaprolactone, poly(lactic-co-glycolic acid), the poly(fumaric-co-sebacic) anhydride chitosan, and modified chitosan, as well as solid lipids, have shown great potential in the delivery of proteins/peptidal drugs. Moreover, scientists also have used liposomes, PEGylated liposomes, niosomes, and aquasomes, among others, for peptidal drug delivery. They also have developed hydrogels and transdermal drug delivery systems for peptidal drug delivery. A receptor-mediated delivery system is another attractive strategy to overcome the limitation in drug absorption that enables the transcytosis of the protein across the epithelial barrier. Modification such as PEGnology is applied to various proteins and peptides of the desired protein and peptides also increases the circulating life, solubility and stability, pharmacokinetic properties, and antigenicity of protein. This review focuses on various approaches for effective protein/peptidal drug delivery, with special emphasis on insulin delivery.

Smarter Drugs: How Protein Crystallography Revolutionizes Drug Design

International Nuclear Information System (INIS)

Smith, Clyde

2005-01-01

According to Smith, protein crystallography allows scientists to design drugs in a much more efficient way than the standard methods traditionally used by large drug companies, which can cost close to a billion dollars and take 10 to 15 years. 'A lot of the work can be compressed down,' Smith said. Protein crystallography enables researchers to learn the structure of molecules involved in disease and health. Seeing the loops, folds and placement of atoms in anything from a virus to a healthy cell membrane gives important information about how these things work - and how to encourage, sidestep or stop their functions. Drug design can be much faster when the relationship between structure and function tells you what area of a molecule to target. Smith will use a timeline to illustrate the traditional methods of drug development and the new ways it can be done now. 'It is very exciting work. There have been some failures, but many successes too.' A new drug to combat the flu was developed in a year or so. Smith will tell us how. He will also highlight drugs developed to combat HIV, Tuberculosis, hypertension and Anthrax.

Modeling and protein engineering studies of active and inactive states of human dopamine D2 receptor (D2R) and investigation of drug/receptor interactions.

Science.gov (United States)

Salmas, Ramin Ekhteiari; Yurtsever, Mine; Stein, Matthias; Durdagi, Serdar

2015-05-01

Homology model structures of the dopamine D2 receptor (D2R) were generated starting from the active and inactive states of β2-adrenergic crystal structure templates. To the best of our knowledge, the active conformation of D2R was modeled for the first time in this study. The homology models are built and refined using MODELLER and ROSETTA programs. Top-ranked models have been validated with ligand docking simulations and in silico Alanine-scanning mutagenesis studies. The derived extra-cellular loop region of the protein models is directed toward the binding site cavity which is often involved in ligand binding. The binding sites of protein models were refined using induced fit docking to enable the side-chain refinement during ligand docking simulations. The derived models were then tested using molecular modeling techniques on several marketed drugs for schizophrenia. Alanine-scanning mutagenesis and molecular docking studies gave similar results for marketed drugs tested. We believe that these new D2 receptor models will be very useful for a better understanding of the mechanisms of action of drugs to be targeted to the binding sites of D2Rs and they will contribute significantly to drug design studies involving G-protein-coupled receptors in the future.

Phenytoin-Bovine Serum Albumin interactions - modeling plasma protein - drug binding: A multi-spectroscopy and in silico-based correlation

Science.gov (United States)

Suresh, P. K.; Divya, Naik; Nidhi, Shah; Rajasekaran, R.

2018-03-01

The study focused on the analysis of the nature and site of binding of Phenytoin (PHT) -(a model hydrophobic drug) with Bovine Serum Albumin (BSA) (a model protein used as a surrogate for HSA). Interactions with defined amounts of Phenytoin and BSA demonstrated a blue shift (hypsochromic -change in the microenvironment of the tryptophan residue with decrease in the polar environment and more of hydrophobicity) with respect to the albumin protein and a red shift (bathochromic -hydrophobicity and polarity related changes) in the case of the model hydrophobic drug. This shift, albeit lower in magnitude, has been substantiated by a fairly convincing, Phenytoin-mediated quenching of the endogenous fluorophore in BSA. Spectral shifts studied at varying pH, temperatures and incubation periods (at varying concentrations of PHT with a defined/constant BSA concentration) showed no significant differences (data not shown). FTIR analysis provided evidence of the interaction of PHT with BSA with a stretching vibration of 1737.86 cm- 1, apart from the vibrations characteristically associated with the amine and carboxyl groups respectively. Our in vitro findings were extended to molecular docking of BSA with PHT (with the different ionized forms of the drug) and the subsequent LIGPLOT-based analysis. In general, a preponderance of hydrophobic interactions was observed. These hydrophobic interactions corroborate the tryptophan-based spectral shifts and the fluorescence quenching data. These results substantiates our hitherto unreported in vitro/in silico experimental flow and provides a basis for screening other hydrophobic drugs in its class.

Preclinical models used for immunogenicity prediction of therapeutic proteins.

Science.gov (United States)

Brinks, Vera; Weinbuch, Daniel; Baker, Matthew; Dean, Yann; Stas, Philippe; Kostense, Stefan; Rup, Bonita; Jiskoot, Wim

2013-07-01

All therapeutic proteins are potentially immunogenic. Antibodies formed against these drugs can decrease efficacy, leading to drastically increased therapeutic costs and in rare cases to serious and sometimes life threatening side-effects. Many efforts are therefore undertaken to develop therapeutic proteins with minimal immunogenicity. For this, immunogenicity prediction of candidate drugs during early drug development is essential. Several in silico, in vitro and in vivo models are used to predict immunogenicity of drug leads, to modify potentially immunogenic properties and to continue development of drug candidates with expected low immunogenicity. Despite the extensive use of these predictive models, their actual predictive value varies. Important reasons for this uncertainty are the limited/insufficient knowledge on the immune mechanisms underlying immunogenicity of therapeutic proteins, the fact that different predictive models explore different components of the immune system and the lack of an integrated clinical validation. In this review, we discuss the predictive models in use, summarize aspects of immunogenicity that these models predict and explore the merits and the limitations of each of the models.

A Mathematical Model of the Effect of Immunogenicity on Therapeutic Protein Pharmacokinetics

OpenAIRE

Chen, Xiaoying; Hickling, Timothy; Kraynov, Eugenia; Kuang, Bing; Parng, Chuenlei; Vicini, Paolo

2013-01-01

A mathematical pharmacokinetic/anti-drug-antibody (PK/ADA) model was constructed for quantitatively assessing immunogenicity for therapeutic proteins. The model is inspired by traditional pharmacokinetic/pharmacodynamic (PK/PD) models, and is based on the observed impact of ADA on protein drug clearance. The hypothesis for this work is that altered drug PK contains information about the extent and timing of ADA generation. By fitting drug PK profiles while accounting for ADA-mediated drug cle...

INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.

Science.gov (United States)

Verkhivker, Gennady M

2016-01-01

The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling

Systematic identification of proteins that elicit drug side effects

DEFF Research Database (Denmark)

Kuhn, Michael; Al Banchaabouchi, Mumna; Campillos, Monica

2013-01-01

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins...... that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause......) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations....

Bioengineered protein-based nanocage for drug delivery.

Science.gov (United States)

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Protein Complex Production from the Drug Discovery Standpoint.

Science.gov (United States)

Moarefi, Ismail

2016-01-01

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

Targeted Delivery of Protein Drugs by Nanocarriers

Directory of Open Access Journals (Sweden)

Antonella Battisti

2010-03-01

Full Text Available Recent advances in biotechnology demonstrate that peptides and proteins are the basis of a new generation of drugs. However, the transportation of protein drugs in the body is limited by their high molecular weight, which prevents the crossing of tissue barriers, and by their short lifetime due to immuno response and enzymatic degradation. Moreover, the ability to selectively deliver drugs to target organs, tissues or cells is a major challenge in the treatment of several human diseases, including cancer. Indeed, targeted delivery can be much more efficient than systemic application, while improving bioavailability and limiting undesirable side effects. This review describes how the use of targeted nanocarriers such as nanoparticles and liposomes can improve the pharmacokinetic properties of protein drugs, thus increasing their safety and maximizing the therapeutic effect.

Functionalization of protein-based nanocages for drug delivery applications.

Science.gov (United States)

Schoonen, Lise; van Hest, Jan C M

2014-07-07

Traditional drug delivery strategies involve drugs which are not targeted towards the desired tissue. This can lead to undesired side effects, as normal cells are affected by the drugs as well. Therefore, new systems are now being developed which combine targeting functionalities with encapsulation of drug cargo. Protein nanocages are highly promising drug delivery platforms due to their perfectly defined structures, biocompatibility, biodegradability and low toxicity. A variety of protein nanocages have been modified and functionalized for these types of applications. In this review, we aim to give an overview of different types of modifications of protein-based nanocontainers for drug delivery applications.

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

Science.gov (United States)

Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

2010-10-29

Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

Protein Nanoparticles as Drug Delivery Carriers for Cancer Therapy

Directory of Open Access Journals (Sweden)

Warangkana Lohcharoenkal

2014-01-01

Full Text Available Nanoparticles have increasingly been used for a variety of applications, most notably for the delivery of therapeutic and diagnostic agents. A large number of nanoparticle drug delivery systems have been developed for cancer treatment and various materials have been explored as drug delivery agents to improve the therapeutic efficacy and safety of anticancer drugs. Natural biomolecules such as proteins are an attractive alternative to synthetic polymers which are commonly used in drug formulations because of their safety. In general, protein nanoparticles offer a number of advantages including biocompatibility and biodegradability. They can be prepared under mild conditions without the use of toxic chemicals or organic solvents. Moreover, due to their defined primary structure, protein-based nanoparticles offer various possibilities for surface modifications including covalent attachment of drugs and targeting ligands. In this paper, we review the most significant advancements in protein nanoparticle technology and their use in drug delivery arena. We then examine the various sources of protein materials that have been used successfully for the construction of protein nanoparticles as well as their methods of preparation. Finally, we discuss the applications of protein nanoparticles in cancer therapy.

Protein nanoparticles as drug delivery carriers for cancer therapy.

Science.gov (United States)

Lohcharoenkal, Warangkana; Wang, Liying; Chen, Yi Charlie; Rojanasakul, Yon

2014-01-01

Nanoparticles have increasingly been used for a variety of applications, most notably for the delivery of therapeutic and diagnostic agents. A large number of nanoparticle drug delivery systems have been developed for cancer treatment and various materials have been explored as drug delivery agents to improve the therapeutic efficacy and safety of anticancer drugs. Natural biomolecules such as proteins are an attractive alternative to synthetic polymers which are commonly used in drug formulations because of their safety. In general, protein nanoparticles offer a number of advantages including biocompatibility and biodegradability. They can be prepared under mild conditions without the use of toxic chemicals or organic solvents. Moreover, due to their defined primary structure, protein-based nanoparticles offer various possibilities for surface modifications including covalent attachment of drugs and targeting ligands. In this paper, we review the most significant advancements in protein nanoparticle technology and their use in drug delivery arena. We then examine the various sources of protein materials that have been used successfully for the construction of protein nanoparticles as well as their methods of preparation. Finally, we discuss the applications of protein nanoparticles in cancer therapy.

Protein Crystallography: A 'Must' Technology for Drug Design

International Nuclear Information System (INIS)

Matsuzaki, Takao

2004-01-01

The history of drug-related protein crystallography and drug design is reviewed to show that 'Lead Generation' is high-lighted in the pharmaceutical industry nowadays. A new drug design method has been developed. The method gave very high success rate; 10-60 % gave < 100 μM, 90 % gave < 10 mM. The crystal structures of drug-protein complexes have become even more important to give solid experimental bases for e.g. 1,000 designed structures and to find the new mechanisms of drug action

Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

Science.gov (United States)

Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C

2010-09-13

Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.

Molecular imaging of drug-modulated protein-protein interactions in living subjects.

Science.gov (United States)

Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

2004-03-15

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

Physiologically Based Pharmacokinetic Modeling of Therapeutic Proteins.

Science.gov (United States)

Wong, Harvey; Chow, Timothy W

2017-09-01

Biologics or therapeutic proteins are becoming increasingly important as treatments for disease. The most common class of biologics are monoclonal antibodies (mAbs). Recently, there has been an increase in the use of physiologically based pharmacokinetic (PBPK) modeling in the pharmaceutical industry in drug development. We review PBPK models for therapeutic proteins with an emphasis on mAbs. Due to their size and similarity to endogenous antibodies, there are distinct differences between PBPK models for small molecules and mAbs. The high-level organization of a typical mAb PBPK model consists of a whole-body PBPK model with organ compartments interconnected by both blood and lymph flows. The whole-body PBPK model is coupled with tissue-level submodels used to describe key mechanisms governing mAb disposition including tissue efflux via the lymphatic system, elimination by catabolism, protection from catabolism binding to the neonatal Fc (FcRn) receptor, and nonlinear binding to specific pharmacological targets of interest. The use of PBPK modeling in the development of therapeutic proteins is still in its infancy. Further application of PBPK modeling for therapeutic proteins will help to define its developing role in drug discovery and development. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

S-Glutathionylation and Redox Protein Signaling in Drug Addiction.

Science.gov (United States)

Womersley, Jacqueline S; Uys, Joachim D

2016-01-01

Drug addiction is a chronic relapsing disorder that comes at a high cost to individuals and society. Therefore understanding the mechanisms by which drugs exert their effects is of prime importance. Drugs of abuse increase the production of reactive oxygen and nitrogen species resulting in oxidative stress. This change in redox homeostasis increases the conjugation of glutathione to protein cysteine residues; a process called S-glutathionylation. Although traditionally regarded as a protective mechanism against irreversible protein oxidation, accumulated evidence suggests a more nuanced role for S-glutathionylation, namely as a mediator in redox-sensitive protein signaling. The reversible modification of protein thiols leading to alteration in function under different physiologic/pathologic conditions provides a mechanism whereby change in redox status can be translated into a functional response. As such, S-glutathionylation represents an understudied means of post-translational protein modification that may be important in the mechanisms underlying drug addiction. This review will discuss the evidence for S-glutathionylation as a redox-sensing mechanism and how this may be involved in the response to drug-induced oxidative stress. The function of S-glutathionylated proteins involved in neurotransmission, dendritic spine structure, and drug-induced behavioral outputs will be reviewed with specific reference to alcohol, cocaine, and heroin. Copyright © 2016. Published by Elsevier Inc.

Characterization of particulate drug delivery systems for oral delivery of Peptide and protein drugs

DEFF Research Database (Denmark)

Christophersen, Philip Carsten; Fano, Mathias; Saaby, Lasse

2015-01-01

Oral drug delivery is a preferred route because of good patient compliance. However, most peptide/ protein drugs are delivered via parenteral routes because of the absorption barriers in the gastrointestinal (GI) tract such as enzymatic degradation by proteases and low permeability acrossthe...... delivery of peptide/protein drugs and to provide an overview of formulationand characterization strategies. For a better understanding of the challenges in oral delivery of peptide/protein drugs, the composition of GI fluids and the digestion processes of different kinds of excipients in the GI tract...... biological membranes. To overcome these barriers, different formulation strategies for oral delivery of biomacromolecules have been proposed, including lipid based formulations and polymer-based particulate drug delivery systems (DDS). The aim of this review is to summarize the existing knowledge about oral...

Data-driven prediction of adverse drug reactions induced by drug-drug interactions.

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Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Kumar, Kamal; Yu, Xueping; Wallqvist, Anders; Reifman, Jaques

2017-06-08

The expanded use of multiple drugs has increased the occurrence of adverse drug reactions (ADRs) induced by drug-drug interactions (DDIs). However, such reactions are typically not observed in clinical drug-development studies because most of them focus on single-drug therapies. ADR reporting systems collect information on adverse health effects caused by both single drugs and DDIs. A major challenge is to unambiguously identify the effects caused by DDIs and to attribute them to specific drug interactions. A computational method that provides prospective predictions of potential DDI-induced ADRs will help to identify and mitigate these adverse health effects. We hypothesize that drug-protein interactions can be used as independent variables in predicting ADRs. We constructed drug pair-protein interaction profiles for ~800 drugs using drug-protein interaction information in the public domain. We then constructed statistical models to score drug pairs for their potential to induce ADRs based on drug pair-protein interaction profiles. We used extensive clinical database information to construct categorical prediction models for drug pairs that are likely to induce ADRs via synergistic DDIs and showed that model performance deteriorated only slightly, with a moderate amount of false positives and false negatives in the training samples, as evaluated by our cross-validation analysis. The cross validation calculations showed an average prediction accuracy of 89% across 1,096 ADR models that captured the deleterious effects of synergistic DDIs. Because the models rely on drug-protein interactions, we made predictions for pairwise combinations of 764 drugs that are currently on the market and for which drug-protein interaction information is available. These predictions are publicly accessible at http://avoid-db.bhsai.org . We used the predictive models to analyze broader aspects of DDI-induced ADRs, showing that ~10% of all combinations have the potential to induce ADRs

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

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Jung Me Hwang

2011-12-01

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

Quantitative chemogenomics: machine-learning models of protein-ligand interaction.

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Andersson, Claes R; Gustafsson, Mats G; Strömbergsson, Helena

2011-01-01

Chemogenomics is an emerging interdisciplinary field that lies in the interface of biology, chemistry, and informatics. Most of the currently used drugs are small molecules that interact with proteins. Understanding protein-ligand interaction is therefore central to drug discovery and design. In the subfield of chemogenomics known as proteochemometrics, protein-ligand-interaction models are induced from data matrices that consist of both protein and ligand information along with some experimentally measured variable. The two general aims of this quantitative multi-structure-property-relationship modeling (QMSPR) approach are to exploit sparse/incomplete information sources and to obtain more general models covering larger parts of the protein-ligand space, than traditional approaches that focuses mainly on specific targets or ligands. The data matrices, usually obtained from multiple sparse/incomplete sources, typically contain series of proteins and ligands together with quantitative information about their interactions. A useful model should ideally be easy to interpret and generalize well to new unseen protein-ligand combinations. Resolving this requires sophisticated machine-learning methods for model induction, combined with adequate validation. This review is intended to provide a guide to methods and data sources suitable for this kind of protein-ligand-interaction modeling. An overview of the modeling process is presented including data collection, protein and ligand descriptor computation, data preprocessing, machine-learning-model induction and validation. Concerns and issues specific for each step in this kind of data-driven modeling will be discussed. © 2011 Bentham Science Publishers

Convective transport of highly plasma protein bound drugs facilitates direct penetration into deep tissues after topical application

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Dancik, Yuri; Anissimov, Yuri G; Jepps, Owen G; Roberts, Michael S

2012-01-01

AIMS To relate the varying dermal, subcutaneous and muscle microdialysate concentrations found in man after topical application to the nature of the drug applied and to the underlying physiology. METHODS We developed a physiologically based pharmacokinetic model in which transport to deeper tissues was determined by tissue diffusion, blood, lymphatic and intersitial flow transport and drug properties. The model was applied to interpret published human microdialysis data, estimated in vitro dermal diffusion and protein binding affinity of drugs that have been previously applied topically in vivo and measured in deep cutaneous tissues over time. RESULTS Deeper tissue microdialysis concentrations for various drugs in vivo vary widely. Here, we show that carriage by the blood to the deeper tissues below topical application sites facilitates the transport of highly plasma protein bound drugs that penetrate the skin, leading to rapid and significant concentrations in those tissues. Hence, the fractional concentration for the highly plasma protein bound diclofenac in deeper tissues is 0.79 times that in a probe 4.5 mm below a superficial probe whereas the corresponding fractional concentration for the poorly protein bound nicotine is 0.02. Their corresponding estimated in vivo lag times for appearance of the drugs in the deeper probes were 1.1 min for diclofenac and 30 min for nicotine. CONCLUSIONS Poorly plasma protein bound drugs are mainly transported to deeper tissues after topical application by tissue diffusion whereas the transport of highly plasma protein bound drugs is additionally facilitated by convective blood, lymphatic and interstitial transport to deep tissues. PMID:21999217

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

2015-01-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina

2015-07-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Drug disposition in obesity and protein-energy malnutrition.

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Boullata, Joseph I

2010-11-01

Clinical response to medication can differ between patients. Among the known sources of variability is an individual's nutrition status. This review defines some pharmacokinetic terms, provides relevant body size metrics and describes the physiologic influences of protein-energy malnutrition and obesity on drug disposition. Weight-based drug dosing, which presumes a healthy BMI, can be problematic in the protein-energy malnourished or obese patient. The use of total body weight, lean body weight, or an adjusted body weight depends on the drug and how it is differently handled in malnutrition or obesity. Most of the recognized influences are seen in drug distribution and drug elimination as a result of altered body composition and function. Distribution characteristics of each drug are determined by several drug-related factors (e.g. tissue affinity) in combination with body-related factors (e.g. composition). Drug elimination occurs through metabolic and excretory pathways that can also vary with body composition. The current data are limited to select drugs that have been reported in small studies or case reports. In the meantime, a rational approach to evaluate the potential influences of malnutrition and obesity can be used clinically based on available information. Antimicrobials are discussed as a useful example of this approach. Further advancement in this field would require collaboration between experts in body composition and those in drug disposition. Until more data are available, routine monitoring by the clinician of the protein-energy malnourished or obese patient receiving weight-based drug regimens is necessary.

Large-scale prediction of drug–target interactions using protein sequences and drug topological structures

International Nuclear Information System (INIS)

Cao Dongsheng; Liu Shao; Xu Qingsong; Lu Hongmei; Huang Jianhua; Hu Qiannan; Liang Yizeng

2012-01-01

Highlights: ► Drug–target interactions are predicted using an extended SAR methodology. ► A drug–target interaction is regarded as an event triggered by many factors. ► Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. ► Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug–target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug–target interactions in a timely manner. In this article, we aim at extending current structure–activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug–target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug–target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug–target interactions, and show a general compatibility between the new scheme and current SAR

Development of novel drug delivery systems using phage display technology for clinical application of protein drugs.

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Nagano, Kazuya; Tsutsumi, Yasuo

2016-01-01

Attempts are being made to develop therapeutic proteins for cancer, hepatitis, and autoimmune conditions, but their clinical applications are limited, except in the cases of drugs based on erythropoietin, granulocyte colony-stimulating factor, interferon-alpha, and antibodies, owing to problems with fundamental technologies for protein drug discovery. It is difficult to identify proteins useful as therapeutic seeds or targets. Another problem in using bioactive proteins is pleiotropic actions through receptors, making it hard to elicit desired effects without side effects. Additionally, bioactive proteins have poor therapeutic effects owing to degradation by proteases and rapid excretion from the circulatory system. Therefore, it is essential to establish a series of novel drug delivery systems (DDS) to overcome these problems. Here, we review original technologies in DDS. First, we introduce antibody proteomics technology for effective selection of proteins useful as therapeutic seeds or targets and identification of various kinds of proteins, such as cancer-specific proteins, cancer metastasis-related proteins, and a cisplatin resistance-related protein. Especially Ephrin receptor A10 is expressed in breast tumor tissues but not in normal tissues and is a promising drug target potentially useful for breast cancer treatment. Moreover, we have developed a system for rapidly creating functional mutant proteins to optimize the seeds for therapeutic applications and used this system to generate various kinds of functional cytokine muteins. Among them, R1antTNF is a TNFR1-selective antagonistic mutant of TNF and is the first mutein converted from agonist to antagonist. We also review a novel polymer-conjugation system to improve the in vivo stability of bioactive proteins. Site-specific PEGylated R1antTNF is uniform at the molecular level, and its bioactivity is similar to that of unmodified R1antTNF. In the future, we hope that many innovative protein drugs will be

Protein and Peptide in Drug Targeting and its Therapeutic Approach

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Raj K. Keservani

2015-09-01

Full Text Available Aim: The main aim of this review article is to provide information like advantages of protein and peptides via different routes of drug administration, targeted to a particular site and its implication in drug delivery system. Methods: To that aim, from the web sites of PubMed, HCAplus, Thomson, and Registry were used as the main sources to perform the search for the most significant research articles published on the subject. The information was then carefully analyzed, highlighting the most important results in the development of protein and peptide drug targeting as well as its therapeutic activity. Results: In recent years many researchers use protein and peptide as a target site of drug by a different delivery system. Proteins and peptides are used as specific and effective therapeutic agents, due to instability and side effects their use is complicated. Protein kinases are important regulators of most, if not all, biological processes. Abnormal activity of proteins and peptides has been implicated in many human diseases, such as diabetes, cancer and neurodegenerative disorders. Conclusions: It is concluded that the protein and peptide were used in drug targeting to specific site and also used in different diseased states like cancer, diabetes, immunomodulating, neurodegenerative effects and antimicrobial activity.

Photoactive assemblies of organic compounds and biomolecules: drug-protein supramolecular systems.

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Vayá, Ignacio; Lhiaubet-Vallet, Virginie; Jiménez, M Consuelo; Miranda, Miguel A

2014-06-21

The properties of singlet and triplet excited states are strongly medium-dependent. Hence, these species constitute valuable tools as reporters to probe compartmentalised microenvironments, including drug@protein supramolecular systems. In the present review, the attention is focused on the photophysical properties of the probe drugs (rather than those of the protein chromophores) using transport proteins (serum albumins and α1-acid glycoproteins) as hosts. Specifically, fluorescence measurements allow investigation of the structural and dynamic properties of biomolecules or their complexes. Thus, the emission quantum yields and the decay kinetics of the drug singlet excited states provide key information to determine important parameters such as the stoichiometry of the complex, the binding constant, the relative degrees of occupancy of the different compartments, etc. Application of the FRET concept allows determination of donor-acceptor interchromophoric distances. In addition, anisotropy measurements can be related to the orientation of the drug within the binding sites, where the degrees of freedom for conformational relaxation are restricted. Transient absorption spectroscopy is also a potentially powerful tool to investigate the binding of drugs to proteins, where formation of encapsulated triplet excited states is favoured over other possible processes leading to ionic species (i.e. radical ions), and their photophysical properties are markedly sensitive to the microenvironment experienced within the protein binding sites. Even under aerobic conditions, the triplet lifetimes of protein-complexed drugs are remarkably long, which provides a broad dynamic range for identification of distinct triplet populations or for chiral discrimination. Specific applications of the laser flash photolysis technique include the determination of drug distribution among the bulk solution and the protein binding sites, competition of two types of proteins to bind a drug

Touching proteins with virtual bare hands - Visualizing protein-drug complexes and their dynamics in self-made virtual reality using gaming hardware

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Ratamero, Erick Martins; Bellini, Dom; Dowson, Christopher G.; Römer, Rudolf A.

2018-06-01

The ability to precisely visualize the atomic geometry of the interactions between a drug and its protein target in structural models is critical in predicting the correct modifications in previously identified inhibitors to create more effective next generation drugs. It is currently common practice among medicinal chemists while attempting the above to access the information contained in three-dimensional structures by using two-dimensional projections, which can preclude disclosure of useful features. A more accessible and intuitive visualization of the three-dimensional configuration of the atomic geometry in the models can be achieved through the implementation of immersive virtual reality (VR). While bespoke commercial VR suites are available, in this work, we present a freely available software pipeline for visualising protein structures through VR. New consumer hardware, such as the uc(HTC Vive) and the uc(Oculus Rift) utilized in this study, are available at reasonable prices. As an instructive example, we have combined VR visualization with fast algorithms for simulating intramolecular motions of protein flexibility, in an effort to further improve structure-led drug design by exposing molecular interactions that might be hidden in the less informative static models. This is a paradigmatic test case scenario for many similar applications in computer-aided molecular studies and design.

May disordered protein cause serious drug side effect?

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Tou, Weng Ieong; Chen, Calvin Yu-Chian

2014-04-01

Insomnia is a self-reported disease where patients lose their ability to initiate and maintain sleep, leading to daytime performance impairment. Several drug targets to ameliorate insomnia symptoms have been discovered; however, these drug targets lead to serious side effects. Thus, we characterize the structural properties of these sleep-related receptors and the clock complex and discuss a possible drug design that will reduce side effects. Computational prediction shows that disordered property is shared. Over 30% of the structure of CLOCK, PER1/2/3, BMAL-1, muscarinic acetylcholine receptor-M1, melatonin receptor and casein kinase I are structurally disordered (the remaining proteins represent insomnia drugs might be closely related to the protein architecture. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multidrug and toxin extrusion proteins as transporters of antimicrobial drugs.

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Nies, Anne T; Damme, Katja; Schaeffeler, Elke; Schwab, Matthias

2012-12-01

Antimicrobial drugs are essential in the treatment of infectious diseases. A better understanding of transport processes involved in drug disposition will improve the predictability of drug-drug interactions with consequences for drug response. Multidrug And Toxin Extrusion (MATE; SLC47A) proteins are efflux transporters mediating the excretion of several antimicrobial drugs as well as other organic compounds into bile and urine, thereby contributing to drug disposition. This review summarizes current knowledge of the structural and molecular features of human MATE transporters including their functional role in drug transport with a specific focus on antimicrobial drugs. The PubMed database was searched using the terms "MATE1," "MATE-2K," "MATE2," "SLC47A1," "SLC47A2," and "toxin extrusion protein" (up to June 2012). MATE proteins have been recognized as important transporters mediating the final excretion step of cationic drugs into bile and urine. These include the antiviral drugs acyclovir, amprenavir, and ganciclovir, the antibiotics cephalexin, cephradine and levofloxacin, as well as the antimalarial agents chloroquine and quinine. It is therefore important to enhance our understanding of the role of MATEs in drug extrusion with particular emphasis on the functional consequences of genetic variants on disposition of these antimicrobial drugs.

PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins.

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Hussein, Hiba Abi; Borrel, Alexandre; Geneix, Colette; Petitjean, Michel; Regad, Leslie; Camproux, Anne-Claude

2015-07-01

Predicting protein pocket's ability to bind drug-like molecules with high affinity, i.e. druggability, is of major interest in the target identification phase of drug discovery. Therefore, pocket druggability investigations represent a key step of compound clinical progression projects. Currently computational druggability prediction models are attached to one unique pocket estimation method despite pocket estimation uncertainties. In this paper, we propose 'PockDrug-Server' to predict pocket druggability, efficient on both (i) estimated pockets guided by the ligand proximity (extracted by proximity to a ligand from a holo protein structure) and (ii) estimated pockets based solely on protein structure information (based on amino atoms that form the surface of potential binding cavities). PockDrug-Server provides consistent druggability results using different pocket estimation methods. It is robust with respect to pocket boundary and estimation uncertainties, thus efficient using apo pockets that are challenging to estimate. It clearly distinguishes druggable from less druggable pockets using different estimation methods and outperformed recent druggability models for apo pockets. It can be carried out from one or a set of apo/holo proteins using different pocket estimation methods proposed by our web server or from any pocket previously estimated by the user. PockDrug-Server is publicly available at: http://pockdrug.rpbs.univ-paris-diderot.fr. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

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Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2018-01-01

Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

PDTD: a web-accessible protein database for drug target identification

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Gao Zhenting

2008-02-01

Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

Blood-brain barrier drug delivery of IgG fusion proteins with a transferrin receptor monoclonal antibody.

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Pardridge, William M

2015-02-01

Biologic drugs are large molecules that do not cross the blood- brain barrier (BBB). Brain penetration is possible following the re-engineering of the biologic drug as an IgG fusion protein. The IgG domain is a MAb against an endogenous BBB receptor such as the transferrin receptor (TfR). The TfRMAb acts as a molecular Trojan horse to ferry the fused biologic drug into the brain via receptor-mediated transport on the endogenous BBB TfR. This review discusses TfR isoforms, models of BBB transport of transferrin and TfRMAbs, and the genetic engineering of TfRMAb fusion proteins, including BBB penetrating IgG-neurotrophins, IgG-decoy receptors, IgG-lysosomal enzyme therapeutics and IgG-avidin fusion proteins, as well as BBB transport of bispecific antibodies formed by fusion of a therapeutic antibody to a TfRMAb targeting antibody. Also discussed are quantitative aspects of the plasma pharmacokinetics and brain uptake of TfRMAb fusion proteins, as compared to the brain uptake of small molecules, and therapeutic applications of TfRMAb fusion proteins in mouse models of neural disease, including Parkinson's disease, stroke, Alzheimer's disease and lysosomal storage disorders. The review covers the engineering of TfRMAb-avidin fusion proteins for BBB targeted delivery of biotinylated peptide radiopharmaceuticals, low-affinity TfRMAb Trojan horses and the safety pharmacology of chronic administration of TfRMAb fusion proteins. The BBB delivery of biologic drugs is possible following re-engineering as a fusion protein with a molecular Trojan horse such as a TfRMAb. The efficacy of this technology will be determined by the outcome of future clinical trials.

Systematic synergy modeling: understanding drug synergy from a systems biology perspective.

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Chen, Di; Liu, Xi; Yang, Yiping; Yang, Hongjun; Lu, Peng

2015-09-16

Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose-response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and "omic"-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.

Mechanisms of photosensitization by drugs: Involvement of tyrosines in the photomodification of proteins mediated by tiaprofenic acid in vitro.

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Miranda, M A; Castell, J V; Sarabia, Z; Hernández, D; Puertes, I; Morera, I M; Gómez-Lechón, M J

1997-10-01

The photosensitizing potential of drugs must be related to their photoreactivity towards the target biomolecules. In this context, a representative photosensitizing drug (tiaprofenic acid) was co-irradiated with a model protein, bovine serum albumin (BSA). This led to a significant degree of protein crosslinking and to the formation of trace amounts of drug-BSA photoadducts. Amino acid analysis of the hydrolysed (HC1) protein showed that His and Tyr undergo a dramatic decrease (approx. 90%) as a consequence of drug-mediated photodynamic processes. When the drug was irradiated in the presence of the pure amino acids, extensive phototransformation of the latter was observed. Other photosensitizing drugs gave rise to similar processes when irradiated in the presence of BSA or the isolated amino acids. In conclusion, histidine and tyrosine appear to be key sites for the photosensitized damage to proteins. Photodegradation of the isolated amino acids in vitro may be an indicator of the photosensitizing potential of drugs.

Hidden markov model for the prediction of transmembrane proteins using MATLAB.

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Chaturvedi, Navaneet; Shanker, Sudhanshu; Singh, Vinay Kumar; Sinha, Dhiraj; Pandey, Paras Nath

2011-01-01

Since membranous proteins play a key role in drug targeting therefore transmembrane proteins prediction is active and challenging area of biological sciences. Location based prediction of transmembrane proteins are significant for functional annotation of protein sequences. Hidden markov model based method was widely applied for transmembrane topology prediction. Here we have presented a revised and a better understanding model than an existing one for transmembrane protein prediction. Scripting on MATLAB was built and compiled for parameter estimation of model and applied this model on amino acid sequence to know the transmembrane and its adjacent locations. Estimated model of transmembrane topology was based on TMHMM model architecture. Only 7 super states are defined in the given dataset, which were converted to 96 states on the basis of their length in sequence. Accuracy of the prediction of model was observed about 74 %, is a good enough in the area of transmembrane topology prediction. Therefore we have concluded the hidden markov model plays crucial role in transmembrane helices prediction on MATLAB platform and it could also be useful for drug discovery strategy. The database is available for free at bioinfonavneet@gmail.comvinaysingh@bhu.ac.in.

A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

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Yadav, Manoj Kumar; Singh, Amisha; Swati, D

2014-08-01

Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.

Recent advances in (therapeutic protein drug development [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

H.A. Daniel Lagassé

2017-02-01

Full Text Available Therapeutic protein drugs are an important class of medicines serving patients most in need of novel therapies. Recently approved recombinant protein therapeutics have been developed to treat a wide variety of clinical indications, including cancers, autoimmunity/inflammation, exposure to infectious agents, and genetic disorders. The latest advances in protein-engineering technologies have allowed drug developers and manufacturers to fine-tune and exploit desirable functional characteristics of proteins of interest while maintaining (and in some cases enhancing product safety or efficacy or both. In this review, we highlight the emerging trends and approaches in protein drug development by using examples of therapeutic proteins approved by the U.S. Food and Drug Administration over the previous five years (2011–2016, namely January 1, 2011, through August 31, 2016.

Recent trends in drug delivery system using protein nanoparticles.

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Sripriyalakshmi, S; Jose, Pinkybel; Ravindran, Aswathy; Anjali, C H

2014-09-01

Engineered nanoparticles that can facilitate drug formulation and passively target tumours have been under extensive research in recent years. These successes have driven a new wave of significant innovation in the generation of advanced particles. The fate and transport of diagnostic nanoparticles would significantly depend on nonselective drug delivery, and hence the use of high drug dosage is implemented. In this perspective, nanocarrier-based drug targeting strategies can be used which improve the selective delivery of drugs to the site of action, i.e. drug targeting. Pharmaceutical industries majorly focus on reducing the toxicity and side effects of drugs but only recently it has been realised that carrier systems themselves may pose risks to the patient. Proteins are compatible with biological systems and they are biodegradable. They offer a multitude of moieties for modifications to tailor drug binding, imaging or targeting entities. Thus, protein nanoparticles provide outstanding contributions as a carrier for drug delivery systems. This review summarises recent progress in particle-based therapeutic delivery and discusses important concepts in particle design and biological barriers for developing the next generation of particles drug delivery systems.

Investigation of molecular mechanisms of action of chelating drugs on protein-lipid model membranes by X-ray fluorescence

International Nuclear Information System (INIS)

Novikova, N. N.; Zheludeva, S. I.; Koval'chuk, M. V.; Stepina, N. D.; Erko, A. I.; Yur'eva, E. A.

2009-01-01

Protein-lipid films based on the enzyme alkaline phosphatase were subjected to the action of chelating drugs, which are used for accelerating the removal of heavy metals from the human body, and the elemental composition of the resulting films was investigated. Total-reflection X-ray fluorescence measurements were performed at the Berlin Electron Storage Ring Company for Synchrotron Radiation (BESSY) in Germany. A comparative estimation of the protective effect of four drugs (EDTA, succimer, xydiphone, and mediphon) on membrane-bound enzymes damaged by lead ions was made. The changes in the elemental composition of the protein-lipid films caused by high doses of chelating drugs were investigated. It was shown that state-of-the-art X-ray techniques can, in principle, be used to develop new methods for the in vitro evaluation of the efficiency of drugs, providing differential data on their actions.

New potential nonsteroidal anti-inflammatory drugs with antileukotrienic effects: influence on model proteins with catalytic activity.

Science.gov (United States)

Netopilová, Miloslava; Drsata, Jaroslav; Beránek, Martin; Palicka, Vladimír

2002-01-01

Unspecific and side effects caused by interaction with proteins belong to common problems of many structures synthesized as potential medicaments. Possible in vitro interactions with proteins of a group of phenylsulfonyl benzoic acid derivatives (VUFB 19363, 19369, 19370, 19371, and 19760) as new potential anti-inflammatory compounds with anti-leukotrienic activities were studied in the present work. Three purified enzymes were used as model proteins with catalytic activities: Pig heart aspartate aminotransferase (AST, EC 2.6.1.1), alanine aminotransferase (ALT, EC 2.6.1.2), and glutamate decarboxylase (GAD, EC 4.1.1.15) from E. coli. Catalytic activities during incubation of individual compounds (6 x 10(-5) M solution to 5 x 10(-2) M suspension) at 37 degrees C with enzymes served as criteria of stability and function of the proteins. No immediate influence of any compound studied on enzyme activities was found. Aminotransferase activities were not affected even during incubation up to 20 d. In the case of GAD, the compounds VUFB 19369, 19370, 19371, and 19760 had stabilizing influence on GAD activity during incubation at enzyme concentrations of 11.25 and 5.62 mg prot/l. The lack of an immediate effect of compounds and the stability of enzymes during incubation them are favorable and support the prospective of the compounds as potential drugs.

Influence of multidrug resistance and drug transport proteins on chemotherapy drug metabolism.

Science.gov (United States)

Joyce, Helena; McCann, Andrew; Clynes, Martin; Larkin, Annemarie

2015-05-01

Chemotherapy involving the use of anticancer drugs remains an important strategy in the overall management of patients with metastatic cancer. Acquisition of multidrug resistance remains a major impediment to successful chemotherapy. Drug transporters in cell membranes and intracellular drug metabolizing enzymes contribute to the resistance phenotype and determine the pharmacokinetics of anticancer drugs in the body. ATP-binding cassette (ABC) transporters mediate the transport of endogenous metabolites and xenobiotics including cytotoxic drugs out of cells. Solute carrier (SLC) transporters mediate the influx of cytotoxic drugs into cells. This review focuses on the substrate interaction of these transporters, on their biology and what role they play together with drug metabolizing enzymes in eliminating therapeutic drugs from cells. The majority of anticancer drugs are substrates for the ABC transporter and SLC transporter families. Together, these proteins have the ability to control the influx and the efflux of structurally unrelated chemotherapeutic drugs, thereby modulating the intracellular drug concentration. These interactions have important clinical implications for chemotherapy because ultimately they determine therapeutic efficacy, disease progression/relapse and the success or failure of patient treatment.

Supplementary Material for: Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

KAUST Repository

Phelan, Jody; Coll, Francesc; McNerney, Ruth; Ascher, David; Pires, Douglas; Furnham, Nick; Coeck, Nele; Hill-Cawthorne, Grant; Nair, Mridul; Mallard, Kim; Ramsay, Andrew; Campino, Susana; Hibberd, Martin; Pain, Arnab; Rigouts, Leen; Clark, Taane

2016-01-01

Abstract Background Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure

Comprehensive Analysis of Homologous Proteins for Specific Drug ...

African Journals Online (AJOL)

... minimize drug failures by predicting drug efficacy and toxicity. One of the most important pathogenic bacterium is Aeromonas species which causes tissue damage, acute gastroenteritis and neonatal septicemia. Bacterial proteins are the ultimate target to inhibit their growth and these are the executors of cellular function.

Immunogenicity of therapeutic proteins: the use of animal models.

Science.gov (United States)

Brinks, Vera; Jiskoot, Wim; Schellekens, Huub

2011-10-01

Immunogenicity of therapeutic proteins lowers patient well-being and drastically increases therapeutic costs. Preventing immunogenicity is an important issue to consider when developing novel therapeutic proteins and applying them in the clinic. Animal models are increasingly used to study immunogenicity of therapeutic proteins. They are employed as predictive tools to assess different aspects of immunogenicity during drug development and have become vital in studying the mechanisms underlying immunogenicity of therapeutic proteins. However, the use of animal models needs critical evaluation. Because of species differences, predictive value of such models is limited, and mechanistic studies can be restricted. This review addresses the suitability of animal models for immunogenicity prediction and summarizes the insights in immunogenicity that they have given so far.

High-throughput oxidation screen of antibody-drug conjugates by analytical protein A chromatography following IdeS digest.

Science.gov (United States)

Buecheler, Jakob W; Winzer, Matthias; Weber, Christian; Gieseler, Henning

2018-05-01

Oxidation of protein therapeutics is a major chemical degradation pathway which may impact bioactivity, serum half-life and stability. Therefore, oxidation is a relevant parameter which has to be monitored throughout formulation development. Methods such as HIC, RPLC and LC/MS achieve a separation of oxidized and non-oxidized species by differences in hydrophobicity. Antibody-drug conjugates (ADC) although are highly more complex due to the heterogeneity in linker, drug, drug-to-antibody ratio (DAR) and conjugation site. The analytical protein A chromatography can provide a simple and fast alternative to these common methods. A miniature analytical protein A chromatography method in combination with an IdeS digest was developed to analyse ADCs. The IdeS digest efficiency of an IgG1 was monitored using SEC-HPLC and non-reducing SDS-PAGE. An antibody-fluorescent dye conjugate was conjugated at different dye-to-antibody ratios as model construct to mimic an ADC. With IdeS, an almost complete digest of a model IgG1 can be achieved (digested protein amount >98%). This enables subsequent analytical protein A chromatography, which consequently eliminates any interference of payload with the stationary phase. A novel high-throughput method for an interchain cysteine-linked ADC oxidation screens during formulation development was developed. © 2018 Royal Pharmaceutical Society.

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

Science.gov (United States)

Blundell, Tom L

2017-07-01

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

Photoactive assemblies of organic compounds and biomolecules: drug-protein supramolecular systems

OpenAIRE

Vayá Pérez, Ignacio; Lhiaubet-Vallet, Virginie Lyria; Jiménez Molero, María Consuelo; Miranda Alonso, Miguel Ángel

2014-01-01

[EN] The properties of singlet and triplet excited states are strongly medium-dependent. Hence, these species constitute valuable tools as reporters to probe compartmentalised microenvironments, including drug@protein supramolecular systems. In the present review, the attention is focused on the photophysical properties of the probe drugs (rather than those of the protein chromophores) using transport proteins (serum albumins and 1-acid glycoproteins) as hosts. Specifically, f...

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

Science.gov (United States)

Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein Drug Targets of Lavandula angustifolia on treatment of Rat Alzheimer's Disease

Science.gov (United States)

Zali, Hakimeh; Zamanian-Azodi, Mona; Rezaei Tavirani, Mostafa; Akbar-zadeh Baghban, Alireza

2015-01-01

Different treatment strategies of Alzheimer's disease (AD) are being studied for treating or slowing the progression of AD. Many pharmaceutically important regulation systems operate through proteins as drug targets. Here, we investigate the drug target proteins in beta-amyloid (Aβ) injected rat hippocampus treated with Lavandula angustifolia (LA) by proteomics techniques. The reported study showed that lavender extract (LE) improves the spatial performance in AD animal model by diminishing Aβ production in histopathology of hippocampus, so in this study neuroprotective proteins expressed in Aβ injected rats treated with LE were scrutinized. Rats were divided into three groups including normal, Aβ injected, and Aβ injected that was treated with LE. Protein expression profiles of hippocampus tissue were determined by two-dimensional electrophoresis (2DE) method and dysregulated proteins such as Snca, NF-L, Hspa5, Prdx2, Apoa1, and Atp5a1were identified by MALDI-TOF/TOF. KEGG pathway and gene ontology (GO) categories were used by searching DAVID Bioinformatics Resources. All detected protein spots were used to determine predictedinteractions with other proteins in STRING online database. Different isoforms of important protein, Snca that exhibited neuroprotective effects by anti-apoptotic properties were expressed. NF-L involved in the maintenance of neuronal caliber. Hspa5 likewise Prdx2 displays as anti-apoptotic protein that Prdx2 also involved in the neurotrophic effects. Apoa1 has anti-inflammatory activity and Atp5a1, produces ATP from ADP. To sum up, these proteins as potential drug targets were expressed in hippocampus in response to effective components in LA may have therapeutic properties for the treatment of AD and other neurodegenerative diseases. PMID:25561935

Photo-synthesis of protein-based nanoparticles and the application in drug delivery

International Nuclear Information System (INIS)

Xie, Jinbing; Wang, Hongyang; Cao, Yi; Qin, Meng; Wang, Wei

2015-01-01

Recently, protein-based nanoparticles as drug delivery systems have attracted great interests due to the excellent behavior of high biocompatibility and biodegradability, and low toxicity. However, the synthesis techniques are generally costly, chemical reagents introduced, and especially present difficulties in producing homogeneous monodispersed nanoparticles. Here, we introduce a novel physical method to synthesize protein nanoparticles which can be accomplished under physiological condition only through ultraviolet (UV) illumination. By accurately adjusting the intensity and illumination time of UV light, disulfide bonds in proteins can be selectively reduced and the subsequent self-assembly process can be well controlled. Importantly, the co-assembly can also be dominated when the proteins mixed with either anti-cancer drugs, siRNA, or active targeting molecules. Both in vitro and in vivo experiments indicate that our synthesized protein–drug nanoparticles (drug-loading content and encapsulation efficiency being ca. 8.2% and 70%, respectively) not only possess the capability of traditional drug delivery systems (DDS), but also have a greater drug delivery efficiency to the tumor sites and a better inhibition of tumor growth (only 35% of volume comparing to the natural growing state), indicating it being a novel drug delivery system in tumor therapy

Modeling structure of G protein-coupled receptors in huan genome

KAUST Repository

Zhang, Yang

2016-01-26

G protein-coupled receptors (or GPCRs) are integral transmembrane proteins responsible to various cellular signal transductions. Human GPCR proteins are encoded by 5% of human genes but account for the targets of 40% of the FDA approved drugs. Due to difficulties in crystallization, experimental structure determination remains extremely difficult for human GPCRs, which have been a major barrier in modern structure-based drug discovery. We proposed a new hybrid protocol, GPCR-I-TASSER, to construct GPCR structure models by integrating experimental mutagenesis data with ab initio transmembrane-helix assembly simulations, assisted by the predicted transmembrane-helix interaction networks. The method was tested in recent community-wide GPCRDock experiments and constructed models with a root mean square deviation 1.26 Å for Dopamine-3 and 2.08 Å for Chemokine-4 receptors in the transmembrane domain regions, which were significantly closer to the native than the best templates available in the PDB. GPCR-I-TASSER has been applied to model all 1,026 putative GPCRs in the human genome, where 923 are found to have correct folds based on the confidence score analysis and mutagenesis data comparison. The successfully modeled GPCRs contain many pharmaceutically important families that do not have previously solved structures, including Trace amine, Prostanoids, Releasing hormones, Melanocortins, Vasopressin and Neuropeptide Y receptors. All the human GPCR models have been made publicly available through the GPCR-HGmod database at http://zhanglab.ccmb.med.umich.edu/GPCR-HGmod/ The results demonstrate new progress on genome-wide structure modeling of transmembrane proteins which should bring useful impact on the effort of GPCR-targeted drug discovery.

Phylogenetic profiles of all membrane transport proteins of the malaria parasite highlight new drug targets

Directory of Open Access Journals (Sweden)

January Weiner 3rd

2016-08-01

Full Text Available In order to combat the on-going malaria epidemic, discovery of new drug targets remains vital. Proteins that are essential to survival and specific to malaria parasites are key candidates. To survive within host cells, the parasites need to acquire nutrients and dispose of waste products across multiple membranes. Additionally, like all eukaryotes, they must redistribute ions and organic molecules between their various internal membrane bound compartments. Membrane transport proteins mediate all of these processes and are considered important mediators of drug resistance as well as drug targets in their own right. Recently, using advanced experimental genetic approaches and streamlined life cycle profiling, we generated a large collection of Plasmodium berghei gene deletion mutants and assigned essential gene functions, highlighting potential targets for prophylactic, therapeutic, and transmission-blocking anti-malarial drugs. Here, we present a comprehensive orthology assignment of all Plasmodium falciparum putative membrane transport proteins and provide a detailed overview of the associated essential gene functions obtained through experimental genetics studies in human and murine model parasites. Furthermore, we discuss the phylogeny of selected potential drug targets identified in our functional screen. We extensively discuss the results in the context of the functional assignments obtained using gene targeting available to date.

Protein Recognition in Drug-Induced DNA Alkylation: When the Moonlight Protein GAPDH Meets S23906-1/DNA Minor Groove Adducts.

Science.gov (United States)

Savreux-Lenglet, Gaëlle; Depauw, Sabine; David-Cordonnier, Marie-Hélène

2015-11-05

DNA alkylating drugs have been used in clinics for more than seventy years. The diversity of their mechanism of action (major/minor groove; mono-/bis-alkylation; intra-/inter-strand crosslinks; DNA stabilization/destabilization, etc.) has undoubtedly major consequences on the cellular response to treatment. The aim of this review is to highlight the variety of established protein recognition of DNA adducts to then particularly focus on glyceraldehyde-3-phosphate dehydrogenase (GAPDH) function in DNA adduct interaction with illustration using original experiments performed with S23906-1/DNA adduct. The introduction of this review is a state of the art of protein/DNA adducts recognition, depending on the major or minor groove orientation of the DNA bonding as well as on the molecular consequences in terms of double-stranded DNA maintenance. It reviews the implication of proteins from both DNA repair, transcription, replication and chromatin maintenance in selective DNA adduct recognition. The main section of the manuscript is focusing on the implication of the moonlighting protein GAPDH in DNA adduct recognition with the model of the peculiar DNA minor groove alkylating and destabilizing drug S23906-1. The mechanism of action of S23906-1 alkylating drug and the large variety of GAPDH cellular functions are presented prior to focus on GAPDH direct binding to S23906-1 adducts.

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

Science.gov (United States)

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

2017-06-19

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

Orally active-targeted drug delivery systems for proteins and peptides.

Science.gov (United States)

Li, Xiuying; Yu, Miaorong; Fan, Weiwei; Gan, Yong; Hovgaard, Lars; Yang, Mingshi

2014-09-01

In the past decade, extensive efforts have been devoted to designing 'active targeted' drug delivery systems (ATDDS) to improve oral absorption of proteins and peptides. Such ATDDS enhance cellular internalization and permeability of proteins and peptides via molecular recognition processes such as ligand-receptor or antigen-antibody interaction, and thus enhance drug absorption. This review focuses on recent advances with orally ATDDS, including ligand-protein conjugates, recombinant ligand-protein fusion proteins and ligand-modified carriers. In addition to traditional intestinal active transport systems of substrates and their corresponding receptors, transporters and carriers, new targets such as intercellular adhesion molecule-1 and β-integrin are also discussed. ATDDS can improve oral absorption of proteins and peptides. However, currently, no clinical studies on ATDDS for proteins and peptides are underway, perhaps due to the complexity and limited knowledge of transport mechanisms. Therefore, more research is warranted to optimize ATDDS efficiency.

Injectable nanocomposite cryogels for versatile protein drug delivery.

Science.gov (United States)

Koshy, Sandeep T; Zhang, David K Y; Grolman, Joshua M; Stafford, Alexander G; Mooney, David J

2018-01-01

Sustained, localized protein delivery can enhance the safety and activity of protein drugs in diverse disease settings. While hydrogel systems are widely studied as vehicles for protein delivery, they often suffer from rapid release of encapsulated cargo, leading to a narrow duration of therapy, and protein cargo can be denatured by incompatibility with the hydrogel crosslinking chemistry. In this work, we describe injectable nanocomposite hydrogels that are capable of sustained, bioactive, release of a variety of encapsulated proteins. Injectable and porous cryogels were formed by bio-orthogonal crosslinking of alginate using tetrazine-norbornene coupling. To provide sustained release from these hydrogels, protein cargo was pre-adsorbed to charged Laponite nanoparticles that were incorporated within the walls of the cryogels. The presence of Laponite particles substantially hindered the release of a number of proteins that otherwise showed burst release from these hydrogels. By modifying the Laponite content within the hydrogels, the kinetics of protein release could be precisely tuned. This versatile strategy to control protein release simplifies the design of hydrogel drug delivery systems. Here we present an injectable nanocomposite hydrogel for simple and versatile controlled release of therapeutic proteins. Protein release from hydrogels often requires first entrapping the protein in particles and embedding these particles within the hydrogel to allow controlled protein release. This pre-encapsulation process can be cumbersome, can damage the protein's activity, and must be optimized for each protein of interest. The strategy presented in this work simply premixes the protein with charged nanoparticles that bind strongly with the protein. These protein-laden particles are then placed within a hydrogel and slowly release the protein into the surrounding environment. Using this method, tunable release from an injectable hydrogel can be achieved for a variety of

Targeted proteins for diabetes drug design

Science.gov (United States)

Doan Trang Nguyen, Ngoc; Thi Le, Ly

2012-03-01

Type 2 diabetes mellitus is a common metabolism disorder characterized by high glucose in the bloodstream, especially in the case of insulin resistance and relative insulin deficiency. Nowadays, it is very common in middle-aged people and involves such dangerous symptoms as increasing risk of stroke, obesity and heart failure. In Vietnam, besides the common treatment of insulin injection, some herbal medication is used but no unified optimum remedy for the disease yet exists and there is no production of antidiabetic drugs in the domestic market yet. In the development of nanomedicine at the present time, drug design is considered as an innovative tool for researchers to study the mechanisms of diseases at the molecular level. The aim of this article is to review some common protein targets involved in type 2 diabetes, offering a new idea for designing new drug candidates to produce antidiabetic drugs against type 2 diabetes for Vietnamese people.

Targeted proteins for diabetes drug design

International Nuclear Information System (INIS)

Trang Nguyen, Ngoc Doan; Le, Ly Thi

2012-01-01

Type 2 diabetes mellitus is a common metabolism disorder characterized by high glucose in the bloodstream, especially in the case of insulin resistance and relative insulin deficiency. Nowadays, it is very common in middle-aged people and involves such dangerous symptoms as increasing risk of stroke, obesity and heart failure. In Vietnam, besides the common treatment of insulin injection, some herbal medication is used but no unified optimum remedy for the disease yet exists and there is no production of antidiabetic drugs in the domestic market yet. In the development of nanomedicine at the present time, drug design is considered as an innovative tool for researchers to study the mechanisms of diseases at the molecular level. The aim of this article is to review some common protein targets involved in type 2 diabetes, offering a new idea for designing new drug candidates to produce antidiabetic drugs against type 2 diabetes for Vietnamese people. (review)

Hybrid protein-inorganic nanoparticles: From tumor-targeted drug delivery to cancer imaging.

Science.gov (United States)

Elzoghby, Ahmed O; Hemasa, Ayman L; Freag, May S

2016-12-10

Recently, a great interest has been paid to the development of hybrid protein-inorganic nanoparticles (NPs) for drug delivery and cancer diagnostics in order to combine the merits of both inorganic and protein nanocarriers. This review primarily discusses the most outstanding advances in the applications of the hybrids of naturally-occurring proteins with iron oxide, gadolinium, gold, silica, calcium phosphate NPs, carbon nanotubes, and quantum dots in drug delivery and cancer imaging. Various strategies that have been utilized for the preparation of protein-functionalized inorganic NPs and the mechanisms involved in the drug loading process are discussed. How can the protein functionalization overcome the limitations of colloidal stability, poor dispersibility and toxicity associated with inorganic NPs is also investigated. Moreover, issues relating to the influence of protein hybridization on the cellular uptake, tumor targeting efficiency, systemic circulation, mucosal penetration and skin permeation of inorganic NPs are highlighted. A special emphasis is devoted to the novel approaches utilizing the protein-inorganic nanohybrids in combined cancer therapy, tumor imaging, and theranostic applications as well as stimuli-responsive drug release from the nanohybrids. Copyright © 2016 Elsevier B.V. All rights reserved.

Computational modeling of drug transport across the in vitro cornea.

Science.gov (United States)

Pak, Joseph; Chen, Z J; Sun, Kay; Przekwas, Andrzej; Walenga, Ross; Fan, Jianghong

2018-01-01

A novel quasi-3D (Q3D) modeling approach was developed to model networks of one dimensional structures like tubes and vessels common in human anatomy such as vascular and lymphatic systems, neural networks, and respiratory airways. Instead of a branching network of the same tissue type, this approach was extended to model an interconnected stack of different corneal tissue layers with membrane junction conditions assigned between the tissues. The multi-laminate structure of the cornea presents a unique barrier design and opportunity for investigation using Q3D modeling. A Q3D model of an in vitro rabbit cornea was created to simulate the drug transport across the cornea, accounting for transcellular and paracellular pathways of passive and convective drug transport as well as physicochemistry of lipophilic partitioning and protein binding. Lipophilic Rhodamine B and hydrophilic fluorescein were used as drug analogs. The model predictions for both hydrophilic and lipophilic tracers were able to match the experimental measurements along with the sharp discontinuities at the epithelium-stroma and stroma-endothelium interfaces. This new modeling approach was successfully applied towards pharmacokinetic modeling for use in topical ophthalmic drug design. Copyright © 2017 Elsevier Ltd. All rights reserved.

Programmable release of multiple protein drugs from aptamer-functionalized hydrogels via nucleic acid hybridization.

Science.gov (United States)

Battig, Mark R; Soontornworajit, Boonchoy; Wang, Yong

2012-08-01

Polymeric delivery systems have been extensively studied to achieve localized and controlled release of protein drugs. However, it is still challenging to control the release of multiple protein drugs in distinct stages according to the progress of disease or treatment. This study successfully demonstrates that multiple protein drugs can be released from aptamer-functionalized hydrogels with adjustable release rates at predetermined time points using complementary sequences (CSs) as biomolecular triggers. Because both aptamer-protein interactions and aptamer-CS hybridization are sequence-specific, aptamer-functionalized hydrogels constitute a promising polymeric delivery system for the programmable release of multiple protein drugs to treat complex human diseases.

Vaginal drug distribution modeling.

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Katz, David F; Yuan, Andrew; Gao, Yajing

2015-09-15

This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of First-Line Drug Resistance Mutations and Drug-Protein Interaction Dynamics from Tuberculosis Patients in South India.

Science.gov (United States)

Nachappa, Somanna Ajjamada; Neelambike, Sumana M; Amruthavalli, Chokkanna; Ramachandra, Nallur B

2018-05-01

Diagnosis of drug-resistant tuberculosis predominantly relies on culture-based drug susceptibility testing, which take weeks to produce a result and a more time-efficient alternative method is multiplex allele-specific PCR (MAS-PCR). Also, understanding the role of mutations in causing resistance helps better drug designing. To evaluate the ability of MAS-PCR in the detection of drug resistance and to understand the mechanism of interaction of drugs with mutant proteins in Mycobacterium tuberculosis. Detection of drug-resistant mutations using MAS-PCR and validation through DNA sequencing. MAS-PCR targeted five loci on three genes, katG 315 and inhA -15 for the drug isoniazid (INH), and rpoB 516, 526, and 531 for rifampicin (RIF). Furthermore, the sequence data were analyzed to study the effect on interaction of the anti-TB drug molecule with the target protein using in silico docking. We identified drug-resistant mutations in 8 out of 114 isolates with 2 of them as multidrug-resistant TB using MAS-PCR. DNA sequencing confirmed only six of these, recording a sensitivity of 85.7% and specificity of 99.3% for MAS-PCR. Molecular docking showed estimated free energy of binding (ΔG) being higher for RIF binding with RpoB S531L mutant. Codon 315 in KatG does not directly interact with INH but blocks the drug access to active site. We propose DNA sequencing-based drug resistance detection for TB, which is more accurate than MAS-PCR. Understanding the action of resistant mutations in disrupting the normal drug-protein interaction aids in designing effective drug alternatives.

Part I---Evaluating Effects of Oligomer Formation on Cytochrome P450 2C9 Electron Transfer and Drug Metabolism, Part II---Utilizing Molecular Modeling Techniques to Study the Src-Interacting Proteins Actin Filament Associated Protein of 110 kDa (AFAP-110) and Cortactin

Science.gov (United States)

Jett, John Edward, Jr.

The dissertation has been divided into two parts to accurately reflect the two distinct areas of interest pursued during my matriculation in the School of Pharmacy at West Virginia University. In Part I, I discuss research probing the nature of electron transfer in the Cytochrome P450 family of proteins, a group of proteins well-known for their role in drug metabolism. In Part II, I focus on in silico and in vitro work developed in concert to probe protein structure and protein-protein interactions involved in actin filament reorganization and cellular motility. Part I. Cytochrome P450s (P450s) are an important class of enzymes known to metabolize a variety of endogenous and xenobiotic compounds. P450s are most commonly found in liver and intestinal endothelial cells and are responsible for the metabolism of approximately 75% of pharmaceutical drugs on the market. CYP2C9---one of the six major P450 isoforms---is responsible for ˜20% of drug metabolism. Elucidation of the factors that affect in vitro drug metabolism is crucial to the accurate prediction of in vivo drug metabolism kinetics. Currently, the two major techniques for studying in vitro drug metabolism are solution-based. However, it is known that the results of solution-based studies can vary from in vivo drug metabolism. One reason suggested to account for this variation is the state of P450 oligomer formation in solution compared to the in vivo environment, where P450s are membrane-bound. To understand the details of how oligomer formation affects in vitro drug metabolism, it is imperative that techniques be developed which will allow for the unequivocal control of oligomer formation without altering other experimental parameters. Our long term goal of this research is to develop methods to more accurately predict in vivo drug metabolism from in vitro data. This section of the dissertation will discuss the development of a platform consisting of a doped silicon surface containing a large array of gold

Hybrid protein-synthetic polymer nanoparticles for drug delivery.

Science.gov (United States)

Koseva, Neli S; Rydz, Joanna; Stoyanova, Ekaterina V; Mitova, Violeta A

2015-01-01

Among the most common nanoparticulate systems, the polymeric nanocarriers have a number of key benefits, which give a great choice of delivery platforms. Nevertheless, polymeric nanoparticles possess some limitations that include use of toxic solvents in the production process, polymer degradation, drug leakage outside the diseased tissue, and polymer cytotoxicity. The combination of polymers of biological and synthetic origin is an appealing modern strategy for the production of novel nanocarriers with unprecedented properties. Proteins' interface can play an important role in determining bioactivity and toxicity and gives perspective for future development of the polymer-based nanoparticles. The design of hybrid constructs composed of synthetic polymer and biological molecules such as proteins can be considered as a straightforward tool to integrate a broad spectrum of properties and biofunctions into a single device. This review discusses hybrid protein-synthetic polymer nanoparticles with different structures and levels in complexity and functionality, in view of their applications as drug delivery systems. © 2015 Elsevier Inc. All rights reserved.

Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Science.gov (United States)

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

A sight on protein-based nanoparticles as drug/gene delivery systems.

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Salatin, Sara; Jelvehgari, Mitra; Maleki-Dizaj, Solmaz; Adibkia, Khosro

2015-01-01

Polymeric nanomaterials have extensively been applied for the preparation of targeted and controlled release drug/gene delivery systems. However, problems involved in the formulation of synthetic polymers such as using of the toxic solvents and surfactants have limited their desirable applications. In this regard, natural biomolecules including proteins and polysaccharide are suitable alternatives due to their safety. According to literature, protein-based nanoparticles possess many advantages for drug and gene delivery such as biocompatibility, biodegradability and ability to functionalize with targeting ligands. This review provides a general sight on the application of biodegradable protein-based nanoparticles in drug/gene delivery based on their origins. Their unique physicochemical properties that help them to be formulated as pharmaceutical carriers are also discussed.

Structure-based drug design for G protein-coupled receptors.

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Congreve, Miles; Dias, João M; Marshall, Fiona H

2014-01-01

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed. © 2014 Elsevier B.V. All rights reserved.

Modeling HIV-1 drug resistance as episodic directional selection.

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Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad

2012-01-01

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

Modeling HIV-1 drug resistance as episodic directional selection.

Directory of Open Access Journals (Sweden)

Ben Murrell

Full Text Available The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

Optimization of protein and peptide drugs based on the mechanisms of kidney clearance.

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Huang, Jiaguo; Wu, Huizi

2018-05-30

Development of proteins and peptides into drugs has been considered as a promising strategy to target certain diseases. However, only few proteins and peptides has been approved as new drugs into the market each year. One major problem is that proteins and peptides often exhibit short plasma half-life times, which limits the application for their clinical use. In most cases a short half-life time is not effective to deliver sufficient amount of drugs to the target organs and tissues, which is generally caused by fast renal clearance and low plasma stability due to proteolytic degradation during systemic circulation, because the most common clearance pathway of small proteins and peptides is through glomerular filtration by the kidneys. In this review, enzymatic degradation of proteins and peptides were discussed. Furthermore, several approaches to lengthen the half-life of peptides and proteins drugs based on the unique structures of glomerular capillary wall and the mechanisms of glomerular filtration were summarized, such as increasing the size and hydrodynamic diameter; increasing the negative charge to delay the filtration; increasing plasma protein binding to decrease plasma clearance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

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Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

Models of protein-ligand crystal structures: trust, but verify.

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Deller, Marc C; Rupp, Bernhard

2015-09-01

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

HIV infection and drugs of abuse: role of acute phase proteins.

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Samikkannu, Thangavel; Rao, Kurapati V K; Arias, Adriana Y; Kalaichezian, Aarthi; Sagar, Vidya; Yoo, Changwon; Nair, Madhavan P N

2013-09-17

HIV infection and drugs of abuse such as methamphetamine (METH), cocaine, and alcohol use have been identified as risk factors for triggering inflammation. Acute phase proteins such as C-reactive protein (CRP) and serum amyloid A (SAA) are the biomarkers of inflammation. Hence, the interactive effect of drugs of abuse with acute phase proteins in HIV-positive subjects was investigated. Plasma samples were utilized from 75 subjects with METH use, cocaine use, alcohol use, and HIV-positive alone and HIV-positive METH, cocaine, and alcohol users, and age-matched control subjects. The plasma CRP and SAA levels were measured by ELISA and western blot respectively and the CD4 counts were also measured. Observed results indicated that the CRP and SAA levels in HIV-positive subjects who are METH, cocaine and alcohol users were significantly higher when compared with either drugs of abuse or HIV-positive alone. The CD4 counts were also dramatically reduced in HIV-positive with drugs of abuse subjects compared with only HIV-positive subjects. These results suggest that, in HIV-positive subjects, drugs of abuse increase the levels of CRP and SAA, which may impact on the HIV infection and disease progression.

Site-specific antibody-drug conjugates: the nexus of bioorthogonal chemistry, protein engineering, and drug development.

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Agarwal, Paresh; Bertozzi, Carolyn R

2015-02-18

Antibody-drug conjugates (ADCs) combine the specificity of antibodies with the potency of small molecules to create targeted drugs. Despite the simplicity of this concept, generation of clinically successful ADCs has been very difficult. Over the past several decades, scientists have learned a great deal about the constraints on antibodies, linkers, and drugs as they relate to successful construction of ADCs. Once these components are in hand, most ADCs are prepared by nonspecific modification of antibody lysine or cysteine residues with drug-linker reagents, which results in heterogeneous product mixtures that cannot be further purified. With advances in the fields of bioorthogonal chemistry and protein engineering, there is growing interest in producing ADCs by site-specific conjugation to the antibody, yielding more homogeneous products that have demonstrated benefits over their heterogeneous counterparts in vivo. Here, we chronicle the development of a multitude of site-specific conjugation strategies for assembly of ADCs and provide a comprehensive account of key advances and their roots in the fields of bioorthogonal chemistry and protein engineering.

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

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

2017-02-01

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

Protein Innovations Advance Drug Treatments, Skin Care

Science.gov (United States)

2012-01-01

Dan Carter carefully layered the sheets of tracing paper on the light box. On each sheet were renderings of the atomic components of an essential human protein, one whose structure had long been a mystery. With each layer Carter laid down, a never-before-seen image became clearer. Carter joined NASA s Marshall Space Flight Center in 1985 and began exploring processes of protein crystal growth in space. By bouncing intense X-rays off the crystals, researchers can determine the electron densities around the thousands of atoms forming the protein molecules, unveiling their atomic structures. Cultivating crystals of sufficient quality on Earth was problematic; the microgravity conditions of space were far more accommodating. At the time, only a few hundred protein structures had been mapped, and the methods were time consuming and tedious. Carter hoped his work would help reveal the structure of human serum albumin, a major protein in the human circulatory system responsible for ferrying numerous small molecules in the blood. More was at stake than scientific curiosity. Albumin has a high affinity for most of the world s pharmaceuticals, Carter explains, and its interaction with drugs can change their safety and efficacy. When a medication enters the bloodstream a cancer chemotherapy drug, for example a majority of it can bind with albumin, leaving only a small percentage active for treatment. How a drug interacts with albumin can influence considerations like the necessary effective dosage, playing a significant role in the design and application of therapeutic measures. In spite of numerous difficulties, including having no access to microgravity following the 1986 Space Shuttle Challenger disaster, the image Carter had hoped to see was finally clarifying. In 1988, his lab had acquired specialized X-ray and detection equipment a tipping point. Carter and his colleagues began to piece together albumin s portrait, the formation of its electron densities coalescing on

Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal

OpenAIRE

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of appl...

QSAR Modeling and Prediction of Drug-Drug Interactions.

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Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

2016-02-01

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Zebrafish as a potential model organism for drug test against hepatitis C virus.

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Cun-Bao Ding

Full Text Available Screening and evaluating anti- hepatitis C virus (HCV drugs in vivo is difficult worldwide, mainly because of the lack of suitable small animal models. We investigate whether zebrafish could be a model organism for HCV replication. To achieve NS5B-dependent replication an HCV sub-replicon was designed and created with two vectors, one with HCV ns5b and fluorescent rfp genes, and the other containing HCV's 5'UTR, core, 3'UTR and fluorescent gfp genes. The vectors containing sub-replicons were co-injected into zebrafish zygotes. The sub-replicon amplified in liver showing a significant expression of HCV core RNA and protein. The sub-replicon amplification caused no abnormality in development and growth of zebrafish larvae, but induced gene expression change similar to that in human hepatocytes. As the amplified core fluorescence in live zebrafish was detectable microscopically, it rendered us an advantage to select those with replicating sub-replicon for drug experiments. Ribavirin and oxymatrine, two known anti-HCV drugs, inhibited sub-replicon amplification in this model showing reduced levels of HCV core RNA and protein. Technically, this method had a good reproducibility and is easy to operate. Thus, zebrafish might be a model organism to host HCV, and this zebrafish/HCV (sub-replicon system could be an animal model for anti-HCV drug screening and evaluation.

eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models.

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Michal Brylinski

2014-09-01

Full Text Available Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4-9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.

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

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Tom L. Blundell

2017-07-01

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

Identify drug repurposing candidates by mining the protein data bank.

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Moriaud, Fabrice; Richard, Stéphane B; Adcock, Stewart A; Chanas-Martin, Laetitia; Surgand, Jean-Sébastien; Ben Jelloul, Marouane; Delfaud, François

2011-07-01

Predicting off-targets by computational methods is gaining increasing interest in early-stage drug discovery. Here, we present a computational method based on full 3D comparisons of 3D structures. When a similar binding site is detected in the Protein Data Bank (PDB) (or any protein structure database), it is possible that the corresponding ligand also binds to that similar site. On one hand, this target hopping case is probably rare because it requires a high similarity between the binding sites. On the other hand, it could be a strong rational evidence to highlight possible off-target reactions and possibly a potential undesired side effect. This target-based drug repurposing can be extended a significant step further with the capability of searching the full surface of all proteins in the PDB, and therefore not relying on pocket detection. Using this approach, we describe how MED-SuMo reproduces the repurposing of tadalafil from PDE5A to PDE4A and a structure of PDE4A with tadalafil. Searching for local protein similarities generates more hits than for whole binding site similarities and therefore fragment repurposing is more likely to occur than for drug-sized compounds. In this work, we illustrate that by mining the PDB for proteins sharing similarities with the hinge region of protein kinases. The experimentally validated examples, biotin carboxylase and synapsin, are retrieved. Further to fragment repurposing, this approach can be applied to the detection of druggable sites from 3D structures. This is illustrated with detection of the protein kinase hinge motif in the HIV-RT non-nucleosidic allosteric site.

Modeling complexes of modeled proteins.

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Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.

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Melak, Tilahun; Gakkhar, Sunita

2015-12-01

In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes. The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation. A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism. Potential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to

Protein-Protein Docking in Drug Design and Discovery.

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Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

2018-01-01

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Genipin-induced inhibition of uncoupling protein-2 sensitizes drug-resistant cancer cells to cytotoxic agents.

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Ryan J Mailloux

2010-10-01

Full Text Available Uncoupling protein-2 (UCP2 is known to suppress mitochondrial reactive oxygen species (ROS production and is employed by drug-resistant cancer cells to mitigate oxidative stress. Using the drug-sensitive HL-60 cells and the drug-resistant MX2 subline as model systems, we show that genipin, a UCP2 inhibitor, sensitizes drug-resistant cells to cytotoxic agents. Increased MX2 cell death was observed upon co-treatment with genipin and different doses of menadione, doxorubicin, and epirubicin. DCFH-DA fluorimetry revealed that the increase in MX2 cell death was accompanied by enhanced cellular ROS levels. The drug-induced increase in ROS was linked to genipin-mediated inhibition of mitochondrial proton leak. State 4 and resting cellular respiratory rates were higher in the MX2 cells in comparison to the HL-60 cells, and the increased respiration was readily suppressed by genipin in the MX2 cells. UCP2 accounted for a remarkable 37% of the resting cellular oxygen consumption indicating that the MX2 cells are functionally reliant on this protein. Higher amounts of UCP2 protein were detected in the MX2 versus the HL-60 mitochondria. The observed effects of genipin were absent in the HL-60 cells pointing to the selectivity of this natural product for drug-resistant cells. The specificity of genipin for UCP2 was confirmed using CHO cells stably expressing UCP2 in which genipin induced an ∼22% decrease in state 4 respiration. These effects were absent in empty vector CHO cells expressing no UCP2. Thus, the chemical inhibition of UCP2 with genipin sensitizes multidrug-resistant cancer cells to cytotoxic agents.

A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim.

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Niederalt, Christoph; Kuepfer, Lars; Solodenko, Juri; Eissing, Thomas; Siegmund, Hans-Ulrich; Block, Michael; Willmann, Stefan; Lippert, Jörg

2018-04-01

Proteins are an increasingly important class of drugs used as therapeutic as well as diagnostic agents. A generic physiologically based pharmacokinetic (PBPK) model was developed in order to represent at whole body level the fundamental mechanisms driving the distribution and clearance of large molecules like therapeutic proteins. The model was built as an extension of the PK-Sim model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling as especially relevant for antibodies. For model development and evaluation, PK data was used for compounds with a wide range of solute radii. The model supports the integration of knowledge gained during all development phases of therapeutic proteins, enables translation from pre-clinical species to human and allows predictions of tissue concentration profiles which are of relevance for the analysis of on-target pharmacodynamic effects as well as off-target toxicity. The current implementation of the model replaces the generic protein PBPK model available in PK-Sim since version 4.2 and becomes part of the Open Systems Pharmacology Suite.

Prediction of Effective Drug Combinations by Chemical Interaction, Protein Interaction and Target Enrichment of KEGG Pathways

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Lei Chen

2013-01-01

Full Text Available Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1 chemical interaction between drugs, (2 protein interactions between drugs’ targets, and (3 target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations.

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

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Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biological background, 1 PPDT-Module and 22 PCOS potential drug targets were identified, 21 of which were verified by literatures to be associated with the pathogenesis of PCOS. 42 drugs targeting to 13 PCOS potential drug targets were investigated experimentally or clinically for PCOS. Evaluated by independent datasets, the whole PPDT-Module and 22 PCOS potential drug targets could not only reveal the drug response, but also distinguish the statuses between normal and disease. Our identified PPDT-Module and PCOS potential drug targets would shed light on the treatment of PCOS. And our approach would provide valuable insights to research on the pathogenesis and drug response of other diseases. PMID:27191267

Exploring the binding sites and binding mechanism for hydrotrope encapsulated griseofulvin drug on γ-tubulin protein.

Directory of Open Access Journals (Sweden)

Shubhadip Das

Full Text Available The protein γ-tubulin plays an important role in centrosomal clustering and this makes it an attractive therapeutic target for treating cancers. Griseofulvin, an antifungal drug, has recently been used to inhibit proliferation of various types of cancer cells. It can also affect the microtubule dynamics by targeting the γ-tubulin protein. So far, the binding pockets of γ-tubulin protein are not properly identified and the exact mechanism by which the drug binds to it is an area of intense speculation and research. The aim of the present study is to investigate the binding mechanism and binding affinity of griseofulvin on γ-tubulin protein using classical molecular dynamics simulations. Since the drug griseofulvin is sparingly soluble in water, here we also present a promising approach for formulating and achieving delivery of hydrophobic griseofulvin drug via hydrotrope sodium cumene sulfonate (SCS cluster. We observe that the binding pockets of γ-tubulin protein are mainly formed by the H8, H9 helices and S7, S8, S14 strands and the hydrophobic interactions between the drug and γ-tubulin protein drive the binding process. The release of the drug griseofulvin from the SCS cluster is confirmed by the coordination number analysis. We also find hydrotrope-induced alteration of the binding sites of γ-tubulin protein and the weakening of the drug-protein interactions.

A biotin-drug extraction and acid dissociation (BEAD) procedure to eliminate matrix and drug interference in a protein complex anti-drug antibody (ADA) isotype specific assay.

Science.gov (United States)

Niu, Hongmei; Klem, Thomas; Yang, Jinsong; Qiu, Yongchang; Pan, Luying

2017-07-01

Monitoring anti-drug antibody (ADA) responses in patients receiving protein therapeutics treatment is an important safety assessment for regulatory agencies, drug manufacturers, clinicians and patients. Recombinant human IGF-1/IGFBP-3 (rhIGF-1/rhIGFBP-3) is a 1:1 formulation of naturally occurring protein complex. The individual IGF-1 and IGFBP-3 proteins have multiple binding partners in serum matrix with high binding affinity to each other, which presents challenges in ADA assay development. We have developed a biotin-drug extraction with acid dissociation (BEAD) procedure followed by an electrochemiluminescence (ECL) direct assay to overcome matrix and drug interference. The method utilizes two step acid dissociation and excess biotin-drug to extract total ADA, which are further captured by soluble biotin-drug and detected in an ECL semi-homogeneous direct assay format. The pre-treatment method effectively eliminates interference by serum matrix and free drug, and enhances assay sensitivity. The assays passed acceptance criteria for all validation parameters, and have been used for clinical sample Ab testing. This method principle exemplifies a new approach for anti-isotype ADA assays, and could be an effective strategy for neutralizing antibody (NAb), pharmacokinetic (PK) and biomarker analysis in need of overcoming interference factors. Copyright © 2017 Elsevier B.V. All rights reserved.

Plant protein-based hydrophobic fine and ultrafine carrier particles in drug delivery systems.

Science.gov (United States)

Malekzad, Hedieh; Mirshekari, Hamed; Sahandi Zangabad, Parham; Moosavi Basri, S M; Baniasadi, Fazel; Sharifi Aghdam, Maryam; Karimi, Mahdi; Hamblin, Michael R

2018-02-01

For thousands of years, plants and their products have been used as the mainstay of medicinal therapy. In recent years, besides attempts to isolate the active ingredients of medicinal plants, other new applications of plant products, such as their use to prepare drug delivery vehicles, have been discovered. Nanobiotechnology is a branch of pharmacology that can provide new approaches for drug delivery by the preparation of biocompatible carrier nanoparticles (NPs). In this article, we review recent studies with four important plant proteins that have been used as carriers for targeted delivery of drugs and genes. Zein is a water-insoluble protein from maize; Gliadin is a 70% alcohol-soluble protein from wheat and corn; legumin is a casein-like protein from leguminous seeds such as peas; lectins are glycoproteins naturally occurring in many plants that recognize specific carbohydrate residues. NPs formed from these proteins show good biocompatibility, possess the ability to enhance solubility, and provide sustained release of drugs and reduce their toxicity and side effects. The effects of preparation methods on the size and loading capacity of these NPs are also described in this review.

Mathematical modeling of drug release from lipid dosage forms.

Science.gov (United States)

Siepmann, J; Siepmann, F

2011-10-10

Lipid dosage forms provide an interesting potential for controlled drug delivery. In contrast to frequently used poly(ester) based devices for parenteral administration, they do not lead to acidification upon degradation and potential drug inactivation, especially in the case of protein drugs and other acid-labile active agents. The aim of this article is to give an overview on the current state of the art of mathematical modeling of drug release from this type of advanced drug delivery systems. Empirical and semi-empirical models are described as well as mechanistic theories, considering diffusional mass transport, potentially limited drug solubility and the leaching of other, water-soluble excipients into the surrounding bulk fluid. Various practical examples are given, including lipid microparticles, beads and implants, which can successfully be used to control the release of an incorporated drug during periods ranging from a few hours up to several years. The great benefit of mechanistic mathematical theories is the possibility to quantitatively predict the effects of different formulation parameters and device dimensions on the resulting drug release kinetics. Thus, in silico simulations can significantly speed up product optimization. This is particularly useful if long release periods (e.g., several months) are targeted, since experimental trial-and-error studies are highly time-consuming in these cases. In the future it would be highly desirable to combine mechanistic theories with the quantitative description of the drug fate in vivo, ideally including the pharmacodynamic efficacy of the treatments. Copyright © 2011 Elsevier B.V. All rights reserved.

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

OpenAIRE

Huang, Hao; He, Yuehan; Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biologi...

A new strategy to deliver synthetic protein drugs: self-reproducible biologics using minicircles.

Science.gov (United States)

Yi, Hyoju; Kim, Youngkyun; Kim, Juryun; Jung, Hyerin; Rim, Yeri Alice; Jung, Seung Min; Park, Sung-Hwan; Ju, Ji Hyeon

2014-08-05

Biologics are the most successful drugs used in anticytokine therapy. However, they remain partially unsuccessful because of the elevated cost of their synthesis and purification. Development of novel biologics has also been hampered by the high cost. Biologics are made of protein components; thus, theoretically, they can be produced in vivo. Here we tried to invent a novel strategy to allow the production of synthetic drugs in vivo by the host itself. The recombinant minicircles encoding etanercept or tocilizumab, which are synthesized currently by pharmaceutical companies, were injected intravenously into animal models. Self-reproduced etanercept and tocilizumab were detected in the serum of mice. Moreover, arthritis subsided in mice that were injected with minicircle vectors carrying biologics. Self-reproducible biologics need neither factory facilities for drug production nor clinical processes, such as frequent drug injection. Although this novel strategy is in its very early conceptual stage, it seems to represent a potential alternative method for the delivery of biologics.

Energetics investigation on encapsulation of protein/peptide drugs in carbon nanotubes.

Science.gov (United States)

Chen, Qu; Wang, Qi; Liu, Ying-Chun; Wu, Tao; Kang, Yu; Moore, Joshua D; Gubbins, Keith E

2009-07-07

This work focuses on the dynamic properties and energetics of the protein/peptide drug during its transport through carbon nanotubes (CNTs). A systematic study was performed on the interaction between the peptide and the CNTs. In the molecular dynamics (MD) simulations, the protein/peptide molecule Zadaxin is observed to be encapsulated inside the nanotube after its spontaneous insertion and oscillates around the center of the tube, where the van der Waals interaction energy is observed to be a minimum. Furthermore, it is found by performing steered MD simulations that the pulling force applied to the peptide reaches a maximum value, which demonstrates the ability of the CNTs to trap protein/peptide drugs. Such effects, attributed to van der Waals interactions, can be influenced by varying the lengths and diameters of the CNTs. Longer nanotubes provide a broader area to trap the peptide, while smaller nanotubes are able to encapsulate the peptide with a deeper interaction energy well. This investigation provides insights into nanoscale pharmaceutical drug delivery devices.

Application of Minicircle Technology of Self-Reproducing Synthetic Protein Drugs in Preventing Skin Allograft Rejection.

Science.gov (United States)

Lim, Sun Woo; Kim, Young Kyun; Park, Narae; Jin, Long; Jin, Jian; Doh, Kyoung Chan; Ju, Ji Hyeon; Yang, Chul Woo

2015-07-30

Recently, it has been reported that minicircle vectors could allow the expression of transgenes using the protein synthesis system of the host. Here, we tested a novel strategy to permit the production of synthetic biologics using minicircle technology and evaluated their feasibility as a therapeutic tool in a skin allograft model. We engineered vectors to carry cassette sequences for tocilizumab [anti-soluble interleukin-6 receptor (sIL-6R) antibody] and/or etanercept [tumor necrosis factor receptor 2 (TNFR2)-Fc fusion protein], and then isolated minicircle vectors from the parent vectors. We verified the production of proteins from minicircles and their duration in HEK293T cells and mice. We also evaluated whether these proteins were expressed at levels sufficient to ameliorate skin allograft rejection in mice. Each minicircle transfected into cells was detectable for at least 30 days. In mice, the drugs were mainly expressed in the liver and were detectable for at least 10 days after a single injection. These drugs were also detected in the blood. Treatment of mice with minicircles prolonged skin allograft survival, which was accompanied by a reduction of the number of interferon-γ+ or interleukin-17+ lymphocytes and an induction of forkhead box P3 expression. These findings suggest that blocking of sIL-6R and/or TNF-α using minicircles encoding tocilizumab and/or etanercept was functionally active and relevant for preventing acute allograft rejection. Self-reproducing synthetic protein drugs produced using minicircle technology are potentially powerful tools for preventing acute rejection in transplantation.

ANALYSIS OF DRUG-PROTEIN BINDING BY ULTRAFAST AFFINITY CHROMATOGRAPHY USING IMMOBILIZED HUMAN SERUM ALBUMIN

Science.gov (United States)

Mallik, Rangan; Yoo, Michelle J.; Briscoe, Chad J.; Hage, David S.

2010-01-01

Human serum albumin (HSA) was explored for use as a stationary phase and ligand in affinity microcolumns for the ultrafast extraction of free drug fractions and the use of this information for the analysis of drug-protein binding. Warfarin, imipramine, and ibuprofen were used as model analytes in this study. It was found that greater than 95% extraction of all these drugs could be achieved in as little as 250 ms on HSA microcolumns. The retained drug fraction was then eluted from the same column under isocratic conditions, giving elution in less than 40 s when working at 4.5 mL/min. The chromatographic behavior of this system gave a good fit with that predicted by computer simulations based on a reversible, saturable model for the binding of an injected drug with immobilized HSA. The free fractions measured by this method were found to be comparable to those determined by ultrafiltration, and equilibrium constants estimated by this approach gave good agreement with literature values. Advantages of this method include its speed and the relatively low cost of microcolumns that contain HSA. The ability of HSA to bind many types of drugs also creates the possibility of using the same affinity microcolumn to study and measure the free fractions for a variety of pharmaceutical agents. These properties make this technique appealing for use in drug binding studies and in the high-throughput screening of new drug candidates. PMID:20227701

Photobinding of tiaprofenic acid and suprofen to proteins and cells: a combined study using radiolabeling, antibodies and laser flash photolysis of model bichromophores.

Science.gov (United States)

Castell, J V; Hernández, D; Gómez-Lechón, M J; Lahoz, A; Miranda, M A; Morera, I M; Pérez-Prieto, J; Sarabia, Z

1998-11-01

Drug photoallergy is a matter of current concern. It involves the formation of drug-protein photoadducts (photoantigens) that may ultimately trigger an immunological response. Tyrosine residues appear to be key binding sites in proteins. The present work has investigated the photobinding of tiaprofenic and (TPA) and the closely related isomer suprofen (SUP) to proteins and cells by means of radioactive labelling and drug-directed antibodies. To ascertain whether preassociation with the protein may play a role in photoreactivity, two model bichromophoric compounds (TPA-Tyr and SUP-Tyr) have been prepared and studied by laser flash photolysis. The results of this work show that (a) TPA and SUP photobind to proteins with similar efficiencies, (b) both drugs form photoadducts that share a basic common structure, as they are recognized by the same antibody and (c) drug-protein preassociation must play a key role in photoreactivity, as indicated by the dramatic decrease in the triplet state lifetimes of the model bichromophores compared to the parent drugs.

Single chain Fc-dimer-human growth hormone fusion protein for improved drug delivery.

Science.gov (United States)

Zhou, Li; Wang, Hsuan-Yao; Tong, Shanshan; Okamoto, Curtis T; Shen, Wei-Chiang; Zaro, Jennica L

2017-02-01

Fc fusion protein technology has been successfully used to generate long-acting forms of several protein therapeutics. In this study, a novel Fc-based drug carrier, single chain Fc-dimer (sc(Fc) 2 ), was designed to contain two Fc domains recombinantly linked via a flexible linker. Since the Fc dimeric structure is maintained through the flexible linker, the hinge region was omitted to further stabilize it against proteolysis and reduce FcγR-related effector functions. The resultant sc(Fc) 2 candidate preserved the neonatal Fc receptor (FcRn) binding. sc(Fc) 2 -mediated delivery was then evaluated using a therapeutic protein with a short plasma half-life, human growth hormone (hGH), as the protein drug cargo. This novel carrier protein showed a prolonged in vivo half-life and increased hGH-mediated bioactivity compared to the traditional Fc-based drug carrier. sc(Fc) 2 technology has the potential to greatly advance and expand the use of Fc-technology for improving the pharmacokinetics and bioactivity of protein therapeutics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spectroscopic study of drug-binding characteristics of unmodified and pNPA-based acetylated human serum albumin: Does esterase activity affect microenvironment of drug binding sites on the protein?

Energy Technology Data Exchange (ETDEWEB)

Moradi, Nastaran [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Ashrafi-Kooshk, Mohammad Reza [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Ghobadi, Sirous [Department of Biology, Faculty of Sciences, Razi University, Kermanshah (Iran, Islamic Republic of); Shahlaei, Mohsen [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Khodarahmi, Reza, E-mail: rkhodarahmi@mbrc.ac.ir [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of)

2015-04-15

Human serum albumin (HSA) is the most prominent extracellular protein in blood plasma. There are several binding sites on the protein which provide accommodation for structurally-unrelated endogenous and exogenous ligands and a wide variety of drugs. “Esterase-like” activity (hydrolysis of p-nitrophenyl esters) by the protein has been also reported. In the current study, we set out to investigate the interaction of indomethacin and ibuprofen with the unmodified and modified HSA (pNPA-modified HSA) using various spectroscopic techniques. Fluorescence data showed that 1:1 binding of drug to HSA is associated with quenching of the protein intrinsic fluorescence. Decrease of protein surface hydrophobicity (PSH), alteration in drug binding affinity and change of the protein stability, after esterase-like activity and permanent acetylation of HSA, were also documented. Analysis of the quenching and thermodynamic parameters indicated that forces involved in drug–HSA interactions change upon the protein modification. - Highlights: • Binding propensity of indomethacin extremely decreased upon the protein acetylation. • There is no ibuprofen binding after protein acetylation. • Protein stability changes upon drug binding as well as protein acetylation. • Drug pharmacokinetics may be influenced under co-administration of HSA-modifier drugs.

Spectroscopic study of drug-binding characteristics of unmodified and pNPA-based acetylated human serum albumin: Does esterase activity affect microenvironment of drug binding sites on the protein?

International Nuclear Information System (INIS)

Moradi, Nastaran; Ashrafi-Kooshk, Mohammad Reza; Ghobadi, Sirous; Shahlaei, Mohsen; Khodarahmi, Reza

2015-01-01

Human serum albumin (HSA) is the most prominent extracellular protein in blood plasma. There are several binding sites on the protein which provide accommodation for structurally-unrelated endogenous and exogenous ligands and a wide variety of drugs. “Esterase-like” activity (hydrolysis of p-nitrophenyl esters) by the protein has been also reported. In the current study, we set out to investigate the interaction of indomethacin and ibuprofen with the unmodified and modified HSA (pNPA-modified HSA) using various spectroscopic techniques. Fluorescence data showed that 1:1 binding of drug to HSA is associated with quenching of the protein intrinsic fluorescence. Decrease of protein surface hydrophobicity (PSH), alteration in drug binding affinity and change of the protein stability, after esterase-like activity and permanent acetylation of HSA, were also documented. Analysis of the quenching and thermodynamic parameters indicated that forces involved in drug–HSA interactions change upon the protein modification. - Highlights: • Binding propensity of indomethacin extremely decreased upon the protein acetylation. • There is no ibuprofen binding after protein acetylation. • Protein stability changes upon drug binding as well as protein acetylation. • Drug pharmacokinetics may be influenced under co-administration of HSA-modifier drugs

Inhibition of protein synthesis and malaria parasite development by drug targeting of methionyl-tRNA synthetases.

Science.gov (United States)

Hussain, Tahir; Yogavel, Manickam; Sharma, Amit

2015-04-01

Aminoacyl-tRNA synthetases (aaRSs) are housekeeping enzymes that couple cognate tRNAs with amino acids to transmit genomic information for protein translation. The Plasmodium falciparum nuclear genome encodes two P. falciparum methionyl-tRNA synthetases (PfMRS), termed PfMRS(cyt) and PfMRS(api). Phylogenetic analyses revealed that the two proteins are of primitive origin and are related to heterokonts (PfMRS(cyt)) or proteobacteria/primitive bacteria (PfMRS(api)). We show that PfMRS(cyt) localizes in parasite cytoplasm, while PfMRS(api) localizes to apicoplasts in asexual stages of malaria parasites. Two known bacterial MRS inhibitors, REP3123 and REP8839, hampered Plasmodium growth very effectively in the early and late stages of parasite development. Small-molecule drug-like libraries were screened against modeled PfMRS structures, and several "hit" compounds showed significant effects on parasite growth. We then tested the effects of the hit compounds on protein translation by labeling nascent proteins with (35)S-labeled cysteine and methionine. Three of the tested compounds reduced protein synthesis and also blocked parasite growth progression from the ring stage to the trophozoite stage. Drug docking studies suggested distinct modes of binding for the three compounds, compared with the enzyme product methionyl adenylate. Therefore, this study provides new targets (PfMRSs) and hit compounds that can be explored for development as antimalarial drugs. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Polysaccharides-based polyelectrolyte nanoparticles as protein drugs delivery system

Energy Technology Data Exchange (ETDEWEB)

Shu Shujun; Sun Lei; Zhang Xinge, E-mail: zhangxinge@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China); Wu Zhongming [Tianjin Medical University, Metabolic Diseases Hospital (China); Wang Zhen; Li Chaoxing, E-mail: lcx@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China)

2011-09-15

Polysaccharides-based nanoparticles were prepared by synthesized quaternized chitosan and dextran sulfate through simple ionic-gelation self-assembled method. Introduction of quaternized groups was intended to increase water solubility of chitosan and make the nanoparticles have broader pH sensitive range which can remain more stable in physiological pH and decrease the loss of protein drugs caused by the gastric cavity. The load of BSA was affected by molecular parameter, i.e., degree of substitution, and average molecular weight of quaternized chitosan, as well as concentration of BSA. Fast release occurred in phosphate buffer solution (pH 7.4) while the release was slow in hydrochloric acid (pH 1.4). The drug release mechanism is Fickian diffusion through release kinetics analysis. Cell uptake demonstrated nanoparicles can internalize into Caco-2 cells, which suggested that nanoparticles had good biocompatibility. No significant conformation change was noted for the released BSA in comparison with native BSA using circular dichroism spectroscopy. This kind of novel composite nanoparticles may be a promising delivery system for oral protein and peptide drugs.

Modeling Drug-Carrier Interaction in the Drug Release from Nanocarriers

Directory of Open Access Journals (Sweden)

Like Zeng

2011-01-01

Full Text Available Numerous nanocarriers of various compositions and geometries have been developed for the delivery and release of therapeutic and imaging agents. Due to the high specific surface areas of nanocarriers, different mechanisms such as ion pairing and hydrophobic interaction need to be explored for achieving sustained release. Recently, we developed a three-parameter model that considers reversible drug-carrier interaction and first-order drug release from liposomes. A closed-form analytical solution was obtained. Here, we further explore the ability of the model to capture the release of bioactive molecules such as drugs and growth factors from various nanocarriers. A parameter study demonstrates that the model is capable of resembling major categories of drug release kinetics. We further fit the model to 60 sets of experimental data from various drug release systems, including nanoparticles, hollow particles, fibers, and hollow fibers. Additionally, bootstrapping is used to evaluate the accuracy of parameter determination and validate the model in selected cases. The simplicity and universality of the model and the clear physical meanings of each model parameter render the model useful for the design and development of new drug delivery systems.

Drug target ontology to classify and integrate drug discovery data.

Science.gov (United States)

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

2017-11-09

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

Analysis of drug-protein binding using on-line immunoextraction and high-performance affinity microcolumns: Studies with normal and glycated human serum albumin.

Science.gov (United States)

Matsuda, Ryan; Jobe, Donald; Beyersdorf, Jared; Hage, David S

2015-10-16

A method combining on-line immunoextraction microcolumns with high-performance affinity chromatography (HPAC) was developed and tested for use in examining drug-protein interactions with normal or modified proteins. Normal human serum albumin (HSA) and glycated HSA were used as model proteins for this work. High-performance immunoextraction microcolumns with sizes of 1.0-2.0 cm × 2.1mm i.d. and containing anti-HSA polyclonal antibodies were developed and tested for their ability to bind normal HSA or glycated HSA. These microcolumns were able to extract up to 82-93% for either type of protein at 0.05-0.10 mL/min and had a binding capacity of 0.34-0.42 nmol HSA for a 1.0 cm × 2.1mm i.d. microcolumn. The immunoextraction microcolumns and their adsorbed proteins were tested for use in various approaches for drug binding studies. Frontal analysis was used with the adsorbed HSA/glycated HSA to measure the overall affinities of these proteins for the drugs warfarin and gliclazide, giving comparable values to those obtained previously using similar protein preparations that had been covalently immobilized within HPAC columns. Zonal elution competition studies with gliclazide were next performed to examine the specific interactions of this drug at Sudlow sites I and II of the adsorbed proteins. These results were also comparable to those noted in prior work with covalently immobilized samples of normal HSA or glycated HSA. These experiments indicated that drug-protein binding studies can be carried out by using on-line immunoextraction microcolumns with HPAC. The same method could be used in the future with clinical samples and other drugs or proteins of interest in pharmaceutical studies or biomedical research. Copyright © 2015 Elsevier B.V. All rights reserved.

Potent antitumor activities of recombinant human PDCD5 protein in combination with chemotherapy drugs in K562 cells

International Nuclear Information System (INIS)

Shi, Lin; Song, Quansheng; Zhang, Yingmei; Lou, Yaxin; Wang, Yanfang; Tian, Linjie; Zheng, Yi; Ma, Dalong; Ke, Xiaoyan; Wang, Ying

2010-01-01

Conventional chemotherapy is still frequently used. Programmed cell death 5 (PDCD5) enhances apoptosis of various tumor cells triggered by certain stimuli and is lowly expressed in leukemic cells from chronic myelogenous leukemia patients. Here, we describe for the first time that recombinant human PDCD5 protein (rhPDCD5) in combination with chemotherapy drugs has potent antitumor effects on chronic myelogenous leukemia K562 cells in vitro and in vivo. The antitumor efficacy of rhPDCD5 protein with chemotherapy drugs, idarubicin (IDR) or cytarabine (Ara-C), was examined in K562 cells in vitro and K562 xenograft tumor models in vivo. rhPDCD5 protein markedly increased the apoptosis rates and decreased the colony-forming capability of K562 cells after the combined treatment with IDR or Ara-C. rhPDCD5 protein by intraperitoneal administration dramatically improved the antitumor effects of IDR treatment in the K562 xenograft model. The tumor sizes and cell proliferation were significantly decreased; and TUNEL positive cells were significantly increased in the combined group with rhPDCD5 protein and IDR treatment compared with single IDR treatment groups. rhPDCD5 protein, in combination with IDR, has potent antitumor effects on chronic myelogenous leukemia K562 cells and may be a novel and promising agent for the treatment of chronic myelogenous leukemia.

A model in which heat shock protein 90 targets protein-folding clefts: rationale for a new approach to neuroprotective treatment of protein folding diseases.

Science.gov (United States)

Pratt, William B; Morishima, Yoshihiro; Gestwicki, Jason E; Lieberman, Andrew P; Osawa, Yoichi

2014-11-01

In an EBM Minireview published in 2010, we proposed that the heat shock protein (Hsp)90/Hsp70-based chaperone machinery played a major role in determining the selection of proteins that have undergone oxidative or other toxic damage for ubiquitination and proteasomal degradation. The proposal was based on a model in which the Hsp90 chaperone machinery regulates signaling by modulating ligand-binding clefts. The model provides a framework for thinking about the development of neuroprotective therapies for protein-folding diseases like Alzheimer's disease (AD), Parkinson's disease (PD), and the polyglutamine expansion disorders, such as Huntington's disease (HD) and spinal and bulbar muscular atrophy (SBMA). Major aberrant proteins that misfold and accumulate in these diseases are "client" proteins of the abundant and ubiquitous stress chaperone Hsp90. These Hsp90 client proteins include tau (AD), α-synuclein (PD), huntingtin (HD), and the expanded glutamine androgen receptor (polyQ AR) (SBMA). In this Minireview, we update our model in which Hsp90 acts on protein-folding clefts and show how it forms a rational basis for developing drugs that promote the targeted elimination of these aberrant proteins. © 2014 by the Society for Experimental Biology and Medicine.

The potential of protein-nanomaterial interaction for advanced drug delivery

DEFF Research Database (Denmark)

Peng, Qiang; Mu, Huiling

2016-01-01

Nanomaterials, like nanoparticles, micelles, nano-sheets, nanotubes and quantum dots, have great potentials in biomedical fields. However, their delivery is highly limited by the formation of protein corona upon interaction with endogenous proteins. This new identity, instead of nanomaterial itself...... of such interaction for advanced drug delivery are presented........ Therefore, protein-nanomaterial interaction is a great challenge for nanomaterial systems and should be inhibited. However, this interaction can also be used to functionalize nanomaterials by forming a selected protein corona. Unlike other decoration using exogenous molecules, nanomaterials functionalized...

Drug-model membrane interactions

International Nuclear Information System (INIS)

Deniz, Usha K.

1994-01-01

In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab

Determination of the total concentration of highly protein-bound drugs in plasma by on-line dialysis and column liquid chromatography: application to non-steroidal anti-inflammatory drugs.

NARCIS (Netherlands)

Herraez-Hernandez, R.; van de Merbel, N.C.; Brinkman, U.A.T.

1995-01-01

The potential of on-line dialysis as a sample preparation procedure for compounds highly bound to plasma proteins is evaluated, using non-steroidal anti-inflammatory drugs as model compounds and column liquid chromatography as the separation technique. Different strategies to reduce the degree of

Determination of the total concentration of highly protein-bound drugs in plasma by on-line dialysis and column liquid chromatography : application to non-steroidal anti-inflammatory drugs

NARCIS (Netherlands)

Herráez-Hernández, R; van de Merbel, N C; Brinkman, U A

1995-01-01

The potential of on-line dialysis as a sample preparation procedure for compounds highly bound to plasma proteins is evaluated, using non-steroidal anti-inflammatory drugs as model compounds and column liquid chromatography as the separation technique. Different strategies to reduce the degree of

The human multidrug resistance-associated protein MRP is a plasma membrane drug-efflux pump

NARCIS (Netherlands)

Zaman, G. J.; Flens, M. J.; van Leusden, M. R.; de Haas, M.; Mülder, H. S.; Lankelma, J.; Pinedo, H. M.; Scheper, R. J.; Baas, F.; Broxterman, H. J.

1994-01-01

The multidrug-resistance associated protein MRP is a 180- to 195-kDa membrane protein associated with resistance of human tumor cells to cytotoxic drugs. We have investigated how MRP confers drug resistance in SW-1573 human lung carcinoma cells by generating a subline stably transfected with an

Identification of putative drug targets in Vancomycin-resistant Staphylococcus aureus (VRSA) using computer aided protein data analysis.

Science.gov (United States)

Hasan, Md Anayet; Khan, Md Arif; Sharmin, Tahmina; Hasan Mazumder, Md Habibul; Chowdhury, Afrin Sultana

2016-01-01

Vancomycin-resistant Staphylococcus aureus (VRSA) is a Gram-positive, facultative aerobic bacterium which is evolved from the extensive exposure of Vancomycin to Methicillin resistant S. aureus (MRSA) that had become the most common cause of hospital and community-acquired infections. Due to the emergence of different antibiotic resistance strains, there is an exigency to develop novel drug targets to address the provocation of multidrug-resistant bacteria. In this study, in-silico genome subtraction methodology was used to design potential and pathogen specific drug targets against VRSA. Our study divulged 1987 proteins from the proteome of 34,549 proteins, which have no homologues in human genome after sequential analysis through CD-HIT and BLASTp. The high stringency analysis of the remaining proteins against database of essential genes (DEG) resulted in 169 proteins which are essential for S. aureus. Metabolic pathway analysis of human host and pathogen by KAAS at the KEGG server sorted out 19 proteins involved in unique metabolic pathways. 26 human non-homologous membrane-bound essential proteins including 4 which were also involved in unique metabolic pathway were deduced through PSORTb, CELLO v.2.5, ngLOC. Functional classification of uncharacterized proteins through SVMprot derived 7 human non-homologous membrane-bound hypothetical essential proteins. Study of potential drug target against Drug Bank revealed pbpA-penicillin-binding protein 1 and hypothetical protein MQW_01796 as the best drug target candidate. 2D structure was predicted by PRED-TMBB, 3D structure and functional analysis was also performed. Protein-protein interaction network of potential drug target proteins was analyzed by using STRING. The identified drug targets are expected to have great potential for designing novel drugs against VRSA infections and further screening of the compounds against these new targets may result in the discovery of novel therapeutic compounds that can be

Structural analysis of protein-ligand interactions: the binding of endogenous compounds and of synthetic drugs.

Science.gov (United States)

Gallina, Anna M; Bork, Peer; Bordo, Domenico

2014-02-01

The large number of macromolecular structures deposited with the Protein Data Bank (PDB) describing complexes between proteins and either physiological compounds or synthetic drugs made it possible a systematic analysis of the interactions occurring between proteins and their ligands. In this work, the binding pockets of about 4000 PDB protein-ligand complexes were investigated and amino acid and interaction types were analyzed. The residues observed with lowest frequency in protein sequences, Trp, His, Met, Tyr, and Phe, turned out to be the most abundant in binding pockets. Significant differences between drug-like and physiological compounds were found. On average, physiological compounds establish with respect to drugs about twice as many hydrogen bonds with protein atoms, whereas drugs rely more on hydrophobic interactions to establish target selectivity. The large number of PDB structures describing homologous proteins in complex with the same ligand made it possible to analyze the conservation of binding pocket residues among homologous protein structures bound to the same ligand, showing that Gly, Glu, Arg, Asp, His, and Thr are more conserved than other amino acids. Also in the cases in which the same ligand is bound to unrelated proteins, the binding pockets showed significant conservation in the residue types. In this case, the probability of co-occurrence of the same amino acid type in the binding pockets could be up to thirteen times higher than that expected on a random basis. The trends identified in this study may provide an useful guideline in the process of drug design and lead optimization. Copyright © 2014 John Wiley & Sons, Ltd.

Synthesis, characterization and target protein binding of drug-conjugated quantum dots in vitro and in living cells

International Nuclear Information System (INIS)

Choi, Youngseon; Kim, Minjung; Cho, Yoojin; Yun, Eunsuk; Song, Rita

2013-01-01

Elucidation of unknown target proteins of a drug is of great importance in understanding cell biology and drug discovery. There have been extensive studies to discover and identify target proteins in the cell. Visualization of targets using drug-conjugated probes has been an important approach to gathering mechanistic information of drug action at the cellular level. As quantum dot (QD) nanocrystals have attracted much attention as a fluorescent probe in the bioimaging area, we prepared drug-conjugated QD to explore the potential of target discovery. As a model drug, we selected a well-known anticancer drug, methotrexate (MTX), which has been known to target dihydrofolate reductase (DHFR) with high affinity binding (K d = 0.54 nM). MTX molecules were covalently attached to amino-PEG-polymer-coated QDs. Specific interactions of MTX-conjugated QDs with DHFR were identified using agarose gel electrophoresis and fluorescence microscopy. Cellular uptake of the MTX-conjugated QDs in living CHO cells was investigated with regard to their localization and distribution pattern. MTX–QD was found to be internalized into the cells via caveolae-medicated endocytosis without significant sequestration in endosomes. A colocalization experiment of the MTX–QD conjugate with antiDHFR-TAT-QD also confirmed that MTX–QD binds to the target DHFR. This study showed the potential of the drug-QD conjugate to identify or visualize drug–target interactions in the cell, which is currently of great importance in the area of drug discovery and chemical biology. (paper)

2D MI-DRAGON: a new predictor for protein-ligands interactions and theoretic-experimental studies of US FDA drug-target network, oxoisoaporphine inhibitors for MAO-A and human parasite proteins.

Science.gov (United States)

Prado-Prado, Francisco; García-Mera, Xerardo; Escobar, Manuel; Sobarzo-Sánchez, Eduardo; Yañez, Matilde; Riera-Fernandez, Pablo; González-Díaz, Humberto

2011-12-01

There are many pairs of possible Drug-Proteins Interactions that may take place or not (DPIs/nDPIs) between drugs with high affinity/non-affinity for different proteins. This fact makes expensive in terms of time and resources, for instance, the determination of all possible ligands-protein interactions for a single drug. In this sense, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out rational DPIs prediction. Unfortunately, almost all QSAR models predict activity against only one target. To solve this problem we can develop multi-target QSAR (mt-QSAR) models. In this work, we introduce the technique 2D MI-DRAGON a new predictor for DPIs based on two different well-known software. We use the software MARCH-INSIDE (MI) to calculate 3D structural parameters for targets and the software DRAGON was used to calculated 2D molecular descriptors all drugs showing known DPIs present in the Drug Bank (US FDA benchmark dataset). Both classes of parameters were used as input of different Artificial Neural Network (ANN) algorithms to seek an accurate non-linear mt-QSAR predictor. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 21:21-31-1:1. This MLP classifies correctly 303 out of 339 DPIs (Sensitivity = 89.38%) and 480 out of 510 nDPIs (Specificity = 94.12%), corresponding to training Accuracy = 92.23%. The validation of the model was carried out by means of external predicting series with Sensitivity = 92.18% (625/678 DPIs; Specificity = 90.12% (730/780 nDPIs) and Accuracy = 91.06%. 2D MI-DRAGON offers a good opportunity for fast-track calculation of all possible DPIs of one drug enabling us to re-construct large drug-target or DPIs Complex Networks (CNs). For instance, we reconstructed the CN of the US FDA benchmark dataset with 855 nodes 519 drugs+336 targets). We predicted CN with similar topology (observed and predicted values of average distance are equal to 6.7 vs. 6.6). These CNs can be used to explore

Coarse-grain modelling of protein-protein interactions

NARCIS (Netherlands)

Baaden, Marc; Marrink, Siewert J.

2013-01-01

Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are

Thiomers and thiomer-based nanoparticles in protein and DNA drug delivery.

Science.gov (United States)

Hauptstein, Sabine; Bernkop-Schnürch, Andreas

2012-09-01

Thanks to advances in biotechnology, more and more highly efficient protein- and DNA-based drugs have been developed. Unfortunately, these kinds of drugs underlie poor non-parental bioavailability. To overcome hindrances like low mucosal permeability and enzymatic degradation polymeric excipients are utilized as drug carrier whereat thiolated excipients showed several promising qualities in comparison to the analogical unmodified polymer. The article deals with the comparatively easy modification of well-established polymers like chitosan or poly(acrylates) to synthesize thiomers. Further, the recently developed "next generation" thiomers e.g. preactivated or S-protected thiomers are introduced. Designative properties like mucoadhesion, uptake and permeation enhancement, efflux pump inhibition and protection against enzymatic degradation will be discussed and differences between first and next generation thiomers will be pointed out. Additionally, nanoparticles prepared with thiomers will be dealt with regarding to protein and DNA drug delivery as thiomers seem to be a promising approach to avoid parenteral application. Properties of thiomers per se and results of in vivo studies carried out so far for peptide and DNA drugs demonstrate their potential as multifunctional excipients. However, further investigations and optimizations have to be done before establishing a carrier system ready for clinical approval.

Microfluidic Devices for Drug Delivery Systems and Drug Screening

Science.gov (United States)

Kompella, Uday B.; Damiati, Safa A.

2018-01-01

Microfluidic devices present unique advantages for the development of efficient drug carrier particles, cell-free protein synthesis systems, and rapid techniques for direct drug screening. Compared to bulk methods, by efficiently controlling the geometries of the fabricated chip and the flow rates of multiphase fluids, microfluidic technology enables the generation of highly stable, uniform, monodispersed particles with higher encapsulation efficiency. Since the existing preclinical models are inefficient drug screens for predicting clinical outcomes, microfluidic platforms might offer a more rapid and cost-effective alternative. Compared to 2D cell culture systems and in vivo animal models, microfluidic 3D platforms mimic the in vivo cell systems in a simple, inexpensive manner, which allows high throughput and multiplexed drug screening at the cell, organ, and whole-body levels. In this review, the generation of appropriate drug or gene carriers including different particle types using different configurations of microfluidic devices is highlighted. Additionally, this paper discusses the emergence of fabricated microfluidic cell-free protein synthesis systems for potential use at point of care as well as cell-, organ-, and human-on-a-chip models as smart, sensitive, and reproducible platforms, allowing the investigation of the effects of drugs under conditions imitating the biological system. PMID:29462948

Prediction of potential drug targets based on simple sequence properties

Directory of Open Access Journals (Sweden)

Lai Luhua

2007-09-01

Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

Antibodies directed to drug epitopes to investigate the structure of drug-protein photoadducts. Recognition of a common photobound substructure in tiaprofenic acid/ketoprofen cross-photoreactivity.

Science.gov (United States)

Lahoz, A; Hernández, D; Miranda, M A; Pérez-Prieto, J; Morera, I M; Castell, J V

2001-11-01

Drug-induced photoallergy is an immune adverse reaction to the combined effect of drugs and light. From the mechanistic point of view, it first involves covalent binding of drug to protein resulting in the formation of a photoantigen. Hence, determination of the structures of drug-protein photoadducts is of great relevance to understand the molecular basis of photoallergy and cross-immunoreactivity among drugs. Looking for new strategies to investigate the covalent photobinding of drugs to proteins, we generated highly specific antibodies to drug chemical substructures. The availability of such antibodies has allowed us to discriminate between the different modes by which tiaprofenic acid (TPA), suprofen (SUP), and ketoprofen (KTP) photobind to proteins. The finding that the vast majority of the TPA photoadduct can be accounted for by means of antibody anti-benzoyl strongly supports the view that the drug binds preferentially via the thiophene ring, leaving the benzene ring more accessible. By contrast, selective recognition of SUP-protein photoadducts by antibody anti-thenoyl evidences a preferential coupling via the benzene ring leaving the thiophene moiety more distant from the protein matrix. In the case of KTP, photoadducts are exclusively recognized by antibody anti-benzoyl, indicating that the benzene ring is again more accessible. As a result of this research, we have been able to identify a common substructure that is present in TPA-albumin and KTP-albumin photoadducts. This is remarkable since, at a first sight, the greatest structural similarities can be found between TPA and SUP as they share the same benzoylthiophene chromophore. These findings can explain the previously reported observations of cross-reactivity to KTP (or TPA) in patients photosensitized to TPA (or KTP).

PockDrug: A Model for Predicting Pocket Druggability That Overcomes Pocket Estimation Uncertainties.

Science.gov (United States)

Borrel, Alexandre; Regad, Leslie; Xhaard, Henri; Petitjean, Michel; Camproux, Anne-Claude

2015-04-27

Predicting protein druggability is a key interest in the target identification phase of drug discovery. Here, we assess the pocket estimation methods' influence on druggability predictions by comparing statistical models constructed from pockets estimated using different pocket estimation methods: a proximity of either 4 or 5.5 Å to a cocrystallized ligand or DoGSite and fpocket estimation methods. We developed PockDrug, a robust pocket druggability model that copes with uncertainties in pocket boundaries. It is based on a linear discriminant analysis from a pool of 52 descriptors combined with a selection of the most stable and efficient models using different pocket estimation methods. PockDrug retains the best combinations of three pocket properties which impact druggability: geometry, hydrophobicity, and aromaticity. It results in an average accuracy of 87.9% ± 4.7% using a test set and exhibits higher accuracy (∼5-10%) than previous studies that used an identical apo set. In conclusion, this study confirms the influence of pocket estimation on pocket druggability prediction and proposes PockDrug as a new model that overcomes pocket estimation variability.

Effect of nonsteroidal antiinflammatory drugs on the C-reactive protein level in rheumatoid arthritis

DEFF Research Database (Denmark)

Tarp, Simon; Bartels, Else M.; Bliddal, Henning

2012-01-01

To evaluate the effects of oral nonsteroidal antiinflammatory drugs (NSAIDs) on C-reactive protein (CRP) levels in rheumatoid arthritis (RA) patients, with a prespecified focus on the different NSAIDs.......To evaluate the effects of oral nonsteroidal antiinflammatory drugs (NSAIDs) on C-reactive protein (CRP) levels in rheumatoid arthritis (RA) patients, with a prespecified focus on the different NSAIDs....

Polyionic hydrocolloids for the intestinal delivery of protein drugs: alginate and chitosan--a review.

Science.gov (United States)

George, Meera; Abraham, T Emilia

2006-08-10

The protein pharmaceutical market is rapidly growing, since it is gaining support from the recombinant DNA technology. To deliver these drugs via the oral route, the most preferred route, is the toughest challenge. In the design of oral delivery of peptide or protein drugs, pH sensitive hydrogels like alginate and chitosan have attracted increasing attention, since most of the synthetic polymers are immunogenic and the incorporation of proteins in to these polymers require harsh environment which may denature and inactivate the desired protein. Alginate is a water-soluble linear polysaccharide composed of alternating blocks of 1-4 linked alpha-L-guluronic and beta-D-mannuronic acid residues where as chitosan is a co polymer of D-glucosamine and N-acetyl glucosamine. The incorporation of protein into these two matrices can be done under relatively mild environment and hence the chances of protein denaturation are minimal. The limitations of these polymers, like drug leaching during preparation can be overcome by different techniques which increase their encapsulation efficiency. Alginate, being an anionic polymer with carboxyl end groups, is a good mucoadhesive agent. The pore size of alginate gel microbeads has been shown to be between 5 and 200 nm and coated beads and microspheres are found to be better oral delivery vehicles. Cross-linked alginate has more capacity to retain the entrapped drugs and mixing of alginate with other polymers such as neutral gums, pectin, chitosan, and eudragit have been found to solve the problem of drug leaching. Chitosan has only limited ability for controlling the release of encapsulated compound due to its hydrophilic nature and easy solubility in acidic medium. By simple covalent modifications of the polymer, its physicochemical properties can be changed and can be made suitable for the peroral drug delivery purpose. Ionic interactions between positively charged amino groups in chitosan and the negatively charged mucus gel layer

Investigating drug repositioning opportunities in FDA drug labels through topic modeling.

Science.gov (United States)

Bisgin, Halil; Liu, Zhichao; Kelly, Reagan; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-01-01

Drug repositioning offers an opportunity to revitalize the slowing drug discovery pipeline by finding new uses for currently existing drugs. Our hypothesis is that drugs sharing similar side effect profiles are likely to be effective for the same disease, and thus repositioning opportunities can be identified by finding drug pairs with similar side effects documented in U.S. Food and Drug Administration (FDA) approved drug labels. The safety information in the drug labels is usually obtained in the clinical trial and augmented with the observations in the post-market use of the drug. Therefore, our drug repositioning approach can take the advantage of more comprehensive safety information comparing with conventional de novo approach. A probabilistic topic model was constructed based on the terms in the Medical Dictionary for Regulatory Activities (MedDRA) that appeared in the Boxed Warning, Warnings and Precautions, and Adverse Reactions sections of the labels of 870 drugs. Fifty-two unique topics, each containing a set of terms, were identified by using topic modeling. The resulting probabilistic topic associations were used to measure the distance (similarity) between drugs. The success of the proposed model was evaluated by comparing a drug and its nearest neighbor (i.e., a drug pair) for common indications found in the Indications and Usage Section of the drug labels. Given a drug with more than three indications, the model yielded a 75% recall, meaning 75% of drug pairs shared one or more common indications. This is significantly higher than the 22% recall rate achieved by random selection. Additionally, the recall rate grows rapidly as the number of drug indications increases and reaches 84% for drugs with 11 indications. The analysis also demonstrated that 65 drugs with a Boxed Warning, which indicates significant risk of serious and possibly life-threatening adverse effects, might be replaced with safer alternatives that do not have a Boxed Warning. In

Protein encapsulated magnetic carriers for micro/nanoscale drug delivery systems.

Energy Technology Data Exchange (ETDEWEB)

Xie, Y.; Kaminski, M. D.; Mertz, C. J.; Finck, M. R.; Guy, S. G.; Chen, H.; Rosengart, A. J.; Chemical Engineering; Univ. of Chicago, Pritzker School of Medicine

2005-01-01

Novel methods for drug delivery may be based on nanotechnology using non-invasive magnetic guidance of drug loaded magnetic carriers to the targeted site and thereafter released by external ultrasound energy. The key building block of this system is to successfully synthesize biodegradable, magnetic drug carriers. Magnetic carriers using poly(D,L-lactide-co-glycolide) (PLGA) or poly(lactic acid)-poly(ethylene glycol) (PLA-PEG) as matrix materials were loaded with bovine serum albumin (BSA) by a double-emulsion technique. BSA-loaded magnetic microspheres were characterized for size, morphology, surface charge, and magnetization. The BSA encapsulation efficiency was determined by recovering albumin from the microspheres using dimethyl sulfoxide and 0.05N NaOH/0.5% SDS then quantifying with the Micro-BCA protein assay. BSA release profiles were also determined by the Micro-BCA protein assay. The microspheres had drug encapsulation efficiencies up to 90% depending on synthesis parameters. Particles were spherical with a smooth or porous surface having a size range less than 5 {mu}m. The surface charge (expressed as zeta potential) was near neutral, optimal for prolonged intravascular survival. The magnetization of these BSA loaded magnetic carriers was 2 to 6 emu/g, depending on the specific magnetic materials used during synthesis.

Effect of Antimalarial Drugs on Plasmodia Cell-Free Protein Synthesis

Directory of Open Access Journals (Sweden)

Ana Ferreras

2002-04-01

Full Text Available A cell-free system from Plasmodium falciparum able to translate endogenous mRNA was used to determine the effect of artemisinin, chloroquine and primaquine on the protein synthesis mechanism of the parasite. The antimalarial drugs did not inhibit the incorporation of [³H] methionine into parasite proteins even at concentrations higher than the ones found to strongly inhibit the parasite growth. Results clearly indicate that these compounds do not have a direct effect on protein synthesis activity of P. falciparum coded by endogenous mRNA.

Protein-lipid nanohybrids as emerging platforms for drug and gene delivery: Challenges and outcomes.

Science.gov (United States)

Gaber, Mohamed; Medhat, Waseem; Hany, Mark; Saher, Nourhan; Fang, Jia-You; Elzoghby, Ahmed

2017-05-28

Nanoparticulate drug delivery systems have been long used to deliver a vast range of drugs and bioactives owing to their ability to demonstrate novel physical, chemical, and/or biological properties. An exponential growth has spurred in research and development of these nanocarriers which led to the evolution of a great number of diverse nanosystems including liposomes, nanoemulsions, solid lipid nanoparticles (SLNs), micelles, dendrimers, polymeric nanoparticles (NPs), metallic NPs, and carbon nanotubes. Among them, lipid-based nanocarriers have made the largest progress whether commercially or under development. Despite this progress, these lipid-based nanocarriers suffer from several limitations that led to the development of many protein-coated lipid nanocarriers. To less extent, protein-based nanocarriers suffer from limitations that led to the fabrication of some lipid bilayer enveloping protein nanocarriers. This review discusses in-depth some limitations associated with the lipid-based or protein-based nanocarriers and the fruitful outcomes brought by protein-lipid hybridization. Also discussed are the various hybridization techniques utilized to formulate these protein-lipid nanohybrids and the mechanisms involved in the drug loading process. Copyright © 2017 Elsevier B.V. All rights reserved.

Oral Delivery of Protein Drugs Bioencapsulated in Plant Cells.

Science.gov (United States)

Kwon, Kwang-Chul; Daniell, Henry

2016-08-01

Plants cells are now approved by the FDA for cost-effective production of protein drugs (PDs) in large-scale current Good Manufacturing Practice (cGMP) hydroponic growth facilities. In lyophilized plant cells, PDs are stable at ambient temperature for several years, maintaining their folding and efficacy. Upon oral delivery, PDs bioencapsulated in plant cells are protected in the stomach from acids and enzymes but are subsequently released into the gut lumen by microbes that digest the plant cell wall. The large mucosal area of the human intestine offers an ideal system for oral drug delivery. When tags (receptor-binding proteins or cell-penetrating peptides) are fused to PDs, they efficiently cross the intestinal epithelium and are delivered to the circulatory or immune system. Unique tags to deliver PDs to human immune or nonimmune cells have been developed recently. After crossing the epithelium, ubiquitous proteases cleave off tags at engineered sites. PDs are also delivered to the brain or retina by crossing the blood-brain or retinal barriers. This review highlights recent advances in PD delivery to treat Alzheimer's disease, diabetes, hypertension, Gaucher's or ocular diseases, as well as the development of affordable drugs by eliminating prohibitively expensive purification, cold chain and sterile delivery.

The Protein Model Portal.

Science.gov (United States)

Arnold, Konstantin; Kiefer, Florian; Kopp, Jürgen; Battey, James N D; Podvinec, Michael; Westbrook, John D; Berman, Helen M; Bordoli, Lorenza; Schwede, Torsten

2009-03-01

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at http://www.proteinmodelportal.org and from the PSI Structural Genomics Knowledgebase.

Mechanisms of drug resistance in cancer cells

International Nuclear Information System (INIS)

Iqbal, M.P.

2003-01-01

Development of drug resist chemotherapy. For the past several years, investigators have been striving hard to unravel mechanisms of drug resistance in cancer cells. Using different experimental models of cancer, some of the major mechanisms of drug resistance identified in mammalian cells include: (a) Altered transport of the drug (decreased influx of the drug; increased efflux of the drug (role of P-glycoprotein; role of polyglutamation; role of multiple drug resistance associated protein)), (b) Increase in total amount of target enzyme/protein (gene amplification), (c) alteration in the target enzyme/protein (low affinity enzyme), (d) Elevation of cellular glutathione, (e) Inhibition of drug-induced apoptosis (mutation in p53 tumor suppressor gene; increased expression of bcl-xl gene). (author)

Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

Directory of Open Access Journals (Sweden)

Sudin eBhattacharya

2012-12-01

Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

Ceramic core with polymer corona hybrid nanocarrier for the treatment of osteosarcoma with co-delivery of protein and anti-cancer drug

Science.gov (United States)

Ram Prasad, S.; Sampath Kumar, T. S.; Jayakrishnan, A.

2018-01-01

For the treatment of metastatic bone cancer, local delivery of therapeutic agents is preferred compared to systemic administration. Delivery of an anti-cancer drug and a protein that helps in bone regeneration simultaneously is a challenging approach. In this study, a nanoparticulate carrier which delivers a protein and an anti-cancer drug is reported. Bovine serum albumin (BSA) as a model protein was loaded into hydroxyapatite (HA) nanoparticles (NPs) and methotrexate (MTX) conjugated to poly(vinyl alcohol) was coated onto BSA-loaded HA NPs. Coating efficiency was in the range of 10-17 wt%. In vitro drug release showed that there was a steady increase in the release of both BSA and MTX with 76% of BSA and 88% of MTX being released in 13 days. Cytotoxicity studies of the NPs performed using human osteosarcoma (OMG-63) cell line showed the NPs were highly biocompatible and exhibited anti-proliferative activity in a concentration-dependent manner.

Drug repurposing for aging research using model organisms.

Science.gov (United States)

Ziehm, Matthias; Kaur, Satwant; Ivanov, Dobril K; Ballester, Pedro J; Marcus, David; Partridge, Linda; Thornton, Janet M

2017-10-01

Many increasingly prevalent diseases share a common risk factor: age. However, little is known about pharmaceutical interventions against aging, despite many genes and pathways shown to be important in the aging process and numerous studies demonstrating that genetic interventions can lead to a healthier aging phenotype. An important challenge is to assess the potential to repurpose existing drugs for initial testing on model organisms, where such experiments are possible. To this end, we present a new approach to rank drug-like compounds with known mammalian targets according to their likelihood to modulate aging in the invertebrates Caenorhabditis elegans and Drosophila. Our approach combines information on genetic effects on aging, orthology relationships and sequence conservation, 3D protein structures, drug binding and bioavailability. Overall, we rank 743 different drug-like compounds for their likelihood to modulate aging. We provide various lines of evidence for the successful enrichment of our ranking for compounds modulating aging, despite sparse public data suitable for validation. The top ranked compounds are thus prime candidates for in vivo testing of their effects on lifespan in C. elegans or Drosophila. As such, these compounds are promising as research tools and ultimately a step towards identifying drugs for a healthier human aging. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Animal models of drug addiction.

Science.gov (United States)

García Pardo, María Pilar; Roger Sánchez, Concepción; De la Rubia Ortí, José Enrique; Aguilar Calpe, María Asunción

2017-09-29

The development of animal models of drug reward and addiction is an essential factor for progress in understanding the biological basis of this disorder and for the identification of new therapeutic targets. Depending on the component of reward to be studied, one type of animal model or another may be used. There are models of reinforcement based on the primary hedonic effect produced by the consumption of the addictive substance, such as the self-administration (SA) and intracranial self-stimulation (ICSS) paradigms, and there are models based on the component of reward related to associative learning and cognitive ability to make predictions about obtaining reward in the future, such as the conditioned place preference (CPP) paradigm. In recent years these models have incorporated methodological modifications to study extinction, reinstatement and reconsolidation processes, or to model specific aspects of addictive behavior such as motivation to consume drugs, compulsive consumption or drug seeking under punishment situations. There are also models that link different reinforcement components or model voluntary motivation to consume (two-bottle choice, or drinking in the dark tests). In short, innovations in these models allow progress in scientific knowledge regarding the different aspects that lead individuals to consume a drug and develop compulsive consumption, providing a target for future treatments of addiction.

Overcoming T. gondii infection and intracellular protein nanocapsules as biomaterials for ultrasonically controlled drug release.

Science.gov (United States)

Aw, M S; Paniwnyk, L

2017-09-26

One of the pivotal matters of concern in intracellular drug delivery is the preparation of biomaterials containing drugs that are compatible with the host target. Nanocapsules for oral delivery are found to be suitable candidates for targeting Toxoplasma gondii (T. gondii), a maneuvering and smart protozoic parasite found across Europe and America that causes a subtle but deadly infection. To overcome this disease, there is much potential of integrating protein-based cells into bioinspired nanocompartments such as via biodegradable cross-linked disulfide polyelectrolyte nanoparticles. The inner membrane vesicle system of these protein-drugs is not as simple as one might think. It is a complex transport network that includes sequential pathways, namely, endocytosis, exocytosis and autophagy. Unfortunately, the intracellular trafficking routes for nanoparticles in cells have not been extensively and intensively investigated. Hence, there lies the need to create robust protein nanocapsules for precise tracing and triggering of drug release to combat this protozoic disease. Protein nanocapsules have the advantage over other biomaterials due to their biocompatibility, use of natural ingredients, non-invasiveness, patient compliance, cost and time effectiveness. They also offer low maintenance, non-toxicity to healthy cells and a strictly defined route toward intracellular elimination through controlled drug delivery within the therapeutic window. This review covers the unprecedented opportunities that exist for constructing advanced nanocapsules to meet the growing needs arising from many therapeutic fields. Their versatile use includes therapeutic ultrasound for tumor imaging, recombinant DNA, ligand and functional group binding, the delivery of drugs and peptides via protein nanocapsules and polyelectrolytes, ultrasound-(US)-aided drug release through the gastrointestinal (GI) tract, and the recent progress in targeting tumor cells and a vast range of cancer therapies

Assessing the structural conservation of protein pockets to study functional and allosteric sites: implications for drug discovery

Directory of Open Access Journals (Sweden)

Daura Xavier

2010-03-01

Full Text Available Abstract Background With the classical, active-site oriented drug-development approach reaching its limits, protein ligand-binding sites in general and allosteric sites in particular are increasingly attracting the interest of medicinal chemists in the search for new types of targets and strategies to drug development. Given that allostery represents one of the most common and powerful means to regulate protein function, the traditional drug discovery approach of targeting active sites can be extended by targeting allosteric or regulatory protein pockets that may allow the discovery of not only novel drug-like inhibitors, but activators as well. The wealth of available protein structural data can be exploited to further increase our understanding of allosterism, which in turn may have therapeutic applications. A first step in this direction is to identify and characterize putative effector sites that may be present in already available structural data. Results We performed a large-scale study of protein cavities as potential allosteric and functional sites, by integrating publicly available information on protein sequences, structures and active sites for more than a thousand protein families. By identifying common pockets across different structures of the same protein family we developed a method to measure the pocket's structural conservation. The method was first parameterized using known active sites. We characterized the predicted pockets in terms of sequence and structural conservation, backbone flexibility and electrostatic potential. Although these different measures do not tend to correlate, their combination is useful in selecting functional and regulatory sites, as a detailed analysis of a handful of protein families shows. We finally estimated the numbers of potential allosteric or regulatory pockets that may be present in the data set, finding that pockets with putative functional and effector characteristics are widespread across

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

Science.gov (United States)

Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein. In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking

Distribution of Animal Drugs among Curd, Whey, and Milk Protein Fractions in Spiked Skim Milk and Whey.

Science.gov (United States)

Shappell, Nancy W; Shelver, Weilin L; Lupton, Sara J; Fanaselle, Wendy; Van Doren, Jane M; Hakk, Heldur

2017-02-01

It is important to understand the partitioning of drugs in processed milk and milk products, when drugs are present in raw milk, in order to estimate the potential consumer exposure. Radioisotopically labeled erythromycin, ivermectin, ketoprofen, oxytetracycline, penicillin G, sulfadimethoxine, and thiabendazole were used to evaluate the distribution of animal drugs among rennet curd, whey, and protein fractions from skim cow milk. Our previous work reported the distribution of these same drugs between skim and fat fractions of milk. Drug distribution between curd and whey was significantly correlated (R 2 = 0.70) to the drug's lipophilicity (log P), with improved correlation using log D (R 2 = 0.95). Distribution of drugs was concentration independent over the range tested (20-2000 nM). With the exception of thiabendazole and ivermectin, more drug was associated with whey protein than casein on a nmol/g protein basis (oxytetracycline experiment not performed). These results provide insights into the distribution of animal drug residues, if present in cow milk, among milk fractions, with possible extrapolation to milk products.

Recent advances in protein and Peptide drug delivery: a special emphasis on polymeric nanoparticles.

Science.gov (United States)

Patel, Ashaben; Patel, Mitesh; Yang, Xiaoyan; Mitra, Ashim K

2014-01-01

Proteins and peptides are widely indicated in many diseased states. Parenteral route is the most commonly em- ployed method of administration for therapeutic proteins and peptides. However, requirement of frequent injections due to short in vivo half-life results in poor patient compliance. Non-invasive drug delivery routes such as nasal, transdermal, pulmonary, and oral offer several advantages over parenteral administration. Intrinsic physicochemical properties and low permeability across biological membrane limit protein delivery via non-invasive routes. One of the strategies to improve protein and peptide absorption is by delivering through nanostructured delivery carriers. Among nanocarriers, polymeric nanoparticles (NPs) have demonstrated significant advantages over other delivery systems. This article summarizes the application of polymeric NPs for protein and peptide drug delivery following oral, nasal, pulmonary, parenteral, transder mal, and ocular administrations.

Protein folding and non-conventional drug design: a primer for nuclear structure physicists

International Nuclear Information System (INIS)

Broglia, R.A.; Tiana, G.; Provasi, D.

2004-01-01

Some of the paradigms emerging from the study of the phenomena of phase transitions in finite many-body systems, like e.g. the atomic nucleus can be used at profit to solve the protein folding problem within the framework of simple (although not oversimplified) models. From this solution a paradigm emerges for the design of non-conventional drugs, which inhibit enzymatic action without inducing resistance (mutations). The application of these concepts to the design of an inhibitor to the HIV-protease central in the life cycle of the HIV virus is discussed

The Protein Model Portal

OpenAIRE

Arnold, Konstantin; Kiefer, Florian; Kopp, J?rgen; Battey, James N. D.; Podvinec, Michael; Westbrook, John D.; Berman, Helen M.; Bordoli, Lorenza; Schwede, Torsten

2008-01-01

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploratio...

In vitro haematic proteins adsorption and cytocompatibility study on acrylic copolymer to realise coatings for drug-eluting stents

International Nuclear Information System (INIS)

Gagliardi, Mariacristina

2012-01-01

In the present paper, a preliminary in vitro analysis of biocompatibility of newly-synthesised acrylic copolymers is reported. In particular, with the aim to obtain coatings for drug-eluting stents, blood protein absorption and cytocompatibility were studied. For protein absorption tests, bovine serum albumin and bovine plasma fibrinogen were considered. Cytocompatibility was tested using C2C12 cell line as model, analysing the behaviour of polymeric matrices and of drug-eluting systems, obtained loading polymeric matrices with paclitaxel, an anti-mitotic drug, in order to evaluate the efficacy of a pharmacological treatment locally administered from these materials. Results showed that the amount of albumin absorbed was greater than the amount of fibrinogen (comprised in the range of 70%–85% and 10%–22% respectively) and it is a good behaviour in terms of haemocompatibility. Cell culture tests showed good adhesion properties and a relative poor proliferation. In addition, a strong effect related to drug elution and a correlation with the macromolecular composition were detected. In this preliminary analysis, tested materials showed good characteristics and can be considered possible candidates to obtain coatings for drug-eluting stents. Highlights: ► Preliminary evaluation of haemo- and cytocompatibility of newly-synthesised acrylic copolymers ► Materials adsorb higher amounts of albumin and with a faster rate than fibrinogen. ► Protein adsorption depended on the macromolecular composition and surface properties. ► Cell viability on pure samples and efficacy of paclitaxel release were verified in C2C12 cultures.

In vitro haematic proteins adsorption and cytocompatibility study on acrylic copolymer to realise coatings for drug-eluting stents

Energy Technology Data Exchange (ETDEWEB)

Gagliardi, Mariacristina, E-mail: mariacristina.gagliardi@iit.it

2012-12-01

In the present paper, a preliminary in vitro analysis of biocompatibility of newly-synthesised acrylic copolymers is reported. In particular, with the aim to obtain coatings for drug-eluting stents, blood protein absorption and cytocompatibility were studied. For protein absorption tests, bovine serum albumin and bovine plasma fibrinogen were considered. Cytocompatibility was tested using C2C12 cell line as model, analysing the behaviour of polymeric matrices and of drug-eluting systems, obtained loading polymeric matrices with paclitaxel, an anti-mitotic drug, in order to evaluate the efficacy of a pharmacological treatment locally administered from these materials. Results showed that the amount of albumin absorbed was greater than the amount of fibrinogen (comprised in the range of 70%-85% and 10%-22% respectively) and it is a good behaviour in terms of haemocompatibility. Cell culture tests showed good adhesion properties and a relative poor proliferation. In addition, a strong effect related to drug elution and a correlation with the macromolecular composition were detected. In this preliminary analysis, tested materials showed good characteristics and can be considered possible candidates to obtain coatings for drug-eluting stents. Highlights: Black-Right-Pointing-Pointer Preliminary evaluation of haemo- and cytocompatibility of newly-synthesised acrylic copolymers Black-Right-Pointing-Pointer Materials adsorb higher amounts of albumin and with a faster rate than fibrinogen. Black-Right-Pointing-Pointer Protein adsorption depended on the macromolecular composition and surface properties. Black-Right-Pointing-Pointer Cell viability on pure samples and efficacy of paclitaxel release were verified in C2C12 cultures.

Promotion of the transdermal delivery of protein drugs by N-trimethyl chitosan nanoparticles combined with polypropylene electret.

Science.gov (United States)

Tu, Ye; Wang, Xinxia; Lu, Ying; Zhang, He; Yu, Yuan; Chen, Yan; Liu, Junjie; Sun, Zhiguo; Cui, Lili; Gao, Jing; Zhong, Yanqiang

We recently reported that electret, which was prepared by a corona charging system with polypropylene film, could enhance the transdermal delivery of several drugs of low molecular weight. The aim of this study was to investigate whether electret could enhance the transdermal delivery of protein drugs by N -trimethyl chitosan nanoparticles (TMC NPs) prepared by an ionic gelation method. A series of experiments were performed, including in vitro skin permeation assays and anti-inflammatory effects, to evaluate the transdermal delivery of protein drugs by TMC NPs in the presence of electret. The results showed that in the presence of electret, the transdermal delivery of protein drugs in TMC NPs was significantly enhanced, as demonstrated by in vitro permeation studies and confocal laser scanning microscopy. Notably, superoxide dismutase-loaded TMC NPs combined with electret exhibited the best inhibitory effect on the edema of the mouse ear. TMC NPs combined with electret represent a novel platform for the transdermal delivery of protein drugs.

Overview on zein protein: a promising pharmaceutical excipient in drug delivery systems and tissue engineering.

Science.gov (United States)

Labib, Gihan

2018-01-01

Natural pharmaceutical excipients have been applied extensively in the past decades owing to their safety and biocompatibility. Zein, a natural protein of plant origin offers great benefit over other synthetic polymers used in controlled drug and biomedical delivery systems. It was used in a variety of medical fields including pharmaceutical and biomedical drug targeting, vaccine, tissue engineering, and gene delivery. Being biodegradable and biocompatible, the current review focuses on the history and the medical application of zein as an attractive still promising biopolymer. Areas covered: The current review gives a broadscope on zein as a still promising protein excipient in different fields. Zein- based drug and biomedical delivery systems are discussed with special focus on current and potential application in controlled drug delivery systems, and tissue engineering. Expert opinion: Zein as a protein of natural origin can still be considered a promising polymer in the field of drug delivery systems as well as in tissue engineering. Although different researchers spotted light on zein application in different industrial fields extensively, the feasibility of its use in the field of drug delivery replenished by investigators in recent years has not yet been fully approached.

Calibration and LOD/LOQ estimation of a chemiluminescent hybridization assay for residual DNA in recombinant protein drugs expressed in E. coli using a four-parameter logistic model.

Science.gov (United States)

Lee, K R; Dipaolo, B; Ji, X

2000-06-01

Calibration is the process of fitting a model based on reference data points (x, y), then using the model to estimate an unknown x based on a new measured response, y. In DNA assay, x is the concentration, and y is the measured signal volume. A four-parameter logistic model was used frequently for calibration of immunoassay when the response is optical density for enzyme-linked immunosorbent assay (ELISA) or adjusted radioactivity count for radioimmunoassay (RIA). Here, it is shown that the same model or a linearized version of the curve are equally useful for the calibration of a chemiluminescent hybridization assay for residual DNA in recombinant protein drugs and calculation of performance measures of the assay.

The Role of ABC Proteins in Drug Resistant Breast Cancer Cells

Science.gov (United States)

2008-04-01

called the Plasmodium falciparum Chloroquine Transporter (PfCRT). While PfCRT is known to be the main molecular determinant of chloroquine resistance...proteins (such as human P-glycoprotein) and labeled PfCRT with a photoaffinity drug analogue . A manuscript is currently in preparation detailing my results...directly responsible for drug response, the Plasmodium falciparum Chloroquine Resistance Transporter (PfCRT) (Fidock et al 2000). While not a member of

Bioengineered Liver Models for Drug Testing and Cell Differentiation Studies

Directory of Open Access Journals (Sweden)

Gregory H. Underhill

2018-01-01

Full Text Available In vitro models of the human liver are important for the following: (1 mitigating the risk of drug-induced liver injury to human beings, (2 modeling human liver diseases, (3 elucidating the role of single and combinatorial microenvironmental cues on liver cell function, and (4 enabling cell-based therapies in the clinic. Methods to isolate and culture primary human hepatocytes (PHHs, the gold standard for building human liver models, were developed several decades ago; however, PHHs show a precipitous decline in phenotypic functions in 2-dimensional extracellular matrix–coated conventional culture formats, which does not allow chronic treatment with drugs and other stimuli. The development of several engineering tools, such as cellular microarrays, protein micropatterning, microfluidics, biomaterial scaffolds, and bioprinting, now allow precise control over the cellular microenvironment for enhancing the function of both PHHs and induced pluripotent stem cell–derived human hepatocyte-like cells; long-term (4+ weeks stabilization of hepatocellular function typically requires co-cultivation with liver-derived or non–liver-derived nonparenchymal cell types. In addition, the recent development of liver organoid culture systems can provide a strategy for the enhanced expansion of therapeutically relevant cell types. Here, we discuss advances in engineering approaches for constructing in vitro human liver models that have utility in drug screening and for determining microenvironmental determinants of liver cell differentiation/function. Design features and validation data of representative models are presented to highlight major trends followed by the discussion of pending issues that need to be addressed. Overall, bioengineered liver models have significantly advanced our understanding of liver function and injury, which will prove useful for drug development and ultimately cell-based therapies.

Bcl-2 family of proteins as drug targets for cancer chemotherapy: the long way of BH3 mimetics from bench to bedside.

Science.gov (United States)

Vela, Laura; Marzo, Isabel

2015-08-01

Bcl-2 proteins are key determinants in the life-death balance. In recent years, proteins in this family have been identified as drug targets in the design of new anti-tumor therapies. Advances in the knowledge of the mechanism of action of anti-apoptotic and pro-apoptotic members of the Bcl-2 family have enabled the development of the so-called 'BH3 mimetics'. These compounds act by inhibiting anti-apoptotic proteins of the family, imitating the function of the BH3-only subset of pro-apoptotic members. Combinations of BH3-mimetics with anti-tumor drugs are being evaluated in both preclinical models and clinical trials. Recent advances in these approaches will be reviewed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Denatured protein-coated docetaxel nanoparticles: Alterable drug state and cytosolic delivery.

Science.gov (United States)

Zhang, Li; Xiao, Qingqing; Wang, Yiran; Zhang, Chenshuang; He, Wei; Yin, Lifang

2017-05-15

Many lead compounds have a low solubility in water, which substantially hinders their clinical application. Nanosuspensions have been considered a promising strategy for the delivery of water-insoluble drugs. Here, denatured soy protein isolate (SPI)-coated docetaxel nanosuspensions (DTX-NS) were developed using an anti-solvent precipitation-ultrasonication method to improve the water-solubility of DTX, thus improving its intracellular delivery. DTX-NS, with a diameter of 150-250nm and drug-loading up to 18.18%, were successfully prepared by coating drug particles with SPI. Interestingly, the drug state of DTX-NS was alterable. Amorphous drug nanoparticles were obtained at low drug-loading, whereas at a high drug-loading, the DTX-NS drug was mainly present in the crystalline state. Moreover, DTX-NS could be internalized at high levels by cancer cells and enter the cytosol by lysosomal escape, enhancing cell cytotoxicity and apoptosis compared with free DTX. Taken together, denatured SPI has a strong stabilization effect on nanosuspensions, and the drug state in SPI-coated nanosuspensions is alterable by changing the drug-loading. Moreover, DTX-NS could achieve cytosolic delivery, generating enhanced cell cytotoxicity against cancer cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Validation-driven protein-structure improvement

NARCIS (Netherlands)

Touw, W.G.

2016-01-01

High-quality protein structure models are essential for many Life Science applications, such as protein engineering, molecular dynamics, drug design, and homology modelling. The WHAT_CHECK model validation project and the PDB_REDO model optimisation project have shown that many structure models in

The Role of Extracellular Binding Proteins in the Cellular Uptake of Drugs: Impact on Quantitative In Vitro-to-In Vivo Extrapolations of Toxicity and Efficacy in Physiologically Based Pharmacokinetic-Pharmacodynamic Research.

Science.gov (United States)

Poulin, Patrick; Burczynski, Frank J; Haddad, Sami

2016-02-01

A critical component in the development of physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) models for estimating target organ dosimetry in pharmacology and toxicology studies is the understanding of the uptake kinetics and accumulation of drugs and chemicals at the cellular level. Therefore, predicting free drug concentrations in intracellular fluid will contribute to our understanding of concentrations at the site of action in cells in PBPK/PD research. Some investigators believe that uptake of drugs in cells is solely driven by the unbound fraction; conversely, others argue that the protein-bound fraction contributes a significant portion of the total amount delivered to cells. Accordingly, the current literature suggests the existence of a so-called albumin-mediated uptake mechanism(s) for the protein-bound fraction (i.e., extracellular protein-facilitated uptake mechanisms) at least in hepatocytes and cardiac myocytes; however, such mechanism(s) and cells from other organs deserve further exploration. Therefore, the main objective of this present study was to discuss further the implication of potential protein-facilitated uptake mechanism(s) on drug distribution in cells under in vivo conditions. The interplay between the protein-facilitated uptake mechanism(s) and the effects of a pH gradient, metabolism, transport, and permeation limitation potentially occurring in cells was also discussed, as this should violate the basic assumption on similar free drug concentration in cells and plasma. This was made because the published equations used to calculate drug concentrations in cells in a PBPK/PD model did not consider potential protein-facilitated uptake mechanism(s). Consequently, we corrected some published equations for calculating the free drug concentrations in cells compared with plasma in PBPK/PD modeling studies, and we proposed a refined strategy for potentially performing more accurate quantitative in vitro-to-in vivo extrapolations

Structure of liposome encapsulating proteins characterized by X-ray scattering and shell-modeling

International Nuclear Information System (INIS)

Hirai, Mitsuhiro; Kimura, Ryota; Takeuchi, Kazuki; Hagiwara, Yoshihiko; Kawai-Hirai, Rika; Ohta, Noboru; Igarashi, Noriyuki; Shimuzu, Nobutaka

2013-01-01

Wide-angle X-ray scattering data using a third-generation synchrotron radiation source are presented. Lipid liposomes are promising drug delivery systems because they have superior curative effects owing to their high adaptability to a living body. Lipid liposomes encapsulating proteins were constructed and the structures examined using synchrotron radiation small- and wide-angle X-ray scattering (SR-SWAXS). The liposomes were prepared by a sequential combination of natural swelling, ultrasonic dispersion, freeze-throw, extrusion and spin-filtration. The liposomes were composed of acidic glycosphingolipid (ganglioside), cholesterol and phospholipids. By using shell-modeling methods, the asymmetric bilayer structure of the liposome and the encapsulation efficiency of proteins were determined. As well as other analytical techniques, SR-SWAXS and shell-modeling methods are shown to be a powerful tool for characterizing in situ structures of lipid liposomes as an important candidate of drug delivery systems

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.

Drug-target residence time--a case for G protein-coupled receptors.

Science.gov (United States)

Guo, Dong; Hillger, Julia M; IJzerman, Adriaan P; Heitman, Laura H

2014-07-01

A vast number of marketed drugs act on G protein-coupled receptors (GPCRs), the most successful category of drug targets to date. These drugs usually possess high target affinity and selectivity, and such combined features have been the driving force in the early phases of drug discovery. However, attrition has also been high. Many investigational new drugs eventually fail in clinical trials due to a demonstrated lack of efficacy. A retrospective assessment of successfully launched drugs revealed that their beneficial effects in patients may be attributed to their long drug-target residence times (RTs). Likewise, for some other GPCR drugs short RT could be beneficial to reduce the potential for on-target side effects. Hence, the compounds' kinetics behavior might in fact be the guiding principle to obtain a desired and durable effect in vivo. We therefore propose that drug-target RT should be taken into account as an additional parameter in the lead selection and optimization process. This should ultimately lead to an increased number of candidate drugs moving to the preclinical development phase and on to the market. This review contains examples of the kinetics behavior of GPCR ligands with improved in vivo efficacy and summarizes methods for assessing drug-target RT. © 2014 Wiley Periodicals, Inc.

TIMP-1 increases expression and phosphorylation of proteins associated with drug resistance in breast cancer cells

DEFF Research Database (Denmark)

Hekmat, Omid; Munk, Stephanie; Fogh, Louise

2013-01-01

may explain the resistance phenotype to topoisomerase inhibitors that was observed in cells with high TIMP-1 levels. Pathway analysis showed an enrichment of proteins from functional categories such as apoptosis, cell cycle, DNA repair, transcription factors, drug targets and proteins associated......Tissue inhibitor of metalloproteinase 1 (TIMP-1) is a protein with a potential biological role in drug resistance. To elucidate the unknown molecular mechanisms underlying the association between high TIMP-1 levels and increased chemotherapy resistance, we employed SILAC-based quantitative mass...... spectrometry to analyze global proteome and phosphoproteome differences of MCF-7 breast cancer cells expressing high or low levels of TIMP-1. In TIMP-1 high expressing cells, 312 proteins and 452 phosphorylation sites were up-regulated. Among these were the cancer drug targets topoisomerase 1, 2A and 2B, which...

The transport of nifurtimox, an anti-trypanosomal drug, in an in vitro model of the human blood-brain barrier: evidence for involvement of breast cancer resistance protein.

Science.gov (United States)

Watson, Christopher P; Dogruel, Murat; Mihoreanu, Larisa; Begley, David J; Weksler, Babette B; Couraud, Pierre O; Romero, Ignacio A; Thomas, Sarah A

2012-02-03

Human African trypanosomiasis (HAT) is a parasitic disease affecting sub-Saharan Africa. The parasites are able to traverse the blood-brain barrier (BBB), which marks stage 2 (S2) of the disease. Delivery of anti-parasitic drugs across the BBB is key to treating S2 effectively and the difficulty in achieving this goal is likely to be a reason why some drugs require highly intensive treatment regimes to be effective. This study aimed to investigate not only the drug transport mechanisms utilised by nifurtimox at the BBB, but also the impact of nifurtimox-eflornithine combination therapy (NECT) and other anti-HAT drug combination therapies (CTs) on radiolabelled-nifurtimox delivery in an in vitro model of drug accumulation and the human BBB, the hCMEC/D3 cell line. We found that nifurtimox appeared to use several membrane transporters, in particular breast-cancer resistance protein (BCRP), to exit the BBB cells. The addition of eflornithine caused no change in the accumulation of nifurtimox, nor did the addition of clinically relevant doses of the other anti-HAT drugs suramin, nifurtimox or melarsoprol, but a significant increase was observed with the addition of pentamidine. The results provide evidence that anti-HAT drugs are interacting with membrane transporters at the human BBB and suggest that combination with known transport inhibitors could potentially improve their efficacy. Copyright © 2011 Elsevier B.V. All rights reserved.

The potential of protein-nanomaterial interaction for advanced drug delivery.

Science.gov (United States)

Peng, Qiang; Mu, Huiling

2016-03-10

Nanomaterials, like nanoparticles, micelles, nano-sheets, nanotubes and quantum dots, have great potentials in biomedical fields. However, their delivery is highly limited by the formation of protein corona upon interaction with endogenous proteins. This new identity, instead of nanomaterial itself, would be the real substance the organs and cells firstly encounter. Consequently, the behavior of nanomaterials in vivo is uncontrollable and some undesired effects may occur, like rapid clearance from blood stream; risk of capillary blockage; loss of targeting capacity; and potential toxicity. Therefore, protein-nanomaterial interaction is a great challenge for nanomaterial systems and should be inhibited. However, this interaction can also be used to functionalize nanomaterials by forming a selected protein corona. Unlike other decoration using exogenous molecules, nanomaterials functionalized by selected protein corona using endogenous proteins would have greater promise for clinical use. In this review, we aim to provide a comprehensive understanding of protein-nanomaterial interaction. Importantly, a discussion about how to use such interaction is launched and some possible applications of such interaction for advanced drug delivery are presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Simulations of CYP51A from Aspergillus fumigatus in a model bilayer provide insights into triazole drug resistance.

Science.gov (United States)

Nash, Anthony; Rhodes, Johanna

2018-04-01

Azole antifungal drugs target CYP51A in Aspergillus fumigatus by binding with the active site of the protein, blocking ergosterol biosynthesis. Resistance to azole antifungal drugs is now common, with a leucine to histidine amino acid substitution at position 98 the most frequent, predominantly conferring resistance to itraconazole, although cross-resistance has been reported in conjunction with other mutations. In this study, we create a homology model of CYP51A using a recently published crystal structure of the paralog protein CYP51B. The derived structures, wild type, and L98H mutant are positioned within a lipid membrane bilayer and subjected to molecular dynamics simulations in order improve the accuracy of both models. The structural analysis from our simulations suggests a decrease in active site surface from the formation of hydrogen bonds between the histidine substitution and neighboring polar side chains, potentially preventing the binding of azole drugs. This study yields a biologically relevant structure and set of dynamics of the A. fumigatus Lanosterol 14 alpha-demethylase enzyme and provides further insight into azole antifungal drug resistance.

Proteins with complex architecture as potential targets for drug design: a case study of Mycobacterium tuberculosis.

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Bálint Mészáros

2011-07-01

Full Text Available Lengthy co-evolution of Homo sapiens and Mycobacterium tuberculosis, the main causative agent of tuberculosis, resulted in a dramatically successful pathogen species that presents considerable challenge for modern medicine. The continuous and ever increasing appearance of multi-drug resistant mycobacteria necessitates the identification of novel drug targets and drugs with new mechanisms of action. However, further insights are needed to establish automated protocols for target selection based on the available complete genome sequences. In the present study, we perform complete proteome level comparisons between M. tuberculosis, mycobacteria, other prokaryotes and available eukaryotes based on protein domains, local sequence similarities and protein disorder. We show that the enrichment of certain domains in the genome can indicate an important function specific to M. tuberculosis. We identified two families, termed pkn and PE/PPE that stand out in this respect. The common property of these two protein families is a complex domain organization that combines species-specific regions, commonly occurring domains and disordered segments. Besides highlighting promising novel drug target candidates in M. tuberculosis, the presented analysis can also be viewed as a general protocol to identify proteins involved in species-specific functions in a given organism. We conclude that target selection protocols should be extended to include proteins with complex domain architectures instead of focusing on sequentially unique and essential proteins only.

SEIIrR: Drug abuse model with rehabilitation

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Sutanto, Azizah, Afina; Widyaningsih, Purnami; Saputro, Dewi Retno Sari

2017-05-01

Drug abuse in the world quite astonish and tend to increase. The increase and decrease on the number of drug abusers showed a pattern of spread that had the same characteristics with patterns of spread of infectious disease. The susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) epidemic models for infectious disease was developed to study social epidemic. In this paper, SEIR model for disease epidemic was developed to study drug abuse epidemic with rehabilitation treatment. The aims of this paper were to analogize susceptible exposed infected isolated recovered (SEIIrR) model on the drug abusers, to determine solutions of the model, to determine equilibrium point, and to do simulation on β. The solutions of SEIIrR model was determined by using fourth order of Runge-Kutta algorithm, equilibrium point obtained was free-drug equilibrium point. Solutions of SEIIrR showed that the model was able to suppress the spread of drug abuse. The increasing value of contact rate was not affect the number of infected individuals due to rehabilitation treatment.

Mathematical modeling of drug dissolution.

Science.gov (United States)

Siepmann, J; Siepmann, F

2013-08-30

The dissolution of a drug administered in the solid state is a pre-requisite for efficient subsequent transport within the human body. This is because only dissolved drug molecules/ions/atoms are able to diffuse, e.g. through living tissue. Thus, generally major barriers, including the mucosa of the gastro intestinal tract, can only be crossed after dissolution. Consequently, the process of dissolution is of fundamental importance for the bioavailability and, hence, therapeutic efficacy of various pharmaco-treatments. Poor aqueous solubility and/or very low dissolution rates potentially lead to insufficient availability at the site of action and, hence, failure of the treatment in vivo, despite a potentially ideal chemical structure of the drug to interact with its target site. Different physical phenomena are involved in the process of drug dissolution in an aqueous body fluid, namely the wetting of the particle's surface, breakdown of solid state bonds, solvation, diffusion through the liquid unstirred boundary layer surrounding the particle as well as convection in the surrounding bulk fluid. Appropriate mathematical equations can be used to quantify these mass transport steps, and more or less complex theories can be developed to describe the resulting drug dissolution kinetics. This article gives an overview on the current state of the art of modeling drug dissolution and points out the assumptions the different theories are based on. Various practical examples are given in order to illustrate the benefits of such models. This review is not restricted to mathematical theories considering drugs exhibiting poor aqueous solubility and/or low dissolution rates, but also addresses models quantifying drug release from controlled release dosage forms, in which the process of drug dissolution plays a major role. Copyright © 2013 Elsevier B.V. All rights reserved.

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

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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.

Conformational transition paths harbor structures useful for aiding drug discovery and understanding enzymatic mechanisms in protein kinases.

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Wong, Chung F

2016-01-01

This short article examines the usefulness of fast simulations of conformational transition paths in elucidating enzymatic mechanisms and guiding drug discovery for protein kinases. It applies the transition path method in the MOIL software package to simulate the paths of conformational transitions between six pairs of structures from the Protein Data Bank. The structures along the transition paths were found to resemble experimental structures that mimic transient structures believed to form during enzymatic catalysis or conformational transitions, or structures that have drug candidates bound. These findings suggest that such simulations could provide quick initial insights into the enzymatic mechanisms or pathways of conformational transitions of proteins kinases, or could provide structures useful for aiding structure-based drug design. © 2015 The Protein Society.

Mechanism of the pharmacokinetic interaction between methotrexate and benzimidazoles: potential role for breast cancer resistance protein in clinical drug-drug interactions

NARCIS (Netherlands)

Breedveld, Pauline; Zelcer, Noam; Pluim, Dick; Sönmezer, Ozgür; Tibben, Matthijs M.; Beijnen, Jos H.; Schinkel, Alfred H.; van Tellingen, Olaf; Borst, Piet; Schellens, Jan H. M.

2004-01-01

The antifolate drug methotrexate (MTX) is transported by breast cancer resistance protein (BCRP; ABCG2) and multidrug resistance-associated protein1-4 (MRP1-4; ABCC1-4). In cancer patients, coadministration of benzimidazoles and MTX can result in profound MTX-induced toxicity coinciding with an

The Protein Model Portal--a comprehensive resource for protein structure and model information.

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Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

2013-01-01

The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org.

The Protein Model Portal—a comprehensive resource for protein structure and model information

Science.gov (United States)

Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

2013-01-01

The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org PMID:23624946

Retrieval of Enterobacteriaceae drug targets using singular value decomposition.

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Silvério-Machado, Rita; Couto, Bráulio R G M; Dos Santos, Marcos A

2015-04-15

The identification of potential drug target proteins in bacteria is important in pharmaceutical research for the development of new antibiotics to combat bacterial agents that cause diseases. A new model that combines the singular value decomposition (SVD) technique with biological filters composed of a set of protein properties associated with bacterial drug targets and similarity to protein-coding essential genes of Escherichia coli (strain K12) has been created to predict potential antibiotic drug targets in the Enterobacteriaceae family. This model identified 99 potential drug target proteins in the studied family, which exhibit eight different functions and are protein-coding essential genes or similar to protein-coding essential genes of E.coli (strain K12), indicating that the disruption of the activities of these proteins is critical for cells. Proteins from bacteria with described drug resistance were found among the retrieved candidates. These candidates have no similarity to the human proteome, therefore exhibiting the advantage of causing no adverse effects or at least no known adverse effects on humans. rita_silverio@hotmail.com. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

How to calculate clearance of highly protein-bound drugs during continuous venovenous hemofiltration demonstrated with flucloxacillin.

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Meyer, Brigitte; Ahmed el Gendy, Salwa; Delle Karth, Georg; Locker, Gottfried J; Heinz, Gottfried; Jaeger, Walter; Thalhammer, Florian

2003-01-01

Flucloxacillin is an important antimicrobial drug in the treatment of infections with Staphylococcus aureus and therefore is often used in staphylococcal infections. Furthermore, flucloxacillin has a high protein binding rate as for example ceftriaxone or teicoplanin--drugs which have formerly been characterized as not being dialyzable. The pharmacokinetic parameters of 4.0 g flucloxacillin every 8 h were examined in 10 intensive care patients during continuous venovenous hemofiltration (CVVH) using a polyamide capillary hemofilter. In addition, the difficulty of calculating the hemofiltration clearance of a highly protein-bound drug is described. Flucloxacillin serum levels were significantly lowered (56.9 +/- 24.0%) even though only 15% of the drug was detected in the ultrafiltrate. Elimination half-life, total body clearance and sieving coefficient were 4.9 +/- 0.7 h, 117.2 +/- 79.1 ml/min and 0.21 +/- 0.09, respectively. These discrepancies can be explained by the high protein binding of flucloxacillin, the adsorbing property of polyamide and the equation in order to calculate hemofiltration clearance. The unbound fraction of a 4.0 g flucloxacillin dosage facilitates time above the minimum inhibitory concentration (T > MIC) of 60% only for strains up to a minimum inhibitory concentration (MIC) of 0.5 mg/l. Based on the data of this study, we conclude that intensive care patients with staphylococcal infections on CVVH should be treated with 4.0 g flucloxacillin every 8 h which was safe and well tolerated. Moreover, further studies with highly protein-bound drugs are recommended to check the classical 'hemodialysis' equation as the standard equation in calculating the CVVH clearance of highly protein-bound drugs. Copyright 2003 S. Karger AG, Basel

Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

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Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

2013-07-01

In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

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Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

The periplasmic protein TolB as a potential drug target in Pseudomonas aeruginosa.

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Alessandra Lo Sciuto

Full Text Available The Gram-negative bacterium Pseudomonas aeruginosa is one of the most dreaded pathogens in the hospital setting, and represents a prototype of multi-drug resistant "superbug" for which effective therapeutic options are very limited. The identification and characterization of new cellular functions that are essential for P. aeruginosa viability and/or virulence could drive the development of anti-Pseudomonas compounds with novel mechanisms of action. In this study we investigated whether TolB, the periplasmic component of the Tol-Pal trans-envelope protein complex of Gram-negative bacteria, represents a potential drug target in P. aeruginosa. By combining conditional mutagenesis with the analysis of specific pathogenicity-related phenotypes, we demonstrated that TolB is essential for P. aeruginosa growth, both in laboratory and clinical strains, and that TolB-depleted P. aeruginosa cells are strongly defective in cell-envelope integrity, resistance to human serum and several antibiotics, as well as in the ability to cause infection and persist in an insect model of P. aeruginosa infection. The essentiality of TolB for P. aeruginosa growth, resistance and pathogenicity highlights the potential of TolB as a novel molecular target for anti-P. aeruginosa drug discovery.

Ribonucleotide reductase as a drug target against drug resistance Mycobacterium leprae: A molecular docking study.

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Mohanty, Partha Sarathi; Bansal, Avi Kumar; Naaz, Farah; Gupta, Umesh Datta; Dwivedi, Vivek Dhar; Yadava, Umesh

2018-06-01

Leprosy is a chronic infection of skin and nerve caused by Mycobacterium leprae. The treatment is based on standard multi drug therapy consisting of dapsone, rifampicin and clofazamine. The use of rifampicin alone or with dapsone led to the emergence of rifampicin-resistant Mycobacterium leprae strains. The emergence of drug-resistant leprosy put a hurdle in the leprosy eradication programme. The present study aimed to predict the molecular model of ribonucleotide reductase (RNR), the enzyme responsible for biosynthesis of nucleotides, to screen new drugs for treatment of drug-resistant leprosy. The study was conducted by retrieving RNR of M. leprae from GenBank. A molecular 3D model of M. leprae was predicted using homology modelling and validated. A total of 325 characters were included in the analysis. The predicted 3D model of RNR showed that the ϕ and φ angles of 251 (96.9%) residues were positioned in the most favoured regions. It was also conferred that 18 α-helices, 6 β turns, 2 γ turns and 48 helix-helix interactions contributed to the predicted 3D structure. Virtual screening of Food and Drug Administration approved drug molecules recovered 1829 drugs of which three molecules, viz., lincomycin, novobiocin and telithromycin, were taken for the docking study. It was observed that the selected drug molecules had a strong affinity towards the modelled protein RNR. This was evident from the binding energy of the drug molecules towards the modelled protein RNR (-6.10, -6.25 and -7.10). Three FDA-approved drugs, viz., lincomycin, novobiocin and telithromycin, could be taken for further clinical studies to find their efficacy against drug resistant leprosy. Copyright © 2018 Elsevier B.V. All rights reserved.

Protein redox chemistry: post-translational cysteine modifications that regulate signal transduction and drug pharmacology

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Revati eWani

2014-10-01

Full Text Available The perception of reactive oxygen species (ROS has evolved over the past decade from agents of cellular damage to secondary messengers which modify signaling proteins in physiology and the disease state (e.g. cancer. New protein targets of specific oxidation are rapidly being identified. One emerging class of redox modification occurs to the thiol side chain of cysteine residues which can produce multiple chemically-distinct alterations to the protein (e.g. sulfenic/sulfinic/sulfonic acid, disulfides. These post-translational modifications (PTM are shown to affect the protein structure and function. Because redox-sensitive proteins can traffic between subcellular compartments that have different redox environments, cysteine oxidation enables a spatio-temporal control to signaling. Understanding ramifications of these oxidative modifications to the functions of signaling proteins is crucial for understanding cellular regulation as well as for informed-drug discovery process. The effects of EGFR oxidation of Cys797 on inhibitor pharmacology are presented to illustrate the principle. Taken together, cysteine redox PTM can impact both cell biology and drug pharmacology.

Altered drug binding to serum proteins in pregnant women: therapeutic relevance.

OpenAIRE

Perucca, E; Ruprah, M; Richens, A

1981-01-01

The binding of diazepam, phenytoin and valproic acid to serum proteins in vitro has been compared in pregnant women of different gestational ages and in controls. The unbound fraction of each of three drugs was elevated during pregnancy (particularly during the last 8 weeks) probably due, at least in part, to a fall in serum albumin concentration. These findings may provide a partial explanation for the increase in the clearance of certain drugs during pregnancy and need to be taken into acco...

Spread of anti-malarial drug resistance: Mathematical model with implications for ACT drug policies

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Dondorp Arjen M

2008-11-01

Full Text Available Abstract Background Most malaria-endemic countries are implementing a change in anti-malarial drug policy to artemisinin-based combination therapy (ACT. The impact of different drug choices and implementation strategies is uncertain. Data from many epidemiological studies in different levels of malaria endemicity and in areas with the highest prevalence of drug resistance like borders of Thailand are certainly valuable. Formulating an appropriate dynamic data-driven model is a powerful predictive tool for exploring the impact of these strategies quantitatively. Methods A comprehensive model was constructed incorporating important epidemiological and biological factors of human, mosquito, parasite and treatment. The iterative process of developing the model, identifying data needed, and parameterization has been taken to strongly link the model to the empirical evidence. The model provides quantitative measures of outcomes, such as malaria prevalence/incidence and treatment failure, and illustrates the spread of resistance in low and high transmission settings. The model was used to evaluate different anti-malarial policy options focusing on ACT deployment. Results The model predicts robustly that in low transmission settings drug resistance spreads faster than in high transmission settings, and treatment failure is the main force driving the spread of drug resistance. In low transmission settings, ACT slows the spread of drug resistance to a partner drug, especially at high coverage rates. This effect decreases exponentially with increasing delay in deploying the ACT and decreasing rates of coverage. In the high transmission settings, however, drug resistance is driven by the proportion of the human population with a residual drug level, which gives resistant parasites some survival advantage. The spread of drug resistance could be slowed down by controlling presumptive drug use and avoiding the use of combination therapies containing drugs with

Site-selective protein-modification chemistry for basic biology and drug development.

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Krall, Nikolaus; da Cruz, Filipa P; Boutureira, Omar; Bernardes, Gonçalo J L

2016-02-01

Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

Science.gov (United States)

Saini, Harsh; Raicar, Gaurav; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

2015-12-07

Protein subcellular localization is an important topic in proteomics since it is related to a protein׳s overall function, helps in the understanding of metabolic pathways, and in drug design and discovery. In this paper, a basic approximation technique from natural language processing called the linear interpolation smoothing model is applied for predicting protein subcellular localizations. The proposed approach extracts features from syntactical information in protein sequences to build probabilistic profiles using dependency models, which are used in linear interpolation to determine how likely is a sequence to belong to a particular subcellular location. This technique builds a statistical model based on maximum likelihood. It is able to deal effectively with high dimensionality that hinders other traditional classifiers such as Support Vector Machines or k-Nearest Neighbours without sacrificing performance. This approach has been evaluated by predicting subcellular localizations of Gram positive and Gram negative bacterial proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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Donglu Zhang

2012-12-01

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

Protein Kinases C-Mediated Regulations of Drug Transporter Activity, Localization and Expression

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Abdullah Mayati

2017-04-01

Full Text Available Drug transporters are now recognized as major actors in pharmacokinetics, involved notably in drug–drug interactions and drug adverse effects. Factors that govern their activity, localization and expression are therefore important to consider. In the present review, the implications of protein kinases C (PKCs in transporter regulations are summarized and discussed. Both solute carrier (SLC and ATP-binding cassette (ABC drug transporters can be regulated by PKCs-related signaling pathways. PKCs thus target activity, membrane localization and/or expression level of major influx and efflux drug transporters, in various normal and pathological types of cells and tissues, often in a PKC isoform-specific manner. PKCs are notably implicated in membrane insertion of bile acid transporters in liver and, in this way, are thought to contribute to cholestatic or choleretic effects of endogenous compounds or drugs. The exact clinical relevance of PKCs-related regulation of drug transporters in terms of drug resistance, pharmacokinetics, drug–drug interactions and drug toxicity remains however to be precisely determined. This issue is likely important to consider in the context of the development of new drugs targeting PKCs-mediated signaling pathways, for treating notably cancers, diabetes or psychiatric disorders.

Drug-like density: a method of quantifying the "bindability" of a protein target based on a very large set of pockets and drug-like ligands from the Protein Data Bank.

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Sheridan, Robert P; Maiorov, Vladimir N; Holloway, M Katharine; Cornell, Wendy D; Gao, Ying-Duo

2010-11-22

One approach to estimating the "chemical tractability" of a candidate protein target where we know the atomic resolution structure is to examine the physical properties of potential binding sites. A number of other workers have addressed this issue. We characterize ~290,000 "pockets" from ~42,000 protein crystal structures in terms of a three parameter "pocket space": volume, buriedness, and hydrophobicity. A metric DLID (drug-like density) measures how likely a pocket is to bind a drug-like molecule. This is calculated from the count of other pockets in its local neighborhood in pocket space that contain drug-like cocrystallized ligands and the count of total pockets in the neighborhood. Surprisingly, despite being defined locally, a global trend in DLID can be predicted by a simple linear regression on log(volume), buriedness, and hydrophobicity. Two levels of simplification are necessary to relate the DLID of individual pockets to "targets": taking the best DLID per Protein Data Bank (PDB) entry (because any given crystal structure can have many pockets), and taking the median DLID over all PDB entries for the same target (because different crystal structures of the same protein can vary because of artifacts and real conformational changes). We can show that median DLIDs for targets that are detectably homologous in sequence are reasonably similar and that median DLIDs correlate with the "druggability" estimate of Cheng et al. (Nature Biotechnology 2007, 25, 71-75).

Entrapment of alpha1-acid glycoprotein in high-performance affinity columns for drug-protein binding studies.

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Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S

2016-05-15

A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (±0.5)×10(5)M(-1), which agreed with a previously reported value of 1.0 (±0.1)×10(5)M(-1). Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of a combined drug-delivery system for proteins assembled with polymeric nanoparticles and porous microspheres; characterization and protein integrity studies.

Science.gov (United States)

Alcalá-Alcalá, Sergio; Benítez-Cardoza, Claudia G; Lima-Muñoz, Enrique J; Piñón-Segundo, Elizabeth; Quintanar-Guerrero, David

2015-07-15

This work presents an evaluation of the adsorption/infiltration process in relation to the loading of a model protein, α-amylase, into an assembled biodegradable polymeric system, free of organic solvents and made up of poly(D,L-lactide-co-glycolide) acid (PLGA). Systems were assembled in a friendly aqueous medium by adsorbing and infiltrating polymeric nanoparticles into porous microspheres. These assembled systems are able to load therapeutic amounts of the drug through adsorption of the protein onto the large surface area characteristic of polymeric nanoparticles. The subsequent infiltration of nanoparticles adsorbed with the protein into porous microspheres enabled the controlled release of the protein as a function of the amount of infiltrated nanoparticles, since the surface area available on the porous structure is saturated at different levels, thus modifying the protein release rate. Findings were confirmed by both the BET technique (N2 isotherms) and in vitro release studies. During the adsorption process, the pH of the medium plays an important role by creating an environment that favors adsorption between the surfaces of the micro- and nano-structures and the protein. Finally, assays of α-amylase activity using 2-chloro-4-nitrophenyl-α-D-maltotrioside (CNP-G3) as the substrate and the circular dichroism technique confirmed that when this new approach was used no conformational changes were observed in the protein after release. Copyright © 2015 Elsevier B.V. All rights reserved.

Water-based preparation of spider silk films as drug delivery matrices.

Science.gov (United States)

Agostini, Elisa; Winter, Gerhard; Engert, Julia

2015-09-10

The main focus of this work was to obtain a drug delivery matrix characterized by biocompatibility, water insolubility and good mechanical properties. Moreover the preparation process has to be compatible with protein encapsulation and the obtained matrix should be able to sustain release a model protein. Spider silk proteins represent exceptional natural polymers due to their mechanical properties in combination with biocompatibility. As both hydrophobic and slowly biodegrading biopolymers, recombinant spider silk proteins fulfill the required properties for a drug delivery system. In this work, we present the preparation of eADF4(C16) films as drug delivery matrices without the use of any organic solvent. Water-based spider silk films were characterized in terms of protein secondary structure, thermal stability, zeta-potential, solubility, mechanical properties, and water absorption and desorption. Additionally, this study includes an evaluation of their application as a drug delivery system for both small molecular weight drugs and high molecular weight molecules such as proteins. Our investigation focused on possible improvements in the film's mechanical properties including plasticizers in the film matrix. Furthermore, different film designs were prepared, such as: monolayer, coated monolayer, multilayer (sandwich), and coated multilayer. The release of the model protein BSA from these new systems was studied. Results indicated that spider silk films are a promising protein drug delivery matrix, capable of releasing the model protein over 90 days with a release profile close to zero order kinetic. Such films could be used for several pharmaceutical and medical purposes, especially when mechanical strength of a drug eluting matrix is of high importance. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of Radiation and Dietary Iron on Expression of Genes and Proteins Involved in Drug Metabolism

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Faust, K. M.; Wotring, V. E.

2014-01-01

Liver function, especially the rate of metabolic enzyme activities, determines the concentration of circulating drugs and the duration of their efficacy. Most pharmaceuticals are metabolized by the liver, and clinically-used medication doses are given with normal liver function in mind. A drug overdose can result in the case of a liver that is damaged and removing pharmaceuticals from the circulation at a rate slower than normal. Alternatively, if liver function is elevated and removing drugs from the system more quickly than usual, it would be as if too little drug had been given for effective treatment. Because of the importance of the liver in drug metabolism, we want to understand any effects of spaceflight on the enzymes of the liver. Dietary factors and exposure to radiation are aspects of spaceflight that are potential oxidative stressors and both can be modeled in ground experiments. In this experiment, we examined the effects of high dietary iron and low dose gamma radiation (individually and combined) on the gene expression of enzymes involved in drug metabolism, redox homeostasis, and DNA repair. METHODS All procedures were approved by the JSC Animal Care and Use Committee. Male Sprague-Dawley rats were divided into 4 groups (n=8); control, high Fe diet (650 mg iron/kg), radiation (fractionated 3 Gy exposure from a Cs- 137 source) and combined high Fe diet + radiation exposure. Animals were euthanized 24h after the last treatment of radiation; livers were removed immediately and flash -frozen in liquid nitrogen. Expression of genes thought to be involved in redox homeostasis, drug metabolism and DNA damage repair was measured by RT-qPCR. Where possible, protein expression of the same genes was measured by western blotting. All data are expressed as % change in expression normalized to reference gene expression; comparisons were then made of each treatment group to the sham exposed/ normal diet control group. Data was considered significant at phigh Fe

The PMDB Protein Model Database

Science.gov (United States)

Castrignanò, Tiziana; De Meo, Paolo D'Onorio; Cozzetto, Domenico; Talamo, Ivano Giuseppe; Tramontano, Anna

2006-01-01

The Protein Model Database (PMDB) is a public resource aimed at storing manually built 3D models of proteins. The database is designed to provide access to models published in the scientific literature, together with validating experimental data. It is a relational database and it currently contains >74 000 models for ∼240 proteins. The system is accessible at and allows predictors to submit models along with related supporting evidence and users to download them through a simple and intuitive interface. Users can navigate in the database and retrieve models referring to the same target protein or to different regions of the same protein. Each model is assigned a unique identifier that allows interested users to directly access the data. PMID:16381873

In silico modeling to predict drug-induced phospholipidosis

International Nuclear Information System (INIS)

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G.; Sadrieh, Nakissa

2013-01-01

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL

pH-sensitive polymeric nanoparticles to improve oral bioavailability of peptide/protein drugs and poorly water-soluble drugs.

Science.gov (United States)

Wang, Xue-Qing; Zhang, Qiang

2012-10-01

pH-sensitive polymeric nanoparticles are promising for oral drug delivery, especially for peptide/protein drugs and poorly water-soluble medicines. This review describes current status of pH-sensitive polymeric nanoparticles for oral drug delivery and introduces the mechanisms of drug release from them as well as possible reasons for absorption improvement, with emphasis on our contribution to this field. pH-sensitive polymeric nanoparticles are prepared mainly with polyanions, polycations, their mixtures or cross-linked polymers. The mechanisms of drug release are the result of carriers' dissolution, swelling or both of them at specific pH. The possible reasons for improvement of oral bioavailability include the following: improve drug stability, enhance mucoadhesion, prolong resident time in GI tract, ameliorate intestinal permeability and increase saturation solubility and dissolution rate for poorly water-soluble drugs. As for the advantages of pH-sensitive nanoparticles over conventional nanoparticles, we conclude that (1) most carriers used are enteric-coating materials and their safety has been approved. (2) The rapid dissolution or swelling of carriers at specific pH results in quick drug release and high drug concentration gradient, which is helpful for absorption. (3) At the specific pH carriers dissolve or swell, and the bioadhesion of carriers to mucosa becomes high because nanoparticles turn from solid to gel, which can facilitate drug absorption. Copyright © 2012 Elsevier B.V. All rights reserved.

Dysregulation of protein degradation pathways may mediate the liver injury and phospholipidosis associated with a cationic amphiphilic antibiotic drug

International Nuclear Information System (INIS)

Mosedale, Merrie; Wu, Hong; Kurtz, C. Lisa; Schmidt, Stephen P.; Adkins, Karissa; Harrill, Alison H.

2014-01-01

A large number of antibiotics are known to cause drug-induced liver injury in the clinic; however, interpreting clinical risk is not straightforward owing to a lack of predictivity of the toxicity by standard preclinical species and a poor understanding of the mechanisms of toxicity. An example is PF-04287881, a novel ketolide antibiotic that caused elevations in liver function tests in Phase I clinical studies. In this study, a mouse diversity panel (MDP), comprised of 34 genetically diverse, inbred mouse strains, was utilized to model the toxicity observed with PF-04287881 treatment and investigate potential mechanisms that may mediate the liver response. Significant elevations in serum alanine aminotransferase (ALT) levels in PF-04287881-treated animals relative to vehicle-treated controls were observed in the majority (88%) of strains tested following a seven day exposure. The average fold elevation in ALT varied by genetic background and correlated with microscopic findings of hepatocellular hypertrophy, hepatocellular single cell necrosis, and Kupffer cell vacuolation (confirmed as phospholipidosis) in the liver. Global liver mRNA expression was evaluated in a subset of four strains to identify transcript and pathway differences that distinguish susceptible mice from resistant mice in the context of PF-04287881 treatment. The protein ubiquitination pathway was highly enriched among genes associated with PF-04287881-induced hepatocellular necrosis. Expression changes associated with PF-04287881-induced phospholipidosis included genes involved in drug transport, phospholipid metabolism, and lysosomal function. The findings suggest that perturbations in genes involved in protein degradation leading to accumulation of oxidized proteins may mediate the liver injury induced by this drug. - Highlights: • Identified susceptible and resistant mouse strains to liver injury induced by a CAD • Liver injury characterized by single cell necrosis, and phospholipidosis �

Dysregulation of protein degradation pathways may mediate the liver injury and phospholipidosis associated with a cationic amphiphilic antibiotic drug

Energy Technology Data Exchange (ETDEWEB)

Mosedale, Merrie [Hamner-University of North Carolina Institute for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709 (United States); Wu, Hong [Drug Safety Research and Development, Pfizer Global Research and Development, Groton, CT06340 (United States); Kurtz, C. Lisa [Hamner-University of North Carolina Institute for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709 (United States); Schmidt, Stephen P. [Drug Safety Research and Development, Pfizer Global Research and Development, Groton, CT06340 (United States); Adkins, Karissa, E-mail: Karissa.Adkins@pfizer.com [Drug Safety Research and Development, Pfizer Global Research and Development, Groton, CT06340 (United States); Harrill, Alison H. [Hamner-University of North Carolina Institute for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709 (United States); University of Arkansas for Medical Sciences, Little Rock, AR72205 (United States)

2014-10-01

A large number of antibiotics are known to cause drug-induced liver injury in the clinic; however, interpreting clinical risk is not straightforward owing to a lack of predictivity of the toxicity by standard preclinical species and a poor understanding of the mechanisms of toxicity. An example is PF-04287881, a novel ketolide antibiotic that caused elevations in liver function tests in Phase I clinical studies. In this study, a mouse diversity panel (MDP), comprised of 34 genetically diverse, inbred mouse strains, was utilized to model the toxicity observed with PF-04287881 treatment and investigate potential mechanisms that may mediate the liver response. Significant elevations in serum alanine aminotransferase (ALT) levels in PF-04287881-treated animals relative to vehicle-treated controls were observed in the majority (88%) of strains tested following a seven day exposure. The average fold elevation in ALT varied by genetic background and correlated with microscopic findings of hepatocellular hypertrophy, hepatocellular single cell necrosis, and Kupffer cell vacuolation (confirmed as phospholipidosis) in the liver. Global liver mRNA expression was evaluated in a subset of four strains to identify transcript and pathway differences that distinguish susceptible mice from resistant mice in the context of PF-04287881 treatment. The protein ubiquitination pathway was highly enriched among genes associated with PF-04287881-induced hepatocellular necrosis. Expression changes associated with PF-04287881-induced phospholipidosis included genes involved in drug transport, phospholipid metabolism, and lysosomal function. The findings suggest that perturbations in genes involved in protein degradation leading to accumulation of oxidized proteins may mediate the liver injury induced by this drug. - Highlights: • Identified susceptible and resistant mouse strains to liver injury induced by a CAD • Liver injury characterized by single cell necrosis, and phospholipidosis �

Peptide drugs to target G protein-coupled receptors.

Science.gov (United States)

Bellmann-Sickert, Kathrin; Beck-Sickinger, Annette G

2010-09-01

Major indications for use of peptide-based therapeutics include endocrine functions (especially diabetes mellitus and obesity), infectious diseases, and cancer. Whereas some peptide pharmaceuticals are drugs, acting as agonists or antagonists to directly treat cancer, others (including peptide diagnostics and tumour-targeting pharmaceuticals) use peptides to 'shuttle' a chemotherapeutic agent or a tracer to the tumour and allow sensitive imaging or targeted therapy. Significant progress has been made in the last few years to overcome disadvantages in peptide design such as short half-life, fast proteolytic cleavage, and low oral bioavailability. These advances include peptide PEGylation, lipidisation or multimerisation; the introduction of peptidomimetic elements into the sequences; and innovative uptake strategies such as liposomal, capsule or subcutaneous formulations. This review focuses on peptides targeting G protein-coupled receptors that are promising drug candidates or that have recently entered the pharmaceutical market. Copyright 2010 Elsevier Ltd. All rights reserved.

Packaging protein drugs as bacterial inclusion bodies for therapeutic applications

Directory of Open Access Journals (Sweden)

Villaverde Antonio

2012-06-01

Full Text Available Abstract A growing number of insights on the biology of bacterial inclusion bodies (IBs have revealed intriguing utilities of these protein particles. Since they combine mechanical stability and protein functionality, IBs have been already exploited in biocatalysis and explored for bottom-up topographical modification in tissue engineering. Being fully biocompatible and with tuneable bio-physical properties, IBs are currently emerging as agents for protein delivery into mammalian cells in protein-replacement cell therapies. So far, IBs formed by chaperones (heat shock protein 70, Hsp70, enzymes (catalase and dihydrofolate reductase, grow factors (leukemia inhibitory factor, LIF and structural proteins (the cytoskeleton keratin 14 have been shown to rescue exposed cells from a spectrum of stresses and restore cell functions in absence of cytotoxicity. The natural penetrability of IBs into mammalian cells (reaching both cytoplasm and nucleus empowers them as an unexpected platform for the controlled delivery of essentially any therapeutic polypeptide. Production of protein drugs by biopharma has been traditionally challenged by IB formation. However, a time might have arrived in which recombinant bacteria are to be engineered for the controlled packaging of therapeutic proteins as nanoparticulate materials (nanopills, for their extra- or intra-cellular release in medicine and cosmetics.

Scaffold proteins LACK and TRACK as potential drug targets in kinetoplastid parasites: Development of inhibitors

Directory of Open Access Journals (Sweden)

Nir Qvit

2016-04-01

Full Text Available Parasitic diseases cause ∼500,000 deaths annually and remain a major challenge for therapeutic development. Using a rational design based approach, we developed peptide inhibitors with anti-parasitic activity that were derived from the sequences of parasite scaffold proteins LACK (Leishmania's receptor for activated C-kinase and TRACK (Trypanosoma receptor for activated C-kinase. We hypothesized that sequences in LACK and TRACK that are conserved in the parasites, but not in the mammalian ortholog, RACK (Receptor for activated C-kinase, may be interaction sites for signaling proteins that are critical for the parasites' viability. One of these peptides exhibited leishmanicidal and trypanocidal activity in culture. Moreover, in infected mice, this peptide was also effective in reducing parasitemia and increasing survival without toxic effects. The identified peptide is a promising new anti-parasitic drug lead, as its unique features may limit toxicity and drug-resistance, thus overcoming central limitations of most anti-parasitic drugs. Keywords: Chagas disease, Leishmaniasis, Peptide, LACK, TRACK, Scaffold protein

Peptide and low molecular weight proteins based kidney targeted drug delivery systems.

Science.gov (United States)

Xu, Pengfei; Zhang, Hailiang; Dang, Ruili; Jiang, Pei

2018-05-30

Renal disease is a worldwide public health problem, and unfortunately, the therapeutic index of regular drugs is limited. Thus, it is a great need to develop effective treatment strategies. Among the reported strategies, kidney-targeted drug delivery system is a promising method to increase renal efficacy and reduce extra-renal toxicity. In recent years, working as vehicles for targeted drug delivery, low molecular weight proteins (LMWP) and peptide have received immense attention due to their many advantages, such as selective accumulation in kidney, high drug loading capability, control over routes of biodegradation, convenience in modification at the amino terminus, and good biocompatibility. In this review, we describe the current LMWP and peptide carriers for kidney targeted drug delivery systems. In addition, we discuss different linking strategies between carriers and drugs. Furthermore, we briefly outline the current status and attempt to give an outlook on the further study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Protein tethering enables rapid and label-free SERS platform for screening drugs of abuse (Conference Presentation)

Science.gov (United States)

Siddhanta, Soumik; Wróbel, Maciej S.; Barman, Ishan

2017-02-01

A quick, cost-effective method for detection of drugs of abuse in biological fluids would be of great value in healthcare, law enforcement, and home testing applications. The alarming rise in narcotics abuse has led to considerable focus on developing potent and versatile analytical tools that can address this societal problem. While laboratory testing plays a key role in the current detection of drug misuse and the evaluation of patients with drug induced intoxication, these typically require expensive reagents and trained personnel, and may take hours to complete. Thus, a significant unmet need is to engineer a facile method that can rapidly detect drugs with little sample preparation, especially the bound fraction that is typically dominant in the blood stream. Here we report an approach that combines the exquisite sensitivity of surface enhanced Raman spectroscopy (SERS) and a facile protein tethering mechanism to reliably detect four different classes of drugs, barbiturate, benzodiazepine, amphetamine and benzoylecgonine. The proposed approach harnesses the reliable and specific attachment of proteins to both drugs and nanoparticle to facilitate the enhancement of spectral markers that are sensitive to the presence of the drugs. In conjunction with chemometric tools, we have shown the ability to quantify these drugs lower than levels achievable by existing clinical immunoassays. Through molecular docking simulations, we also probe the mechanistic underpinnings of the protein tethering approach, opening the door to detection of a broad class of narcotics in biological fluids within a few minutes as well as for groundwater analysis and toxin detection.

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

Science.gov (United States)

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

Context Sensitive Modeling of Cancer Drug Sensitivity.

Directory of Open Access Journals (Sweden)

Bo-Juen Chen

Full Text Available Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression, an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should-and should not-be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features.

Modeling the modified drug release from curved shape drug delivery systems - Dome Matrix®.

Science.gov (United States)

Caccavo, D; Barba, A A; d'Amore, M; De Piano, R; Lamberti, G; Rossi, A; Colombo, P

2017-12-01

The controlled drug release from hydrogel-based drug delivery systems is a topic of large interest for research in pharmacology. The mathematical modeling of the behavior of these systems is a tool of emerging relevance, since the simulations can be of use in the design of novel systems, in particular for complex shaped tablets. In this work a model, previously developed, was applied to complex-shaped oral drug delivery systems based on hydrogels (Dome Matrix®). Furthermore, the model was successfully adopted in the description of drug release from partially accessible Dome Matrix® systems (systems with some surfaces coated). In these simulations, the erosion rate was used asa fitting parameter, and its dependence upon the surface area/volume ratio and upon the local fluid dynamics was discussed. The model parameters were determined by comparison with the drug release profile from a cylindrical tablet, then the model was successfully used for the prediction of the drug release from a Dome Matrix® system, for simple module configuration and for module assembled (void and piled) configurations. It was also demonstrated that, given the same initial S/V ratio, the drug release is independent upon the shape of the tablets but it is only influenced by the S/V evolution. The model reveals itself able to describe the observed phenomena, and thus it can be of use for the design of oral drug delivery systems, even if complex shaped. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiscale Modeling in the Clinic: Drug Design and Development

Energy Technology Data Exchange (ETDEWEB)

Clancy, Colleen E.; An, Gary; Cannon, William R.; Liu, Yaling; May, Elebeoba E.; Ortoleva, Peter; Popel, Aleksander S.; Sluka, James P.; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M.

2016-02-17

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.

Oral delivery of peptides and proteins using lipid-based drug delivery systems

DEFF Research Database (Denmark)

Li, Ping; Nielsen, Hanne Mørck; Müllertz, Anette

2012-01-01

INTRODUCTION: In order to successfully develop lipid-based drug delivery systems (DDS) for oral administration of peptides and proteins, it is important to gain an understanding of the colloid structures formed by these DDS, the mode of peptide and protein incorporation as well as the mechanism...... by which intestinal absorption of peptides and proteins is promoted. AREAS COVERED: The present paper reviews the literature on lipid-based DDS, employed for oral delivery of peptides and proteins and highlights the mechanisms by which the different lipid-based carriers are expected to overcome the two...... and proteins. EXPERT OPINION: Lipid-based DDS are safe and suitable for oral delivery of peptides and proteins. Significant progress has been made in this area with several technologies on clinical trials. However, a better understanding of the mechanism of action in vivo is needed in order to improve...

Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors

Science.gov (United States)

Villa, Stefania; Legnani, Laura; Colombo, Diego; Gelain, Arianna; Lammi, Carmen; Bongiorno, Daniele; Ilboudo, Denise P.; McGee, Kellen E.; Bosch, Jürgen; Grazioso, Giovanni

2018-03-01

The proteins involved in the autophagy (Atg) pathway have recently been considered promising targets for the development of new antimalarial drugs. In particular, inhibitors of the protein-protein interaction (PPI) between Atg3 and Atg8 of Plasmodium falciparum retarded the blood- and liver-stages of parasite growth. In this paper, we used computational techniques to design a new class of peptidomimetics mimicking the Atg3 interaction motif, which were then synthesized by click-chemistry. Surface plasmon resonance has been employed to measure the ability of these compounds to inhibit the Atg3-Atg8 reciprocal protein-protein interaction. Moreover, P. falciparum growth inhibition in red blood cell cultures was evaluated as well as the cyto-toxicity of the compounds.

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method.

Science.gov (United States)

Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

2014-08-01

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Pathophysiological changes that affect drug disposition in protein-energy malnourished children

Directory of Open Access Journals (Sweden)

Oshikoya Kazeem A

2009-12-01

Full Text Available Abstract Protein-energy malnutrition (PEM is a major public health problem affecting a high proportion of infants and older children world-wide and accounts for a high childhood morbidity and mortality in the developing countries. The epidemiology of PEM has been extensively studied globally and management guidelines formulated by the World Health Organization (WHO. A wide spectrum of infections such as measles, malaria, acute respiratory tract infection, intestinal parasitosis, tuberculosis and HIV/AIDS may complicate PEM with two or more infections co-existing. Thus, numerous drugs may be required to treat the patients. In-spite of abundant literature on the epidemiology and management of PEM, focus on metabolism and therapeutic drug monitoring is lacking. A sound knowledge of pathophysiology of PEM and pharmacology of the drugs frequently used for their treatment is required for safe and rational treatment. In this review, we discuss the pathophysiological changes in children with PEM that may affect the disposition of drugs frequently used for their treatment. This review has established abnormal disposition of drugs in children with PEM that may require dosage modification. However, the relevance of these abnormalities to the clinical management of PEM remains inconclusive. At present, there are no good indications for drug dosage modification in PEM; but for drug safety purposes, further studies are required to accurately determine dosages of drugs frequently used for children with PEM.

Structural Model of Drug Use among Students: The Role of Spirituality, Social Modeling and Attitude to Drugs

Directory of Open Access Journals (Sweden)

samira yavari

2015-06-01

Full Text Available Objective: This study was an attempt to explore the structural relationship between religious activity, religious struggle, attitude to drugs, social modeling, spiritual well-being, and cigarette and tobacco smoking among students. Method: For this purpose, 504 male and female students from Kharazmi University, Agricultural Paradise, and Azad University of Karaj were selected by cluster sampling and they were asked to complete spiritual well-being scale, religious activity scale, religious struggle scale, social modeling scale, negative beliefs about drugs, and the tobacco section of the high-risk behavior questionnaire. Results: The results showed that the effect of religious activity on cigarette and tobacco smoking was mediated by negative beliefs about drugs, social modeling, spiritual well-being, and incentives for drug use. Similarly, the effect of religious struggle on cigarette and tobacco smoking was mediated by spiritual well-being. Conclusion: It seems that religion prevents people joining the unhealthy peer groups by the establishment of moral discipline, internal and external rules, and healthy coping styles therefore, people get less attracted to cigarette and tobacco smoking. Accordingly, these factors should be paid more attention in prevention programs for drug use, particularly cigarette and tobacco that are considered as the gateway to other drugs.

Multiscale modeling of transdermal drug delivery

Science.gov (United States)

Rim, Jee Eun

2006-04-01

This study addresses the modeling of transdermal diffusion of drugs, to better understand the permeation of molecules through the skin, and especially the stratum corneum, which forms the main permeation barrier of the skin. In transdermal delivery of systemic drugs, the drugs diffuse from a patch placed on the skin through the epidermis to the underlying blood vessels. The epidermis is the outermost layer of the skin and can be further divided into the stratum corneum (SC) and the viable epidermis layers. The SC consists of keratinous cells (corneocytes) embedded in the lipid multi-bilayers of the intercellular space. It is widely accepted that the barrier properties of the skin mostly arises from the ordered structure of the lipid bilayers. The diffusion path, at least for lipophilic molecules, seems to be mainly through the lipid bilayers. Despite the advantages of transdermal drug delivery compared to other drug delivery routes such as oral dosing and injections, the low percutaneous permeability of most compounds is a major difficulty in the wide application of transdermal drug delivery. In fact, many transdermal drug formulations include one or more permeation enhancers that increase the permeation of the drug significantly. During the last two decades, many researchers have studied percutaneous absorption of drugs both experimentally and theoretically. However, many are based on pharmacokinetic compartmental models, in which steady or pseudo-steady state conditions are assumed, with constant diffusivity and partitioning for single component systems. This study presents a framework for studying the multi-component diffusion of drugs coupled with enhancers through the skin by considering the microstructure of the stratum corneum (SC). A multiscale framework of modeling the transdermal diffusion of molecules is presented, by first calculating the microscopic diffusion coefficient in the lipid bilayers of the SC using molecular dynamics (MD). Then a

Modeling structure of G protein-coupled receptors in huan genome

KAUST Repository

Zhang, Yang

2016-01-01

G protein-coupled receptors (or GPCRs) are integral transmembrane proteins responsible to various cellular signal transductions. Human GPCR proteins are encoded by 5% of human genes but account for the targets of 40% of the FDA approved drugs. Due

Erectile Dysfunction Drugs Changed the Protein Expressions and Activities of Drug-Metabolising Enzymes in the Liver of Male Rats

Directory of Open Access Journals (Sweden)

Salah A. Sheweita

2016-01-01

Full Text Available Erectile dysfunction (ED is a major health problem and is mainly associated with the persistent inability of men to maintain sufficient erection for satisfactory sexual performance. Millions of men are using sildenafil, vardenafil, and/or tadalafil for ED treatment. Cytochrome P450s (CYPs play a central role in the metabolism of a wide range of xenobiotics as well as endogenous compounds. Susceptibility of individuals to the adverse effects of different drugs is mainly dependent on the expression of CYPs proteins. Therefore, changes in activities of phase I drug-metabolising enzymes [arylhydrocarbon hydroxylase (AHH, dimethylnitrosamine N-demethylase (DMN-dI, 7-ethoxycoumarin-O-deethylase (ECOD, and ethoxyresorufin-O-deethylase ((EROD] and the protein expression of different CYPs isozymes (CYP1A2, CYP2E1, CYP2B1/2, CYP3A4, CYP2C23, and CYP2C6 were determined after treatment of male rats with either low or high doses of sildenafil (Viagra, tadalafil (Cialis, and/or vardenafil (Levitra for 3 weeks. The present study showed that low doses of tadalafil and vardenafil increased DMN-dI activity by 32 and 23%, respectively. On the other hand, high doses of tadalafil, vardenafil, and sildenafil decreased such activity by 50, 56, and 52%, respectively. In addition, low doses of tadalafil and vardenafil induced the protein expression of CYP2E1. On the other hand, high doses of either tadalafil or sildenafil were more potent inhibitors to CYP2E1 expression than vardenafil. Moreover, low doses of both vardenafil and sildenafil markedly increased AHH activity by 162 and 247%, respectively, whereas high doses of tadalafil, vardenafil, and sildenafil inhibited such activity by 36, 49, and 57% and inhibited the EROD activity by 39, 49, and 33%, respectively. Low and high doses of tadalafil, vardenafil, and sildenafil inhibited the activity of NADPH-cytochrome c reductase as well as its protein expression. In addition, such drugs inhibited the expression of CYP

Delivery of peptide and protein drugs over the blood-brain barrier.

Science.gov (United States)

Brasnjevic, Ivona; Steinbusch, Harry W M; Schmitz, Christoph; Martinez-Martinez, Pilar

2009-04-01

Peptide and protein (P/P) drugs have been identified as showing great promises for the treatment of various neurodegenerative diseases. A major challenge in this regard, however, is the delivery of P/P drugs over the blood-brain barrier (BBB). Intense research over the last 25 years has enabled a better understanding of the cellular and molecular transport mechanisms at the BBB, and several strategies for enhanced P/P drug delivery over the BBB have been developed and tested in preclinical and clinical-experimental research. Among them, technology-based approaches (comprising functionalized nanocarriers and liposomes) and pharmacological strategies (such as the use of carrier systems and chimeric peptide technology) appear to be the most promising ones. This review combines a comprehensive overview on the current understanding of the transport mechanisms at the BBB with promising selected strategies published so far that can be applied to facilitate enhanced P/P drug delivery over the BBB.

The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

Science.gov (United States)

Vilar, Santiago; Hripcsak, George

2017-07-01

Explosion of the availability of big data sources along with the development in computational methods provides a useful framework to study drugs' actions, such as interactions with pharmacological targets and off-targets. Databases related to protein interactions, adverse effects and genomic profiles are available to be used for the construction of computational models. In this article, we focus on the description of biological profiles for drugs that can be used as a system to compare similarity and create methods to predict and analyze drugs' actions. We highlight profiles constructed with different biological data, such as target-protein interactions, gene expression measurements, adverse effects and disease profiles. We focus on the discovery of new targets or pathways for drugs already in the pharmaceutical market, also called drug repurposing, in the interaction with off-targets responsible for adverse reactions and in drug-drug interaction analysis. The current and future applications, strengths and challenges facing all these methods are also discussed. Biological profiles or signatures are an important source of data generation to deeply analyze biological actions with important implications in drug-related studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Functional characterisation of Burkholderia pseudomallei biotin protein ligase: A toolkit for anti-melioidosis drug development.

Science.gov (United States)

Bond, Thomas E H; Sorenson, Alanna E; Schaeffer, Patrick M

2017-06-01

Burkholderia pseudomallei (Bp) is the causative agent of melioidosis. The bacterium is responsible for 20% of community-acquired sepsis cases and 40% of sepsis-related mortalities in northeast Thailand, and is intrinsically resistant to aminoglycosides, macrolides, rifamycins, cephalosporins, and nonureidopenicillins. There is no vaccine and its diagnosis is problematic. Biotin protein ligase (BirA) which is essential for fatty acid synthesis has been proposed as a drug target in bacteria. Very few bacterial BirA have been characterized, and a better understanding of these enzymes is necessary to further assess their value as drug targets. BirA within the Burkholderia genus have not yet been investigated. We present for the first time the cloning, expression, purification and functional characterisation of the putative Bp BirA and orthologous B. thailandensis (Bt) biotin carboxyl carrier protein (BCCP) substrate. A GFP-tagged Bp BirA was produced and applied for the development of a high-throughput (HT) assay based on our differential scanning fluorimetry of GFP-tagged proteins (DSF-GTP) principle as well as an electrophoretic mobility shift assay. Our biochemical data in combination with the new HT DSF-GTP and biotinylation activity assay could facilitate future drug screening efforts against this drug-resistant organism. Copyright © 2017 Elsevier GmbH. All rights reserved.

Interaction of S-layer proteins of Lactobacillus kefir with model membranes and cells.

Science.gov (United States)

Hollmann, Axel; Delfederico, Lucrecia; Santos, Nuno C; Disalvo, E Anibal; Semorile, Liliana

2018-06-01

In previous works, it was shown that S-layer proteins from Lactobacillus kefir were able to recrystallize and stabilize liposomes, this feature reveling a great potential for developing liposomal-based carriers. Despite previous studies on this subject are important milestones, a number of questions remain unanswered. In this context, the feasibility of S-layer proteins as a biomaterial for drug delivery was evaluated in this work. First, S-layer proteins were fully characterized by electron microscopy, 2D-electrophoresis, and anionic exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD). Afterward, interactions of S-layer proteins with model lipid membranes were evaluated, showing that proteins adsorb to the lipid surface following a non-fickean or anomalous diffusion, when positively charged lipid were employed, suggesting that electrostatic interaction is a key factor in the recrystallization process on these proteins. Finally, the interaction of S-layer coated liposomes with Caco-2 cell line was assessed: First, cytotoxicity of formulations was tested showing no cytotoxic effects in S-layer coated vesicles. Second, by flow cytometry, it was observed an increased ability to transfer cargo molecules into Caco-2 cells from S-layer coated liposomes in comparison to control ones. All data put together, supports the idea that a combination of adhesive properties of S-layer proteins concomitant with higher stability of S-layer coated liposomes represents an exciting starting point in the development of new drug carriers.

Advanced progress of microencapsulation technologies: in vivo and in vitro models for studying oral and transdermal drug deliveries.

Science.gov (United States)

Lam, P L; Gambari, R

2014-03-28

This review provides an overall discussion of microencapsulation systems for both oral and transdermal drug deliveries. Clinically, many drugs, especially proteins and peptides, are susceptible to the gastrointestinal tract and the first-pass metabolism after oral administration while some drugs exhibit low skin permeability through transdermal delivery route. Medicated microcapsules as oral and transdermal drug delivery vehicles are believed to offer an extended drug effect at a relatively low dose and provide a better patient compliance. The polymeric microcapsules can be produced by different microencapsulation methods and the drug microencapsulation technology provides the quality preservation for drug stabilization. The release of the entrapped drug is controlled and prolonged for specific usages. Some recent studies have focused on the evaluation of drug containing microcapsules on potential biological and therapeutic applications. For the oral delivery, in vivo animal models were used for evaluating possible treatment effects of drug containing microcapsules. For the transdermal drug delivery, skin delivery models were introduced to investigate the potential skin delivery of medicated microcapsules. Finally, the challenges and limitations of drug microencapsulation in real life are discussed and the commercially available drug formulations using microencapsulation technology for oral and transdermal applications are shown. Copyright © 2014 Elsevier B.V. All rights reserved.

Expression and Cellular Distribution of Major Vault Protein: A Putative Marker for Pharmacoresistance in a Rat Model for Temporal Lobe Epilepsy

NARCIS (Netherlands)

Vliet van, E.A.; Aronica, E.; Redeker, S.; Gorter, J.A.

2004-01-01

Summary: Purpose: Because drug transporters might play a role in the development of multidrug resistance (MDR), we investigated the expression of a vesicular drug transporter, the major vault protein (MVP), in a rat model for temporal lobe epilepsy. Methods: By using real-time polymerase chain

Matricellular proteins in drug delivery: Therapeutic targets, active agents, and therapeutic localization.

Science.gov (United States)

Sawyer, Andrew J; Kyriakides, Themis R

2016-02-01

Extracellular matrix is composed of a complex array of molecules that together provide structural and functional support to cells. These properties are mainly mediated by the activity of collagenous and elastic fibers, proteoglycans, and proteins such as fibronectin and laminin. ECM composition is tissue-specific and could include matricellular proteins whose primary role is to modulate cell-matrix interactions. In adults, matricellular proteins are primarily expressed during injury, inflammation and disease. Particularly, they are closely associated with the progression and prognosis of cardiovascular and fibrotic diseases, and cancer. This review aims to provide an overview of the potential use of matricellular proteins in drug delivery including the generation of therapeutic agents based on the properties and structures of these proteins as well as their utility as biomarkers for specific diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Drug-loaded electrospun mats of poly(vinyl alcohol) fibres and their release characteristics of four model drugs

Science.gov (United States)

Taepaiboon, Pattama; Rungsardthong, Uracha; Supaphol, Pitt

2006-05-01

Mats of PVA nanofibres were successfully prepared by the electrospinning process and were developed as carriers of drugs for a transdermal drug delivery system. Four types of non-steroidal anti-inflammatory drug with varying water solubility property, i.e. sodium salicylate (freely soluble in water), diclofenac sodium (sparingly soluble in water), naproxen (NAP), and indomethacin (IND) (both insoluble in water), were selected as model drugs. The morphological appearance of the drug-loaded electrospun PVA mats depended on the nature of the model drugs. The 1H-nuclear magnetic resonance results confirmed that the electrospinning process did not affect the chemical integrity of the drugs. Thermal properties of the drug-loaded electrospun PVA mats were analysed by differential scanning calorimetry and thermogravimetric analysis. The molecular weight of the model drugs played a major role on both the rate and the total amount of drugs released from the as-prepared drug-loaded electrospun PVA mats, with the rate and the total amount of the drugs released decreasing with increasing molecular weight of the drugs. Lastly, the drug-loaded electrospun PVA mats exhibited much better release characteristics of the model drugs than drug-loaded as-cast films.

Toxicological relationships between proteins obtained from protein target predictions of large toxicity databases

International Nuclear Information System (INIS)

Nigsch, Florian; Mitchell, John B.O.

2008-01-01

The combination of models for protein target prediction with large databases containing toxicological information for individual molecules allows the derivation of 'toxiclogical' profiles, i.e., to what extent are molecules of known toxicity predicted to interact with a set of protein targets. To predict protein targets of drug-like and toxic molecules, we built a computational multiclass model using the Winnow algorithm based on a dataset of protein targets derived from the MDL Drug Data Report. A 15-fold Monte Carlo cross-validation using 50% of each class for training, and the remaining 50% for testing, provided an assessment of the accuracy of that model. We retained the 3 top-ranking predictions and found that in 82% of all cases the correct target was predicted within these three predictions. The first prediction was the correct one in almost 70% of cases. A model built on the whole protein target dataset was then used to predict the protein targets for 150 000 molecules from the MDL Toxicity Database. We analysed the frequency of the predictions across the panel of protein targets for experimentally determined toxicity classes of all molecules. This allowed us to identify clusters of proteins related by their toxicological profiles, as well as toxicities that are related. Literature-based evidence is provided for some specific clusters to show the relevance of the relationships identified

Protein corona: a new approach for nanomedicine design

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Nguyen VH

2017-04-01

Full Text Available Van Hong Nguyen, Beom-Jin Lee Department of Pharmacy, Bioavailability Control Laboratory, College of Pharmacy, Ajou University, Suwon, Republic of Korea Abstract: After administration of nanoparticle (NP into biological fluids, an NP–protein complex is formed, which represents the “true identity” of NP in our body. Hence, protein–NP interaction should be carefully investigated to predict and control the fate of NPs or drug-loaded NPs, including systemic circulation, biodistribution, and bioavailability. In this review, we mainly focus on the formation of protein corona and its potential applications in pharmaceutical sciences such as prediction modeling based on NP-adsorbed proteins, usage of active proteins for modifying NP to achieve toxicity reduction, circulation time enhancement, and targeting effect. Validated correlative models for NP biological responses mainly based on protein corona fingerprints of NPs are more highly accurate than the models solely set up from NP properties. Based on these models, effectiveness as well as the toxicity of NPs can be predicted without in vivo tests, while novel cell receptors could be identified from prominent proteins which play important key roles in the models. The ungoverned protein adsorption onto NPs may have generally negative effects such as rapid clearance from the bloodstream, hindrance of targeting capacity, and induction of toxicity. In contrast, controlling protein adsorption by modifying NPs with diverse functional proteins or tailoring appropriate NPs which favor selective endogenous peptides and proteins will bring promising therapeutic benefits in drug delivery and targeted cancer treatment. Keywords: protein-nanoparticle interaction, protein corona, exchange of adsorbed protein, toxicity reduction, predictive modeling, targeting drug delivery

Fungal lectin MpL enables entry of protein drugs into cancer cells and their subcellular targeting.

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Å Urga, Simon; Nanut, Milica Perišić; Kos, Janko; Sabotič, Jerica

2017-04-18

Lectins have been recognized as promising carrier molecules for targeted drug delivery. They specifically bind carbohydrate moieties on cell membranes and trigger cell internalization. Fungal lectin MpL (Macrolepiota procera lectin) does not provoke cancer cell cytotoxicity but is able to bind aminopeptidase N (CD13) and integrin α3β1, two glycoproteins that are overexpressed on the membrane of tumor cells. Upon binding, MpL is endocytosed in a clathrin-dependent manner and accumulates initially in the Golgi apparatus and, finally, in the lysosomes. For effective binding and internalization a functional binding site on the α-repeat is needed. To test the potential of MpL as a carrier for delivering protein drugs to cancer cells we constructed fusion proteins consisting of MpL and the cysteine peptidase inhibitors cystatin C and clitocypin. The fused proteins followed the same endocytic route as the unlinked MpL. Peptidase inhibitor-MpL fusions impaired both the intracellular degradation of extracellular matrix and the invasiveness of cancer cells. MpL is thus shown in vitro to be a lectin that can enable protein drugs to enter cancer cells, enhance their internalization and sort them to lysosomes and the Golgi apparatus.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

DEFF Research Database (Denmark)

Nguyen, E.D.; Meiler, J.; Norn, C.

2013-01-01

screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone...... extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves...

Development and evaluation of mucoadhesive nanoparticles based on thiolated Eudragit for oral delivery of protein drugs

Science.gov (United States)

Zhang, Yan; Yang, Zhijie; Hu, Xi; Zhang, Ling; Li, Feng; Li, Meimei; Tang, Xing; Xiao, Wei

2015-02-01

The objective of this study was to develop pH-sensitive Eudragit L100-cysteine/reduced glutathione (Eul-cys/GSH) nanoparticles (NPs), which provided the mucoadhesion and protection for protein drugs against enzymatic degradation. Insulin was chosen as a model biomolecule for testing this system. The Eul-cys conjugate, which was obtained by grafting cysteine onto the carboxy group of Eudragit L100, was analyzed by HNMR and SEM, and the swelling degree (SD), cation binding, and enzymatic inhibition were also determined. The results obtained showed that the Eul-cys conjugate represent a pH-sensitive delivery system which effectively protected the insulin from being degraded by the proteases, and this is related to the mechanism of Ca2+ binding. Insulin-loaded Eul-cys/GSH NPs were prepared by a diffusion method involving an electrostatic interaction between the network structure of the polymer and the embedded proteins, including insulin and GSH. TEM images indicated that Eul-cys/GSH existed as smooth and spherical NPs in aqueous solution with particle sizes of 260 ± 20 nm. The X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) findings showed the presence of amorphous insulin in thiolated NPs and higher free thiol oxidation than the result obtained by Ellman's reagent method. In addition, thiolated NPs showed excellent binding efficiency to the mucin in rat intestine, indicating that Eul-cys/GSH NPs have great potential to be applied as safe carriers for the oral administration of protein drugs.

Protein microarray: sensitive and effective immunodetection for drug residues

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Zer Cindy

2010-02-01

Full Text Available Abstract Background Veterinary drugs such as clenbuterol (CL and sulfamethazine (SM2 are low molecular weight ( Results The artificial antigens were spotted on microarray slides. Standard concentrations of the compounds were added to compete with the spotted antigens for binding to the antisera to determine the IC50. Our microarray assay showed the IC50 were 39.6 ng/ml for CL and 48.8 ng/ml for SM2, while the traditional competitive indirect-ELISA (ci-ELISA showed the IC50 were 190.7 ng/ml for CL and 156.7 ng/ml for SM2. We further validated the two methods with CL fortified chicken muscle tissues, and the protein microarray assay showed 90% recovery while the ci-ELISA had 76% recovery rate. When tested with CL-fed chicken muscle tissues, the protein microarray assay had higher sensitivity (0.9 ng/g than the ci-ELISA (0.1 ng/g for detection of CL residues. Conclusions The protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique.

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....

Drug-protein interactions assessed by fluorescence measurements in the real complexes and in model dyads

Science.gov (United States)

Vayá, Ignacio; Pérez-Ruiz, Raúl; Lhiaubet-Vallet, Virginie; Jiménez, M. Consuelo; Miranda, Miguel A.

2010-02-01

In the present work, a systematic fluorescence study on supramolecular systems using two serum albumins (HSA or BSA) as hosts and the nonsteroidal antiinflammatory drugs carprofen (CPF) or naproxen (NPX) as guests has been undertaken. In parallel, model dyads containing Tyr or Trp covalently linked to CPF or NPX have also been investigated. In HSA/(S)-CPF and BSA/(S)-CPF ( λexc = 266 nm), at 1:1 M ratio, an important degree (more than 40%) of singlet-singlet energy transfer (SSET) was observed to take place. The distance ( r) calculated for energy transfer from the SAs to (S)-CPF through a FRET mechanism was found to be ca. 21 Å. In the case of HSA/(S)-NPX and BSA/(S)-NPX, energy transfer occurred to a lower extent (ca. 7%), and r was determined as ca. 24 Å. In order to investigate the possible excited state interactions between bound ligands and the relevant amino acids present in the protein binding sites, four pairs of model dyads were designed and synthesised, namely ( S, S)-TyrCPF, ( S, R)-TyrCPF, ( S, S)-TrpCPF, ( S, R)-TrpCPF, ( S, S)-TyrNPX, ( S, R)-TyrNPX, ( S, S)-TrpNPX and ( S, R)-TrpNPX. A complete SSET was observed from Tyr or Trp to CPF, since no contribution from the amino acids was present in the emission of the dyads. Likewise, a very efficient Tyr or Trp to NPX energy transfer was observed. Remarkably, in ( S, S)-TrpNPX and ( S, R)-TrpNPX a configuration-dependent reduction in the emission intensity was observed, revealing a strong and stereoselective intramolecular quenching. This effect can be attributed to exciplex formation and is dynamic in nature, as the fluorescence lifetimes were much shorter in ( S, R)- and ( S, S)-TrpNPX (1.5 and 3.1 ns, respectively) than in (S)-NPX (11 ns).

Target-mediated drug disposition model and its approximations for antibody-drug conjugates.

Science.gov (United States)

Gibiansky, Leonid; Gibiansky, Ekaterina

2014-02-01

Antibody-drug conjugate (ADC) is a complex structure composed of an antibody linked to several molecules of a biologically active cytotoxic drug. The number of ADC compounds in clinical development now exceeds 30, with two of them already on the market. However, there is no rigorous mechanistic model that describes pharmacokinetic (PK) properties of these compounds. PK modeling of ADCs is even more complicated than that of other biologics as the model should describe distribution, binding, and elimination of antibodies with different toxin load, and also the deconjugation process and PK of the released toxin. This work extends the target-mediated drug disposition (TMDD) model to describe ADCs, derives the rapid binding (quasi-equilibrium), quasi-steady-state, and Michaelis-Menten approximations of the TMDD model as applied to ADCs, derives the TMDD model and its approximations for ADCs with load-independent properties, and discusses further simplifications of the system under various assumptions. The developed models are shown to describe data simulated from the available clinical population PK models of trastuzumab emtansine (T-DM1), one of the two currently approved ADCs. Identifiability of model parameters is also discussed and illustrated on the simulated T-DM1 examples.

Expression and cellular distribution of major vault protein: a putative marker for pharmacoresistance in a rat model for temporal lobe epilepsy

NARCIS (Netherlands)

van Vliet, Erwin A.; Aronica, Eleonora; Redeker, Sandra; Gorter, Jan A.

2004-01-01

PURPOSE: Because drug transporters might play a role in the development of multidrug resistance (MDR), we investigated the expression of a vesicular drug transporter, the major vault protein (MVP), in a rat model for temporal lobe epilepsy. METHODS: By using real-time polymerase chain reaction (PCR)

Understanding the determinants of selectivity in drug metabolism through modeling of dextromethorphan oxidation by cytochrome P450

Science.gov (United States)

Oláh, Julianna; Mulholland, Adrian J.; Harvey, Jeremy N.

2011-01-01

Cytochrome P450 enzymes play key roles in the metabolism of the majority of drugs. Improved models for prediction of likely metabolites will contribute to drug development. In this work, two possible metabolic routes (aromatic carbon oxidation and O-demethylation) of dextromethorphan are compared using molecular dynamics (MD) simulations and density functional theory (DFT). The DFT results on a small active site model suggest that both reactions might occur competitively. Docking and MD studies of dextromethorphan in the active site of P450 2D6 show that the dextromethorphan is located close to heme oxygen in a geometry apparently consistent with competitive metabolism. In contrast, calculations of the reaction path in a large protein model [using a hybrid quantum mechanical–molecular mechanics (QM/MM) method] show a very strong preference for O-demethylation, in accordance with experimental results. The aromatic carbon oxidation reaction is predicted to have a high activation energy, due to the active site preventing formation of a favorable transition-state structure. Hence, the QM/MM calculations demonstrate a crucial role of many active site residues in determining reactivity of dextromethorphan in P450 2D6. Beyond substrate binding orientation and reactivity of Compound I, successful metabolite predictions must take into account the detailed mechanism of oxidation in the protein. These results demonstrate the potential of QM/MM methods to investigate specificity in drug metabolism. PMID:21444768

Modelling drug flux through microporated skin.

Science.gov (United States)

Rzhevskiy, Alexey S; Guy, Richard H; Anissimov, Yuri G

2016-11-10

A simple mathematical equation has been developed to predict drug flux through microporated skin. The theoretical model is based on an approach applied previously to water evaporation through leaf stomata. Pore density, pore radius and drug molecular weight are key model parameters. The predictions of the model were compared with results derived from a simple, intuitive method using porated area alone to estimate the flux enhancement. It is shown that the new approach predicts significantly higher fluxes than the intuitive analysis, with transport being proportional to the total pore perimeter rather than area as intuitively anticipated. Predicted fluxes were in good general agreement with experimental data on drug delivery from the literature, and were quantitatively closer to the measured values than those derived from the intuitive, area-based approach. Copyright © 2016 Elsevier B.V. All rights reserved.

Application of CYP102A1M11H as a tool for the generation of protein adducts of reactive drug metabolites

NARCIS (Netherlands)

Boerma, J.S.; Vermeulen, N.P.E.; Commandeur, J.N.M.

2011-01-01

Covalent binding of reactive metabolites (RMs) to proteins is considered to be one of the important mechanisms by which drugs can cause tissue damage. To facilitate the study of drug-protein adducts, we developed a potentially generic method for producing high levels of covalently modified proteins.

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.

Protein-protein interactions as a strategy towards protein-specific drug design: the example of ataxin-1.

Directory of Open Access Journals (Sweden)

Cesira de Chiara

Full Text Available A main challenge for structural biologists is to understand the mechanisms that discriminate between molecular interactions and determine function. Here, we show how partner recognition of the AXH domain of the transcriptional co-regulator ataxin-1 is fine-tuned by a subtle balance between self- and hetero-associations. Ataxin-1 is the protein responsible for the hereditary spinocerebellar ataxia type 1, a disease linked to protein aggregation and transcriptional dysregulation. Expansion of a polyglutamine tract is essential for ataxin-1 aggregation, but the sequence-wise distant AXH domain plays an important aggravating role in the process. The AXH domain is also a key element for non-aberrant function as it intervenes in interactions with multiple protein partners. Previous data have shown that AXH is dimeric in solution and forms a dimer of dimers when crystallized. By solving the structure of a complex of AXH with a peptide from the interacting transcriptional repressor CIC, we show that the dimer interface of AXH is displaced by the new interaction and that, when blocked by the CIC peptide AXH aggregation and misfolding are impaired. This is a unique example in which palindromic self- and hetero-interactions within a sequence with chameleon properties discriminate the partner. We propose a drug design strategy for the treatment of SCA1 that is based on the information gained from the AXH/CIC complex.

Disrupting self-assembly and toxicity of amyloidogenic protein oligomers by "molecular tweezers" - from the test tube to animal models.

Science.gov (United States)

Attar, Aida; Bitan, Gal

2014-01-01

Despite decades of research, therapy for diseases caused by abnormal protein folding and aggregation (amyloidoses) is limited to treatment of symptoms and provides only temporary and moderate relief to sufferers. The failure in developing successful disease-modifying drugs for amyloidoses stems from the nature of the targets for such drugs - primarily oligomers of amyloidogenic proteins, which are distinct from traditional targets, such as enzymes or receptors. The oligomers are metastable, do not have well-defined structures, and exist in dynamically changing mixtures. Therefore, inhibiting the formation and toxicity of these oligomers likely will require out-of-the-box thinking and novel strategies. We review here the development of a strategy based on targeting the combination of hydrophobic and electrostatic interactions that are key to the assembly and toxicity of amyloidogenic proteins using lysine (K)-specific "molecular tweezers" (MTs). Our discussion includes a survey of the literature demonstrating the important role of K residues in the assembly and toxicity of amyloidogenic proteins and the development of a lead MT derivative called CLR01, from an inhibitor of protein aggregation in vitro to a drug candidate showing effective amelioration of disease symptoms in animal models of Alzheimer's and Parkinson's diseases.

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

Science.gov (United States)

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

2017-08-24

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

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.

A Network-Based Model of Oncogenic Collaboration for Prediction of Drug Sensitivity

Directory of Open Access Journals (Sweden)

Ted G Laderas

2015-12-01

Full Text Available Tumorigenesis is a multi-step process, involving the acquisition of multiple oncogenic mutations that transform cells, resulting in systemic dysregulation that enables proliferation, among other cancer hallmarks. High throughput omics techniques are used in precision medicine, allowing identification of these mutations with the goal of identifying treatments that target them. However, the multiplicity of oncogenes required for transformation, known as oncogenic collaboration, makes assigning effective treatments difficult. Motivated by this observation, we propose a new type of oncogenic collaboration where mutations in genes that interact with an oncogene may contribute to its dysregulation, a new genomic feature that we term surrogate oncogenes. By mapping mutations to a protein/protein interaction network, we can determine significance of the observed distribution using permutation-based methods. For a panel of 38 breast cancer cell lines, we identified significant surrogate oncogenes in oncogenes such as BRCA1 and ESR1. In addition, using Random Forest Classifiers, we show that these significant surrogate oncogenes predict drug sensitivity for 74 drugs in the breast cancer cell lines with a mean error rate of 30.9%. Additionally, we show that surrogate oncogenes are predictive of survival in patients. The surrogate oncogene framework incorporates unique or rare mutations on an individual level. Our model has the potential for integrating patient-unique mutations in predicting drug-sensitivity, suggesting a potential new direction in precision medicine, as well as a new approach for drug development. Additionally, we show the prevalence of significant surrogate oncogenes in multiple cancers within the Cancer Genome Atlas, suggesting that surrogate oncogenes may be a useful genomic feature for guiding pancancer analyses and assigning therapies across many tissue types.

vPARP Adjusts MVP Expression in Drug-resistant Cell Lines in Conjunction with MDR Proteins.

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Wojtowicz, Karolina; Januchowski, Radoslaw; Nowicki, Michal; Zabel, Maciej

2017-06-01

The definition of vault (ribonucleoprotein particles) function remains highly complex. Vaults may cooperate with multidrug resistance (MDR) proteins, supporting their role in drug resistance. This topic is the main theme of this publication. The cell viability was determined by an MTT assay. The protein expression was detected by western blot analysis. The proteins were knocked-down using siRNA. No major vault protein (MVP) in the LoVo/Dx and W1PR cell lines after tunicamycin treatment was shown. In W1PR cells with knocked-down MVP, a statistically significant decrease in cell viability was noted. In LoVo/Dx, W1TR and A2780TR cells were vault poly-ADP-ribose polymerase (vPARP) was knockdown, a decrease in cell viability was shown. Also, MVP silencing induced an increase in glycoprotein P (Pgp) expression in LoVo/Dx cells. MVP is important for the drug resistance of cancer cells, but it probably requires the presence of vPARP for full activation. Some correlations between MDR proteins and vaults exist. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Failure of Chemotherapy in Hepatocellular Carcinoma Due to Impaired and Dysregulated Primary Liver Drug Metabolizing Enzymes and Drug Transport Proteins: What to Do?

Science.gov (United States)

Ul Islam, Salman; Ahmed, Muhammad Bilal; Shehzad, Adeeb; Ul-Islam, Mazhar; Lee, Young Sup

2018-05-28

Most of the drugs are metabolized in the liver by the action of drug metabolizing enzymes. In hepatocellular carcinoma (HCC), primary drug metabolizing enzymes are severely dysregulated, leading to failure of chemotherapy. Sorafenib is the only standard systemic drug available, but it still presents certain limitations, and much effort is required to understand who is responsive and who is refractory to the drug. Preventive and therapeutic approaches other than systemic chemotherapy include vaccination, chemoprevention, liver transplantation, surgical resection, and locoregional therapies. This review details the dysregulation of primary drug metabolizing enzymes and drug transport proteins of the liver in HCC and their influence on chemotherapeutic drugs. Furthermore, it emphasizes the adoption of safe alternative therapeutic strategies to chemotherapy. The future of HCC treatment should emphasize the understanding of resistance mechanisms and the finding of novel, safe, and efficacious therapeutic strategies, which will surely benefit patients affected by advanced HCC. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A two-dimensional mathematical model of percutaneous drug absorption

Directory of Open Access Journals (Sweden)

Kubota K

2004-06-01

Full Text Available Abstract Background When a drug is applied on the skin surface, the concentration of the drug accumulated in the skin and the amount of the drug eliminated into the blood vessel depend on the value of a parameter, r. The values of r depend on the amount of diffusion and the normalized skin-capillary clearence. It is defined as the ratio of the steady-state drug concentration at the skin-capillary boundary to that at the skin-surface in one-dimensional models. The present paper studies the effect of the parameter values, when the region of contact of the skin with the drug, is a line segment on the skin surface. Methods Though a simple one-dimensional model is often useful to describe percutaneous drug absorption, it may be better represented by multi-dimensional models. A two-dimensional mathematical model is developed for percutaneous absorption of a drug, which may be used when the diffusion of the drug in the direction parallel to the skin surface must be examined, as well as in the direction into the skin, examined in one-dimensional models. This model consists of a linear second-order parabolic equation with appropriate initial conditions and boundary conditions. These boundary conditions are of Dirichlet type, Neumann type or Robin type. A finite-difference method which maintains second-order accuracy in space along the boundary, is developed to solve the parabolic equation. Extrapolation in time is applied to improve the accuracy in time. Solution of the parabolic equation gives the concentration of the drug in the skin at a given time. Results Simulation of the numerical methods described is carried out with various values of the parameter r. The illustrations are given in the form of figures. Conclusion Based on the values of r, conclusions are drawn about (1 the flow rate of the drug, (2 the flux and the cumulative amount of drug eliminated into the receptor cell, (3 the steady-state value of the flux, (4 the time to reach the steady

Development of a green fluorescent protein metastatic-cancer chick-embryo drug-screen model.

Science.gov (United States)

Bobek, Vladimir; Plachy, Jiri; Pinterova, Daniela; Kolostova, Katarina; Boubelik, Michael; Jiang, Ping; Yang, Meng; Hoffman, Robert M

2004-01-01

The chick-embryo model has been an important tool to study tumor growth, metastasis, and angiogenesis. However, an imageable model with a genetic fluorescent tag in the growing and spreading cancer cells that is stable over time has not been developed. We report here the development of such an imageable fluorescent chick-embryo metastatic cancer model with the use of green fluorescent protein (GFP). Lewis lung carcinoma cells, stably expressing GFP, were injected on the 12th day of incubation in the chick embryo. GFP-Lewis lung carcinoma metastases were visualized by fluorescence, after seven days additional incubation, in the brain, heart, and sternum of the developing chick embryo, with the most frequent site being the brain. The combination of streptokinase and gemcitabine was evaluated in this GFP metastatic model. Twelve-day-old chick embryos were injected intravenously with GFP-Lewis lung cancer cells, along with these two agents either alone or in combination. The streptokinase-gemcitabine combination inhibited metastases at all sites. The effective dose of gemcitabine was found to be 10 mg/kg and streptokinase 2000 IU per embryo. The data in this report suggest that this new stably fluorescent imageable metastatic-cancer chick-embryo model will enable rapid screening of new antimetastatic agents.

Zebrafish models in neuropsychopharmacology and CNS drug discovery.

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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.

SC lipid model membranes designed for studying impact of ceramide species on drug diffusion and permeation--part II: diffusion and permeation of model drugs.

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Ochalek, M; Podhaisky, H; Ruettinger, H-H; Wohlrab, J; Neubert, R H H

2012-10-01

The barrier function of two quaternary stratum corneum (SC) lipid model membranes, which were previously characterized with regard to the lipid organization, was investigated based on diffusion studies of model drugs with varying lipophilicities. Diffusion experiments of a hydrophilic drug, urea, and more lipophilic drugs than urea (i.e. caffeine, diclofenac sodium) were conducted using Franz-type diffusion cells. The amount of permeated drug was analyzed using either HPLC or CE technique. The subjects of interest in the present study were the investigation of the influence of physicochemical properties of model drugs on their diffusion and permeation through SC lipid model membranes, as well as the study of the impact of the constituents of these artificial systems (particularly ceramide species) on their barrier properties. The diffusion through both SC lipid model membranes and the human SC of the most hydrophilic model drug, urea, was faster than the permeation of the more lipophilic drugs. The slowest rate of permeation through SC lipid systems occurred in the case of caffeine. The composition of SC lipid model membranes has a significant impact on their barrier function. Model drugs diffused and permeated faster through Membrane II (presence of Cer [EOS]). In terms of the barrier properties, Membrane II is much more similar to the human SC than Membrane I. Copyright © 2012 Elsevier B.V. All rights reserved.

Development and evaluation of mucoadhesive nanoparticles based on thiolated Eudragit for oral delivery of protein drugs

International Nuclear Information System (INIS)

Zhang, Yan; Yang, Zhijie; Hu, Xi; Zhang, Ling; Li, Feng; Li, Meimei; Tang, Xing; Xiao, Wei

2015-01-01

The objective of this study was to develop pH-sensitive Eudragit L100–cysteine/reduced glutathione (Eul–cys/GSH) nanoparticles (NPs), which provided the mucoadhesion and protection for protein drugs against enzymatic degradation. Insulin was chosen as a model biomolecule for testing this system. The Eul–cys conjugate, which was obtained by grafting cysteine onto the carboxy group of Eudragit L100, was analyzed by HNMR and SEM, and the swelling degree (SD), cation binding, and enzymatic inhibition were also determined. The results obtained showed that the Eul–cys conjugate represent a pH-sensitive delivery system which effectively protected the insulin from being degraded by the proteases, and this is related to the mechanism of Ca 2+ binding. Insulin-loaded Eul–cys/GSH NPs were prepared by a diffusion method involving an electrostatic interaction between the network structure of the polymer and the embedded proteins, including insulin and GSH. TEM images indicated that Eul–cys/GSH existed as smooth and spherical NPs in aqueous solution with particle sizes of 260 ± 20 nm. The X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) findings showed the presence of amorphous insulin in thiolated NPs and higher free thiol oxidation than the result obtained by Ellman’s reagent method. In addition, thiolated NPs showed excellent binding efficiency to the mucin in rat intestine, indicating that Eul–cys/GSH NPs have great potential to be applied as safe carriers for the oral administration of protein drugs

Development and evaluation of mucoadhesive nanoparticles based on thiolated Eudragit for oral delivery of protein drugs

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yan [Shenyang University, Normal College (China); Yang, Zhijie; Hu, Xi; Zhang, Ling [Shenyang Pharmaceutical University, Department of Pharmaceutics (China); Li, Feng; Li, Meimei [Shenyang University, Normal College (China); Tang, Xing [Shenyang Pharmaceutical University, Department of Pharmaceutics (China); Xiao, Wei, E-mail: wzhzh-nj@tom.com [Jiangsu Kanion Pharmaceutical Co., Ltd (China)

2015-02-15

The objective of this study was to develop pH-sensitive Eudragit L100–cysteine/reduced glutathione (Eul–cys/GSH) nanoparticles (NPs), which provided the mucoadhesion and protection for protein drugs against enzymatic degradation. Insulin was chosen as a model biomolecule for testing this system. The Eul–cys conjugate, which was obtained by grafting cysteine onto the carboxy group of Eudragit L100, was analyzed by HNMR and SEM, and the swelling degree (SD), cation binding, and enzymatic inhibition were also determined. The results obtained showed that the Eul–cys conjugate represent a pH-sensitive delivery system which effectively protected the insulin from being degraded by the proteases, and this is related to the mechanism of Ca{sup 2+} binding. Insulin-loaded Eul–cys/GSH NPs were prepared by a diffusion method involving an electrostatic interaction between the network structure of the polymer and the embedded proteins, including insulin and GSH. TEM images indicated that Eul–cys/GSH existed as smooth and spherical NPs in aqueous solution with particle sizes of 260 ± 20 nm. The X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) findings showed the presence of amorphous insulin in thiolated NPs and higher free thiol oxidation than the result obtained by Ellman’s reagent method. In addition, thiolated NPs showed excellent binding efficiency to the mucin in rat intestine, indicating that Eul–cys/GSH NPs have great potential to be applied as safe carriers for the oral administration of protein drugs.

Completion of autobuilt protein models using a database of protein fragments

International Nuclear Information System (INIS)

Cowtan, Kevin

2012-01-01

Two developments in the process of automated protein model building in the Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules. Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature

A theory of drug tolerance and dependence II: the mathematical model.

Science.gov (United States)

Peper, Abraham

2004-08-21

The preceding paper presented a model of drug tolerance and dependence. The model assumes the development of tolerance to a repeatedly administered drug to be the result of a regulated adaptive process. The oral detection and analysis of exogenous substances is proposed to be the primary stimulus for the mechanism of drug tolerance. Anticipation and environmental cues are in the model considered secondary stimuli, becoming primary in dependence and addiction or when the drug administration bypasses the natural-oral-route, as is the case when drugs are administered intravenously. The model considers adaptation to the effect of a drug and adaptation to the interval between drug taking autonomous tolerance processes. Simulations with the mathematical model demonstrate the model's behaviour to be consistent with important characteristics of the development of tolerance to repeatedly administered drugs: the gradual decrease in drug effect when tolerance develops, the high sensitivity to small changes in drug dose, the rebound phenomenon and the large reactions following withdrawal in dependence. The present paper discusses the mathematical model in terms of its design. The model is a nonlinear, learning feedback system, fully satisfying control theoretical principles. It accepts any form of the stimulus-the drug intake-and describes how the physiological processes involved affect the distribution of the drug through the body and the stability of the regulation loop. The mathematical model verifies the proposed theory and provides a basis for the implementation of mathematical models of specific physiological processes.

General transfer matrix formalism to calculate DNA-protein-drug binding in gene regulation: application to OR operator of phage lambda.

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Teif, Vladimir B

2007-01-01

The transfer matrix methodology is proposed as a systematic tool for the statistical-mechanical description of DNA-protein-drug binding involved in gene regulation. We show that a genetic system of several cis-regulatory modules is calculable using this method, considering explicitly the site-overlapping, competitive, cooperative binding of regulatory proteins, their multilayer assembly and DNA looping. In the methodological section, the matrix models are solved for the basic types of short- and long-range interactions between DNA-bound proteins, drugs and nucleosomes. We apply the matrix method to gene regulation at the O(R) operator of phage lambda. The transfer matrix formalism allowed the description of the lambda-switch at a single-nucleotide resolution, taking into account the effects of a range of inter-protein distances. Our calculations confirm previously established roles of the contact CI-Cro-RNAP interactions. Concerning long-range interactions, we show that while the DNA loop between the O(R) and O(L) operators is important at the lysogenic CI concentrations, the interference between the adjacent promoters P(R) and P(RM) becomes more important at small CI concentrations. A large change in the expression pattern may arise in this regime due to anticooperative interactions between DNA-bound RNA polymerases. The applicability of the matrix method to more complex systems is discussed.

Comparative Proteomic Characterization of 4 Human Liver-Derived Single Cell Culture Models Reveals Significant Variation in the Capacity for Drug Disposition, Bioactivation, and Detoxication.

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Sison-Young, Rowena L C; Mitsa, Dimitra; Jenkins, Rosalind E; Mottram, David; Alexandre, Eliane; Richert, Lysiane; Aerts, Hélène; Weaver, Richard J; Jones, Robert P; Johann, Esther; Hewitt, Philip G; Ingelman-Sundberg, Magnus; Goldring, Christopher E P; Kitteringham, Neil R; Park, B Kevin

2015-10-01

In vitro preclinical models for the assessment of drug-induced liver injury (DILI) are usually based on cryopreserved primary human hepatocytes (cPHH) or human hepatic tumor-derived cell lines; however, it is unclear how well such cell models reflect the normal function of liver cells. The physiological, pharmacological, and toxicological phenotyping of available cell-based systems is necessary in order to decide the testing purpose for which they are fit. We have therefore undertaken a global proteomic analysis of 3 human-derived hepatic cell lines (HepG2, Upcyte, and HepaRG) in comparison with cPHH with a focus on drug metabolizing enzymes and transport proteins (DMETs), as well as Nrf2-regulated proteins. In total, 4946 proteins were identified, of which 2722 proteins were common across all cell models, including 128 DMETs. Approximately 90% reduction in expression of cytochromes P450 was observed in HepG2 and Upcyte cells, and approximately 60% in HepaRG cells relative to cPHH. Drug transporter expression was also lower compared with cPHH with the exception of MRP3 and P-gp (MDR1) which appeared to be significantly expressed in HepaRG cells. In contrast, a high proportion of Nrf2-regulated proteins were more highly expressed in the cell lines compared with cPHH. The proteomic database derived here will provide a rational basis for the context-specific selection of the most appropriate 'hepatocyte-like' cell for the evaluation of particular cellular functions associated with DILI and, at the same time, assist in the construction of a testing paradigm which takes into account the in vivo disposition of a new drug. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology.

Mathematical modeling and computational prediction of cancer drug resistance.

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Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

Improving Predictive Modeling in Pediatric Drug Development: Pharmacokinetics, Pharmacodynamics, and Mechanistic Modeling

Energy Technology Data Exchange (ETDEWEB)

Slikker, William; Young, John F.; Corley, Rick A.; Dorman, David C.; Conolly, Rory B.; Knudsen, Thomas; Erstad, Brian L.; Luecke, Richard H.; Faustman, Elaine M.; Timchalk, Chuck; Mattison, Donald R.

2005-07-26

A workshop was conducted on November 18?19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adultlike in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.

3D pancreatic carcinoma spheroids induce a matrix-rich, chemoresistant phenotype offering a better model for drug testing

International Nuclear Information System (INIS)

Longati, Paola; Heuchel, Rainer L; Jia, Xiaohui; Eimer, Johannes; Wagman, Annika; Witt, Michael-Robin; Rehnmark, Stefan; Verbeke, Caroline; Toftgård, Rune; Löhr, Matthias

2013-01-01

Pancreatic ductal adenocarcinoma (PDAC) is the fourth most common cause of cancer related death. It is lethal in nearly all patients, due to an almost complete chemoresistance. Most if not all drugs that pass preclinical tests successfully, fail miserably in the patient. This raises the question whether traditional 2D cell culture is the correct tool for drug screening. The objective of this study is to develop a simple, high-throughput 3D model of human PDAC cell lines, and to explore mechanisms underlying the transition from 2D to 3D that might be responsible for chemoresistance. Several established human PDAC and a KPC mouse cell lines were tested, whereby Panc-1 was studied in more detail. 3D spheroid formation was facilitated with methylcellulose. Spheroids were studied morphologically, electron microscopically and by qRT-PCR for selected matrix genes, related factors and miRNA. Metabolic studies were performed, and a panel of novel drugs was tested against gemcitabine. Comparing 3D to 2D cell culture, matrix proteins were significantly increased as were lumican, SNED1, DARP32, and miR-146a. Cell metabolism in 3D was shifted towards glycolysis. All drugs tested were less effective in 3D, except for allicin, MT100 and AX, which demonstrated effect. We developed a high-throughput 3D cell culture drug screening system for pancreatic cancer, which displays a strongly increased chemoresistance. Features associated to the 3D cell model are increased expression of matrix proteins and miRNA as well as stromal markers such as PPP1R1B and SNED1. This is supporting the concept of cell adhesion mediated drug resistance

Self-Assembling Peptide Amphiphiles for Therapeutic Delivery of Proteins, Drugs, and Stem Cells

Science.gov (United States)

Lee, Sungsoo Seth

Biomaterials are used to help regenerate or replace the structure and function of damaged tissues. In order to elicit desired therapeutic responses in vivo, biomaterials are often functionalized with bioactive agents, such as growth factors, small molecule drugs, or even stem cells. Therefore, the strategies used to incorporate these bioactive agents in the microstructures and nanostructures of biomaterials can strongly influence the their therapeutic efficacy. Using self-assembling peptide amphiphiles (PAs), this work has investigated supramolecular nanostructures with improved interaction with three types of therapeutic agents: bone morphogenetic protein 2 (BMP-2) which promotes osteogenic differentiation and bone growth, anti-inflammatory drug naproxen which is used to treat osteo- and rheumatoid arthritis, and neural stem cells that could differentiate into neurons to treat neurodegenerative diseases. For BMP-2 delivery, two specific systems were investigated with affinity for BMP-2: 1) heparin-binding nanofibers that display the natural ligand of the osteogenic protein, and 2) nanofibers that display a synthetic peptide ligand discovered in our laboratory through phage display to directly bind BMP-2. Both systems promoted enhanced osteoblast differentiation of pluripotent C2C12 cells and augmented bone regeneration in two in vivo models, a rat critical-size femur defect model and spinal arthrodesis model. The thesis also describes the use of PA nanofibers to improve the delivery of the anti-inflammatory drug naproxen. To promote a controlled release, naproxen was chemically conjugated to the nanofiber surface via an ester bond that would only be cleaved by esterases, which are enzymes found naturally in the body. In the absence of esterases, the naproxen remained conjugated to the nanofibers and was non-bioactive. On the other hand, in the presence of esterases, naproxen was slowly released and inhibited cyclooxygenase-2 (COX-2) activity, an enzyme responsible

Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

Science.gov (United States)

Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

2012-01-01

High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

Drug target ontology to classify and integrate drug discovery data

DEFF Research Database (Denmark)

Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande

2017-01-01

using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem...... of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target...... characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein...

Moonlighting adenosine deaminase: a target protein for drug development.

Science.gov (United States)

Cortés, Antoni; Gracia, Eduard; Moreno, Estefania; Mallol, Josefa; Lluís, Carme; Canela, Enric I; Casadó, Vicent

2015-01-01

Interest in adenosine deaminase (ADA) in the context of medicine has mainly focused on its enzymatic activity. This is justified by the importance of the reaction catalyzed by ADA not only for the intracellular purine metabolism, but also for the extracellular purine metabolism as well, because of its capacity as a regulator of the concentration of extracellular adenosine that is able to activate adenosine receptors (ARs). In recent years, other important roles have been described for ADA. One of these, with special relevance in immunology, is the capacity of ADA to act as a costimulator, promoting T-cell proliferation and differentiation mainly by interacting with the differentiation cluster CD26. Another role is the ability of ADA to act as an allosteric modulator of ARs. These receptors have very general physiological implications, particularly in the neurological system where they play an important role. Thus, ADA, being a single chain protein, performs more than one function, consistent with the definition of a moonlighting protein. Although ADA has never been associated with moonlighting proteins, here we consider ADA as an example of this family of multifunctional proteins. In this review, we discuss the different roles of ADA and their pathological implications. We propose a mechanism by which some of their moonlighting functions can be coordinated. We also suggest that drugs modulating ADA properties may act as modulators of the moonlighting functions of ADA, giving them additional potential medical interest. © 2014 Wiley Periodicals, Inc.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

Science.gov (United States)

Basith, Shaherin; Cui, Minghua; Macalino, Stephani J. Y.; Park, Jongmi; Clavio, Nina A. B.; Kang, Soosung; Choi, Sun

2018-01-01

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the “golden age for GPCR structural biology.” Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand– and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed. PMID:29593527

Controlling the shape of membrane protein polyhedra

Science.gov (United States)

Li, Di; Kahraman, Osman; Haselwandter, Christoph A.

2017-03-01

Membrane proteins and lipids can self-assemble into membrane protein polyhedral nanoparticles (MPPNs). MPPNs have a closed spherical surface and a polyhedral protein arrangement, and may offer a new route for structure determination of membrane proteins and targeted drug delivery. We develop here a general analytic model of how MPPN self-assembly depends on bilayer-protein interactions and lipid bilayer mechanical properties. We find that the bilayer-protein hydrophobic thickness mismatch is a key molecular control parameter for MPPN shape that can be used to bias MPPN self-assembly towards highly symmetric and uniform MPPN shapes. Our results suggest strategies for optimizing MPPN shape for structural studies of membrane proteins and targeted drug delivery.

Oral delivery of peptides and proteins using lipid-based drug delivery systems.

Science.gov (United States)

Li, Ping; Nielsen, Hanne Mørck; Müllertz, Anette

2012-10-01

In order to successfully develop lipid-based drug delivery systems (DDS) for oral administration of peptides and proteins, it is important to gain an understanding of the colloid structures formed by these DDS, the mode of peptide and protein incorporation as well as the mechanism by which intestinal absorption of peptides and proteins is promoted. The present paper reviews the literature on lipid-based DDS, employed for oral delivery of peptides and proteins and highlights the mechanisms by which the different lipid-based carriers are expected to overcome the two most important barriers (extensive enzymatic degradation and poor transmucosal permeability). This paper also gives a clear-cut idea about advantages and drawbacks of using different lipidic colloidal carriers ((micro)emulsions, solid lipid core particles and liposomes) for oral delivery of peptides and proteins. Lipid-based DDS are safe and suitable for oral delivery of peptides and proteins. Significant progress has been made in this area with several technologies on clinical trials. However, a better understanding of the mechanism of action in vivo is needed in order to improve the design and development of lipid-based DDS with the desired bioavailability and therapeutic profile.

Drug target mining and analysis of the Chinese tree shrew for pharmacological testing.

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Feng Zhao

Full Text Available The discovery of new drugs requires the development of improved animal models for drug testing. The Chinese tree shrew is considered to be a realistic candidate model. To assess the potential of the Chinese tree shrew for pharmacological testing, we performed drug target prediction and analysis on genomic and transcriptomic scales. Using our pipeline, 3,482 proteins were predicted to be drug targets. Of these predicted targets, 446 and 1,049 proteins with the highest rank and total scores, respectively, included homologs of targets for cancer chemotherapy, depression, age-related decline and cardiovascular disease. Based on comparative analyses, more than half of drug target proteins identified from the tree shrew genome were shown to be higher similarity to human targets than in the mouse. Target validation also demonstrated that the constitutive expression of the proteinase-activated receptors of tree shrew platelets is similar to that of human platelets but differs from that of mouse platelets. We developed an effective pipeline and search strategy for drug target prediction and the evaluation of model-based target identification for drug testing. This work provides useful information for future studies of the Chinese tree shrew as a source of novel targets for drug discovery research.

In silico modeling of the yeast protein and protein family interaction network

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Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

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

Directory of Open Access Journals (Sweden)

Klara Livia Valko

2017-03-01

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

The safety, efficacy and regulatory triangle in drug development: Impact for animal models and the use of animals.

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van Meer, Peter J K; Graham, Melanie L; Schuurman, Henk-Jan

2015-07-15

Nonclinical studies in animals are conducted to demonstrate proof-of-concept, mechanism of action and safety of new drugs. For a large part, in particular safety assessment, studies are done in compliance with international regulatory guidance. However, animal models supporting the initiation of clinical trials have their limitations, related to uncertainty regarding the predictive value for a clinical condition. The 3Rs principles (refinement, reduction and replacement) are better applied nowadays, with a more comprehensive application with respect to the original definition. This regards also regulatory guidance, so that opportunities exist to revise or reduce regulatory guidance with the perspective that the optimal balance between scientifically relevant data and animal wellbeing or a reduction in animal use can be achieved. In this manuscript we review the connections in the triangle between nonclinical efficacy/safety studies and regulatory aspects, with focus on in vivo testing of drugs. These connections differ for different drugs (chemistry-based low molecular weight compounds, recombinant proteins, cell therapy or gene therapy products). Regarding animal models and their translational value we focus on regulatory aspects and indications where scientific outcomes warrant changes, reduction or replacement, like for, e.g., biosimilar evaluation and safety testing of monoclonal antibodies. On the other hand, we present applications where translational value has been clearly demonstrated, e.g., immunosuppressives in transplantation. Especially for drugs of more recent date like recombinant proteins, cell therapy products and gene therapy products, a regulatory approach that allows the possibility to conduct combined efficacy/safety testing in validated animal models should strengthen scientific outcomes and improve translational value, while reducing the numbers of animals necessary. Copyright © 2015 Elsevier B.V. All rights reserved.

Simulating the influence of plasma protein on measured receptor affinity in biochemical assays reveals the utility of Schild analysis for estimating compound affinity for plasma proteins.

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Blakeley, D; Sykes, D A; Ensor, P; Bertran, E; Aston, P J; Charlton, S J

2015-11-01

Plasma protein binding (PPB) influences the free fraction of drug available to bind to its target and is therefore an important consideration in drug discovery. While traditional methods for assessing PPB (e.g. rapid equilibrium dialysis) are suitable for comparing compounds with relatively weak PPB, they are not able to accurately discriminate between highly bound compounds (typically >99.5%). The aim of the present work was to use mathematical modelling to explore the potential utility of receptor binding and cellular functional assays to estimate the affinity of compounds for plasma proteins. Plasma proteins are routinely added to in vitro assays, so a secondary goal was to investigate the effect of plasma proteins on observed ligand-receptor interactions. Using the principle of conservation of mass and the law of mass action, a cubic equation was derived describing the ligand-receptor complex [LR] in the presence of plasma protein at equilibrium. The model demonstrates the profound influence of PPB on in vitro assays and identifies the utility of Schild analysis, which is usually applied to determine receptor-antagonist affinities, for calculating affinity at plasma proteins (termed KP ). We have also extended this analysis to functional effects using operational modelling and demonstrate that these approaches can also be applied to cell-based assay systems. These mathematical models can potentially be used in conjunction with experimental data to estimate drug-plasma protein affinities in the earliest phases of drug discovery programmes. © 2015 The British Pharmacological Society.

Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome--clozapine-induced agranulocytosis as a case study.

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Lun Yang

2011-03-01

Full Text Available In the era of personalized medical practice, understanding the genetic basis of patient-specific adverse drug reaction (ADR is a major challenge. Clozapine provides effective treatments for schizophrenia but its usage is limited because of life-threatening agranulocytosis. A recent high impact study showed the necessity of moving clozapine to a first line drug, thus identifying the biomarkers for drug-induced agranulocytosis has become important. Here we report a methodology termed as antithesis chemical-protein interactome (CPI, which utilizes the docking method to mimic the differences in the drug-protein interactions across a panel of human proteins. Using this method, we identified HSPA1A, a known susceptibility gene for CIA, to be the off-target of clozapine. Furthermore, the mRNA expression of HSPA1A-related genes (off-target associated systems was also found to be differentially expressed in clozapine treated leukemia cell line. Apart from identifying the CIA causal genes we identified several novel candidate genes which could be responsible for agranulocytosis. Proteins related to reactive oxygen clearance system, such as oxidoreductases and glutathione metabolite enzymes, were significantly enriched in the antithesis CPI. This methodology conducted a multi-dimensional analysis of drugs' perturbation to the biological system, investigating both the off-targets and the associated off-systems to explore the molecular basis of an adverse event or the new uses for old drugs.

[A model list of high risk drugs].

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Cotrina Luque, J; Guerrero Aznar, M D; Alvarez del Vayo Benito, C; Jimenez Mesa, E; Guzman Laura, K P; Fernández Fernández, L

2013-12-01

«High-risk drugs» are those that have a very high «risk» of causing death or serious injury if an error occurs during its use. The Institute for Safe Medication Practices (ISMP) has prepared a high-risk drugs list applicable to the general population (with no differences between the pediatric and adult population). Thus, there is a lack of information for the pediatric population. The main objective of this work is to develop a high-risk drug list adapted to the neonatal or pediatric population as a reference model for the pediatric hospital health workforce. We made a literature search in May 2012 to identify any published lists or references in relation to pediatric and/or neonatal high-risk drugs. A total of 15 studies were found, from which 9 were selected. A model list was developed mainly based on the ISMP one, adding strongly perceived pediatric risk drugs and removing those where the pediatric use was anecdotal. There is no published list that suits pediatric risk management. The list of pediatric and neonatal high-risk drugs presented here could be a «reference list of high-risk drugs » for pediatric hospitals. Using this list and training will help to prevent medication errors in each drug supply chain (prescribing, transcribing, dispensing and administration). Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

DNA modifications by platinum antitumor drugs and its recognition by DNA-binding proteins

Czech Academy of Sciences Publication Activity Database

Brabec, Viktor

2004-01-01

Roč. 271, Suppl. 1 (2004), s. 90 ISSN 0014-2956. [Meeting of the Federation of the European Biochemical Societies /29./. 26.06.2004-01.07.2004, Warsaw] R&D Projects: GA ČR GA305/02/1552 Keywords : platinum drugs * DNA-protein interaction * NF-kappaB Subject RIV: BO - Biophysics

Animal models of pancreatic cancer for drug research.

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Kapischke, Matthias; Pries, Alexandra

2008-10-01

The operative and conservative results of therapy in pancreatic ductal adenocarcinoma remain appallingly poor. This underlines the demand for further research for effective anticancer drugs. The various animal models remain the essential method for the determination of efficacy of substances during preclinical phase. Unfortunately, most of these tested substances showed a good efficacy in pancreatic carcinoma in the animal model but were not confirmed during the clinical phase. The available literature in PubMed, Medline, Ovid and secondary literature was searched regarding the available animal models for drug testing against pancreatic cancer. The models were analyzed regarding their pros and cons in anticancer drug testing. The different modifications of the orthotopic model (especially in mice) seem at present to be the best model for anticancer testing in pancreatic carcinoma. The value of genetically engineered animal model (GEM) and syngeneic models is on debate. A good selection of the model concerning the questions supposed to be clarified may improve the comparability of the results of animal experiments compared to clinical trials.

Multiple drug resistance protein (MDR-1, multidrug resistance-related protein (MRP and lung resistance protein (LRP gene expression in childhood acute lymphoblastic leukemia

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Elvis Terci Valera

Full Text Available CONTEXT: Despite the advances in the cure rate for acute lymphoblastic leukemia, approximately 25% of affected children suffer relapses. Expression of genes for the multiple drug resistance protein (MDR-1, multidrug resistance-related protein (MRP, and lung resistance protein (LRP may confer the phenotype of resistance to the treatment of neoplasias. OBJECTIVE: To analyze the expression of the MDR-1, MRP and LRP genes in children with a diagnosis of acute lymphoblastic leukemia via the semiquantitative reverse transcription polymerase chain reaction (RT-PCR, and to determine the correlation between expression and event-free survival and clinical and laboratory variables. DESIGN: A retrospective clinical study. SETTING: Laboratory of Pediatric Oncology, Department of Pediatrics, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Brazil. METHODS: Bone marrow aspirates from 30 children with a diagnosis of acute lymphoblastic leukemia were assessed for the expression of messenger RNA for the MDR-1, MRP and LRP genes by semi-quantitative RT-PCR. RESULTS: In the three groups studied, only the increased expression of LRP was related to worsened event-free survival (p = 0.005. The presence of the common acute lymphoblastic leukemia antigen (CALLA was correlated with increased LRP expression (p = 0.009 and increased risk of relapse or death (p = 0.05. The relative risk of relapse or death was six times higher among children with high LRP expression upon diagnosis (p = 0.05, as confirmed by multivariate analysis of the three genes studied (p = 0.035. DISCUSSION: Cell resistance to drugs is a determinant of the response to chemotherapy and its detection via RT-PCR may be of clinical importance. CONCLUSIONS: Evaluation of the expression of genes for resistance to antineoplastic drugs in childhood acute lymphoblastic leukemia upon diagnosis, and particularly the expression of the LRP gene, may be of clinical relevance, and should be the

Design of Protein-Coated Carbon Nanotubes Loaded with Hydrophobic Drugs through Sacrificial Templating of Mesoporous Silica Shells.

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Fiegel, Vincent; Harlepp, Sebastien; Begin-Colin, Sylvie; Begin, Dominique; Mertz, Damien

2018-03-26

One key challenge in the fields of nanomedicine and tissue engineering is the design of theranostic nanoplatforms able to monitor their therapeutic effect by imaging. Among current developed nano-objects, carbon nanotubes (CNTs) were found suitable to combine imaging, photothermal therapy, and to be loaded with hydrophobic drugs. However, a main problem is their resulting low hydrophilicity. To face this problem, an innovative method is developed here, which consists in loading the surface of carbon nanotubes (CNTs) with drugs followed by a protein coating around them. The originality of this method relies on first covering CNTs with a sacrificial template mesoporous silica (MS) shell grafted with isobutyramide (IBAM) binders on which a protein nanofilm is strongly adhered through IBAM-mediated physical cross-linking. This concept is first demonstrated without drugs, and is further improved with the suitable loading of hydrophobic drugs, curcumin (CUR) and camptothecin (CPT), which are retained between the CNTs and human serum albumin (HSA) layer. Such novel nanocomposites with favorable photothermal properties are very promising for theranostic systems, drug delivery, and phototherapy applications. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drug Release from ß-Cyclodextrin Complexes and Drug Transfer into Model Membranes Studied by Affinity Capillary Electrophoresis.

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Darwish, Kinda A; Mrestani, Yahya; Rüttinger, Hans-Hermann; Neubert, Reinhard H H

2016-05-01

Is to characterize the drug release from the ß-cyclodextrin (ß-CD) cavity and the drug transfer into model membranes by affinity capillary electrophoresis. Phospholipid liposomes with and without cholesterol were used to mimic the natural biological membrane. The interaction of cationic and anionic drugs with ß-CD and the interaction of the drugs with liposomes were detected separately by measuring the drug mobility in ß-CD containing buffer and liposome containing buffer; respectively. Moreover, the kinetics of drug release from ß-CD and its transfer into liposomes with or without cholesterol was studied by investigation of changes in the migration behaviours of the drugs in samples, contained drug, ß-CD and liposome, at 1:1:1 molar ratio at different time intervals; zero time, 30 min, 1, 2, 4, 6, 8, 10 and 24 h. Lipophilic drugs such as propranolol and ibuprofen were chosen for this study, because they form complexes with ß-CD. The mobility of the both drug liposome mixtures changed with time to a final state. For samples of liposomal membranes with cholesterol the final state was faster reached than without cholesterol. The study confirmed that the drug release from the CD cavity and its transfer into the model membrane was more enhanced by the competitive displacement of the drug from the ß-CD cavity by cholesterol, the membrane component. The ACE method here developed can be used to optimize the drug release from CD complexes and the drug transfer into model membranes.

A Mesoscopic Model for Protein-Protein Interactions in Solution

OpenAIRE

Lund, Mikael; Jönsson, Bo

2003-01-01

Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

Targeting protein-protein interactions for parasite control.

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Christina M Taylor

2011-04-01

Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly

Mathematical modeling of efficacy and safety for anticancer drugs clinical development.

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Lavezzi, Silvia Maria; Borella, Elisa; Carrara, Letizia; De Nicolao, Giuseppe; Magni, Paolo; Poggesi, Italo

2018-01-01

Drug attrition in oncology clinical development is higher than in other therapeutic areas. In this context, pharmacometric modeling represents a useful tool to explore drug efficacy in earlier phases of clinical development, anticipating overall survival using quantitative model-based metrics. Furthermore, modeling approaches can be used to characterize earlier the safety and tolerability profile of drug candidates, and, thus, the risk-benefit ratio and the therapeutic index, supporting the design of optimal treatment regimens and accelerating the whole process of clinical drug development. Areas covered: Herein, the most relevant mathematical models used in clinical anticancer drug development during the last decade are described. Less recent models were considered in the review if they represent a standard for the analysis of certain types of efficacy or safety measures. Expert opinion: Several mathematical models have been proposed to predict overall survival from earlier endpoints and validate their surrogacy in demonstrating drug efficacy in place of overall survival. An increasing number of mathematical models have also been developed to describe the safety findings. Modeling has been extensively used in anticancer drug development to individualize dosing strategies based on patient characteristics, and design optimal dosing regimens balancing efficacy and safety.

Comparative genomics study for the identification of drug and vaccine targets in Staphylococcus aureus: MurA ligase enzyme as a proposed candidate.

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Ghosh, Soma; Prava, Jyoti; Samal, Himanshu Bhusan; Suar, Mrutyunjay; Mahapatra, Rajani Kanta

2014-06-01

Now-a-days increasing emergence of antibiotic-resistant pathogenic microorganisms is one of the biggest challenges for management of disease. In the present study comparative genomics, metabolic pathways analysis and additional parameters were defined for the identification of 94 non-homologous essential proteins in Staphylococcus aureus genome. Further study prioritized 19 proteins as vaccine candidates where as druggability study reports 34 proteins suitable as drug targets. Enzymes from peptidoglycan biosynthesis, folate biosynthesis were identified as candidates for drug development. Furthermore, bacterial secretory proteins and few hypothetical proteins identified in our analysis fulfill the criteria of vaccine candidates. As a case study, we built a homology model of one of the potential drug target, MurA ligase, using MODELLER (9v12) software. The model has been further selected for in silico docking study with inhibitors from the DrugBank database. Results from this study could facilitate selection of proteins for entry into drug design and vaccine production pipelines. Copyright © 2014 Elsevier B.V. All rights reserved.

Hydroxyapatite hierarchically nanostructured porous hollow microspheres: rapid, sustainable microwave-hydrothermal synthesis by using creatine phosphate as an organic phosphorus source and application in drug delivery and protein adsorption.

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Qi, Chao; Zhu, Ying-Jie; Lu, Bing-Qiang; Zhao, Xin-Yu; Zhao, Jing; Chen, Feng; Wu, Jin

2013-04-22

Hierarchically nanostructured porous hollow microspheres of hydroxyapatite (HAP) are a promising biomaterial, owing to their excellent biocompatibility and porous hollow structure. Traditionally, synthetic hydroxyapatite is prepared by using an inorganic phosphorus source. Herein, we report a new strategy for the rapid, sustainable synthesis of HAP hierarchically nanostructured porous hollow microspheres by using creatine phosphate disodium salt as an organic phosphorus source in aqueous solution through a microwave-assisted hydrothermal method. The as-obtained products are characterized by powder X-ray diffraction (XRD), Fourier-transform IR (FTIR) spectroscopy, SEM, TEM, Brunauer-Emmett-Teller (BET) nitrogen sorptometry, dynamic light scattering (DLS), and thermogravimetric analysis (TGA). SEM and TEM micrographs show that HAP hierarchically nanostructured porous hollow microspheres consist of HAP nanosheets or nanorods as the building blocks and DLS measurements show that the diameters of HAP hollow microspheres are within the range 0.8-1.5 μm. The specific surface area and average pore size of the HAP porous hollow microspheres are 87.3 m(2) g(-1) and 20.6 nm, respectively. The important role of creatine phosphate disodium salt and the influence of the experimental conditions on the products were systematically investigated. This method is facile, rapid, surfactant-free and environmentally friendly. The as-prepared HAP porous hollow microspheres show a relatively high drug-loading capacity and protein-adsorption ability, as well as sustained drug and protein release, by using ibuprofen as a model drug and hemoglobin (Hb) as a model protein, respectively. These experiments indicate that the as-prepared HAP porous hollow microspheres are promising for applications in biomedical fields, such as drug delivery and protein adsorption. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction of protein-protein interactions between viruses and human by an SVM model

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Cui Guangyu

2012-05-01

Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

Cell physiology based pharmacodynamic modeling of antimicrobial drug combinations

OpenAIRE

Hethey, Christoph Philipp

2017-01-01

Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. In...

Protein structure similarity clustering (PSSC) and natural product structure as inspiration sources for drug development and chemical genomics

NARCIS (Netherlands)

Dekker, Frank J; Koch, Marcus A; Waldmann, Herbert; Dekker, Frans

Finding small molecules that modulate protein function is of primary importance in drug development and in the emerging field of chemical genomics. To facilitate the identification of such molecules, we developed a novel strategy making use of structural conservatism found in protein domain

Illustrating and homology modeling the proteins of the Zika virus [version 2; referees: 2 approved

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Sean Ekins

2016-09-01

Full Text Available The Zika virus (ZIKV is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

Prediction of adverse drug reactions using decision tree modeling.

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Hammann, F; Gutmann, H; Vogt, N; Helma, C; Drewe, J

2010-07-01

Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.

From chemical graphs in computer-aided drug design to general Markov-Galvez indices of drug-target, proteome, drug-parasitic disease, technological, and social-legal networks.

Science.gov (United States)

Riera-Fernández, Pablo; Munteanu, Cristian R; Dorado, Julian; Martin-Romalde, Raquel; Duardo-Sanchez, Aliuska; González-Diaz, Humberto

2011-12-01

Complex Networks are useful in solving problems in drug research and industry, developing mathematical representations of different systems. These systems move in a wide range from relatively simple graph representations of drug molecular structures to large systems. We can cite for instance, drug-target protein interaction networks, drug policy legislation networks, or drug treatment in large geographical disease spreading networks. In any case, all these networks have essentially the same components: nodes (atoms, drugs, proteins, microorganisms and/or parasites, geographical areas, drug policy legislations, etc.) and edges (chemical bonds, drug-target interactions, drug-parasite treatment, drug use, etc.). Consequently, we can use the same type of numeric parameters called Topological Indices (TIs) to describe the connectivity patterns in all these kinds of Complex Networks despite the nature of the object they represent. The main reason for this success of TIs is the high flexibility of this theory to solve in a fast but rigorous way many apparently unrelated problems in all these disciplines. Another important reason for the success of TIs is that using these parameters as inputs we can find Quantitative Structure-Property Relationships (QSPR) models for different kind of problems in Computer-Aided Drug Design (CADD). Taking into account all the above-mentioned aspects, the present work is aimed at offering a common background to all the manuscripts presented in this special issue. In so doing, we make a review of the most common types of complex networks involving drugs or their targets. In addition, we review both classic TIs that have been used to describe the molecular structure of drugs and/or larger complex networks. Next, we use for the first time a Markov chain model to generalize Galvez TIs to higher order analogues coined here as the Markov-Galvez TIs of order k (MGk). Lastly, we illustrate the calculation of MGk values for different classes of

Fragment-based drug discovery and protein–protein interactions

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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

The Food and Drug Administration and Drug Legalization: A Brief Model of Regulation

OpenAIRE

Kalam, Murad

2002-01-01

This paper offers a brief model of FDA regulation of currently illegal narcotics in the United States. Given that nearly three out of four Americans believe that the drug war has failed, recent calls from prominent liberal and conservative thinkers to legalize drugs, and state “compassionate use†ballot initiatives, future drug legalization is at least conceivable in the United States. Yet, how would the FDA regulate NLD’s under its current st...

Target specific proteochemometric model development for BACE1 - protein flexibility and structural water are critical in virtual screening.

Science.gov (United States)

Manoharan, Prabu; Chennoju, Kiranmai; Ghoshal, Nanda

2015-07-01

BACE1 is an attractive target in Alzheimer's disease (AD) treatment. A rational drug design effort for the inhibition of BACE1 is actively pursued by researchers in both academic and pharmaceutical industries. This continued effort led to the steady accumulation of BACE1 crystal structures, co-complexed with different classes of inhibitors. This wealth of information is used in this study to develop target specific proteochemometric models and these models are exploited for predicting the prospective BACE1 inhibitors. The models developed in this study have performed excellently in predicting the computationally generated poses, separately obtained from single and ensemble docking approaches. The simple protein-ligand contact (SPLC) model outperforms other sophisticated high end models, in virtual screening performance, developed during this study. In an attempt to account for BACE1 protein active site flexibility information in predictive models, we included the change in the area of solvent accessible surface and the change in the volume of solvent accessible surface in our models. The ensemble and single receptor docking results obtained from this study indicate that the structural water mediated interactions improve the virtual screening results. Also, these waters are essential for recapitulating bioactive conformation during docking study. The proteochemometric models developed in this study can be used for the prediction of BACE1 inhibitors, during the early stage of AD drug discovery.

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

Science.gov (United States)

Cherkaoui-Rbati, Mohammed H; Paine, Stuart W; Littlewood, Peter; Rauch, Cyril

2017-01-01

All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

Directory of Open Access Journals (Sweden)

Mohammed H Cherkaoui-Rbati

Full Text Available All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs of new chemical entities (NCEs and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit, located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level. A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

Assessing the utility of an anti-malarial pharmacokinetic-pharmacodynamic model for aiding drug clinical development

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Zaloumis Sophie

2012-08-01

Full Text Available Abstract Background Mechanistic within-host models relating blood anti-malarial drug concentrations with the parasite-time profile help in assessing dosing schedules and partner drugs for new anti-malarial treatments. A comprehensive simulation study to assess the utility of a stage-specific pharmacokinetic-pharmacodynamic (PK-PD model for predicting within-host parasite response was performed. Methods Three anti-malarial combination therapies were selected: artesunate-mefloquine, dihydroartemisinin-piperaquine, and artemether-lumefantrine. The PK-PD model included parameters to represent the concentration-time profiles of both drugs, the initial parasite burden and distribution across the parasite life cycle, and the parasite multiplication factor due to asexual reproduction. The model also included the maximal killing rate of each drug, and the blood drug concentration associated with half of that killing effect (in vivo EC50, derived from the in vitro IC50, the extent of binding to 0.5% Albumax present in the in vitro testing media, and the drugs plasma protein binding and whole blood to plasma partitioning ratio. All stochastic simulations were performed using a Latin-Hypercube-Sampling approach. Results The simulations demonstrated that the proportion of patients cured was highly sensitive to the in vivo EC50 and the maximal killing rate of the partner drug co-administered with the artemisinin derivative. The in vivo EC50 values that corresponded to on average 95% of patients cured were much higher than the adjusted values derived from the in vitro IC50. The proportion clinically cured was not strongly influenced by changes in the parameters defining the age distribution of the initial parasite burden (mean age of 4 to 16 hours and the parasite multiplication factor every life cycle (ranging from 8 to 12 fold/cycle. The median parasite clearance times, however, lengthened as the standard deviation of the initial parasite burden increased (i

Highly stable, protein capped gold nanoparticles as effective drug delivery vehicles for amino-glycosidic antibiotics

International Nuclear Information System (INIS)

Rastogi, Lori; Kora, Aruna Jyothi; Arunachalam, J.

2012-01-01

A method for the production of highly stable gold nanoparticles (Au NP) was optimized using sodium borohydride as reducing agent and bovine serum albumin as capping agent. The synthesized nanoparticles were characterized using UV–visible spectroscopy, transmission electron microscopy, X‐ray diffraction (XRD) and dynamic light scattering techniques. The formation of gold nanoparticles was confirmed from the appearance of pink colour and an absorption maximum at 532 nm. These protein capped nanoparticles exhibited excellent stability towards pH modification and electrolyte addition. The produced nanoparticles were found to be spherical in shape, nearly monodispersed and with an average particle size of 7.8 ± 1.7 nm. Crystalline nature of the nanoparticles in face centered cubic structure is confirmed from the selected‐area electron diffraction and XRD patterns. The nanoparticles were functionalized with various amino-glycosidic antibiotics for utilizing them as drug delivery vehicles. Using Fourier transform infrared spectroscopy, the possible functional groups of antibiotics bound to the nanoparticle surface have been examined. These drug loaded nanoparticle solutions were tested for their antibacterial activity against Gram-negative and Gram-positive bacterial strains, by well diffusion assay. The antibiotic conjugated Au NP exhibited enhanced antibacterial activity, compared to pure antibiotic at the same concentration. Being protein capped and highly stable, these gold nanoparticles can act as effective carriers for drugs and might have considerable applications in the field of infection prevention and therapeutics. - Highlights: ► Method for NaBH 4 reduced and BSA capped gold nanoparticle was standardized. ► Nanoparticles were spherical and nearly monodispersed with a size of 7.8 nm. ► Nanoparticles are extremely stable towards pH modification and electrolyte addition. ► Antibiotic conjugated nanoparticles exhibited enhanced antibacterial activity

Pushing the frontiers of atomic models for protein tertiary structure ...

Indian Academy of Sciences (India)

as an NP complete or NP hard problem.4,5 This notwith- standing, the dire need for tertiary structures of proteins in drug discovery and other areas6–8 has propelled the development of a multitude of computational recipes. In this article, we focus on ab initio/de novo strategies,. Bhageerath in particular, for protein tertiary ...

Animal Migraine Models for Drug Development

DEFF Research Database (Denmark)

Jansen-Olesen, Inger; Tfelt-Hansen, Peer; Olesen, Jes

2013-01-01

Migraine is number seven in WHO's list of all diseases causing disability and the third most costly neurological disorder in Europe. Acute attacks are treatable by highly selective drugs such as the triptans but there is still a huge unmet therapeutic need. Unfortunately, drug development...... for headache has almost come to a standstill partly because of a lack of valid animal models. Here we review previous models with emphasis on optimal characteristics of a future model. In addition to selection of animal species, the method of induction of migraine-like changes and the method of recording...... responses elicited by such measures are crucial. The most naturalistic way of inducing attacks is by infusion of endogenous signaling molecules that are known to cause migraine in patients. The most valid response is recording of neural activity in the trigeminal system. The most useful headache related...

Addressing drug adherence using an operations management model.

Science.gov (United States)

Nunlee, Martin; Bones, Michelle

2014-01-01

OBJECTIVE To provide a model that enables health systems and pharmacy benefit managers to provide medications reliably and test for reliability and validity in the analysis of adherence to drug therapy of chronic disease. SUMMARY The quantifiable model described here can be used in conjunction with behavioral designs of drug adherence assessments. The model identifies variables that can be reproduced and expanded across the management of chronic diseases with drug therapy. By creating a reorder point system for reordering medications, the model uses a methodology commonly seen in operations research. The design includes a safety stock of medication and current supply of medication, which increases the likelihood that patients will have a continuous supply of medications, thereby positively affecting adherence by removing barriers. CONCLUSION This method identifies an adherence model that quantifies variables related to recommendations from health care providers; it can assist health care and service delivery systems in making decisions that influence adherence based on the expected order cycle days and the expected daily quantity of medication administered. This model addresses the possession of medication as a barrier to adherence.

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

Science.gov (United States)

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

An approach to creating a more realistic working model from a protein data bank entry.

Science.gov (United States)

Brandon, Christopher J; Martin, Benjamin P; McGee, Kelly J; Stewart, James J P; Braun-Sand, Sonja B

2015-01-01

An accurate model of three-dimensional protein structure is important in a variety of fields such as structure-based drug design and mechanistic studies of enzymatic reactions. While the entries in the Protein Data Bank ( http://www.pdb.org ) provide valuable information about protein structures, a small fraction of the PDB structures were found to contain anomalies not reported in the PDB file. The semiempirical PM7 method in MOPAC2012 was used for identifying anomalously short hydrogen bonds, C-H⋯O/C-H⋯N interactions, non-bonding close contacts, and unrealistic covalent bond lengths in recently published Protein Data Bank files. It was also used to generate new structures with these faults removed. When the semiempirical models were compared to those of PDB_REDO (http://www.cmbi.ru.nl/pdb_redo/), the clashscores, as defined by MolProbity ( http://molprobity.biochem.duke.edu/), were better in about 50% of the structures. The semiempirical models also had a lower root-mean-square-deviation value in nearly all cases than those from PDB_REDO, indicative of a better conservation of the tertiary structure. Finally, the semiempirical models were found to have lower clashscores than the initial PDB file in all but one case. Because this approach maintains as much of the original tertiary structure as possible while improving anomalous interactions, it should be useful to theoreticians, experimentalists, and crystallographers investigating the structure and function of proteins.

Toward a normalized clinical drug knowledge base in China-applying the RxNorm model to Chinese clinical drugs.

Science.gov (United States)

Wang, Li; Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Dong, Jiancheng; Liu, Yun; Tao, Cui; Jiang, Guoqian; Zhou, Yi; Xu, Hua

2018-04-04

In recent years, electronic health record systems have been widely implemented in China, making clinical data available electronically. However, little effort has been devoted to making drug information exchangeable among these systems. This study aimed to build a Normalized Chinese Clinical Drug (NCCD) knowledge base, by applying and extending the information model of RxNorm to Chinese clinical drugs. Chinese drugs were collected from 4 major resources-China Food and Drug Administration, China Health Insurance Systems, Hospital Pharmacy Systems, and China Pharmacopoeia-for integration and normalization in NCCD. Chemical drugs were normalized using the information model in RxNorm without much change. Chinese patent drugs (i.e., Chinese herbal extracts), however, were represented using an expanded RxNorm model to incorporate the unique characteristics of these drugs. A hybrid approach combining automated natural language processing technologies and manual review by domain experts was then applied to drug attribute extraction, normalization, and further generation of drug names at different specification levels. Lastly, we reported the statistics of NCCD, as well as the evaluation results using several sets of randomly selected Chinese drugs. The current version of NCCD contains 16 976 chemical drugs and 2663 Chinese patent medicines, resulting in 19 639 clinical drugs, 250 267 unique concepts, and 2 602 760 relations. By manual review of 1700 chemical drugs and 250 Chinese patent drugs randomly selected from NCCD (about 10%), we showed that the hybrid approach could achieve an accuracy of 98.60% for drug name extraction and normalization. Using a collection of 500 chemical drugs and 500 Chinese patent drugs from other resources, we showed that NCCD achieved coverages of 97.0% and 90.0% for chemical drugs and Chinese patent drugs, respectively. Evaluation results demonstrated the potential to improve interoperability across various electronic drug systems

Minimum Transendothelial Electrical Resistance Thresholds for the Study of Small and Large Molecule Drug Transport in a Human in Vitro Blood-Brain Barrier Model.

Science.gov (United States)

Mantle, Jennifer L; Min, Lie; Lee, Kelvin H

2016-12-05

A human cell-based in vitro model that can accurately predict drug penetration into the brain as well as metrics to assess these in vitro models are valuable for the development of new therapeutics. Here, human induced pluripotent stem cells (hPSCs) are differentiated into a polarized monolayer that express blood-brain barrier (BBB)-specific proteins and have transendothelial electrical resistance (TEER) values greater than 2500 Ω·cm 2 . By assessing the permeabilities of several known drugs, a benchmarking system to evaluate brain permeability of drugs was established. Furthermore, relationships between TEER and permeability to both small and large molecules were established, demonstrating that different minimum TEER thresholds must be achieved to study the brain transport of these two classes of drugs. This work demonstrates that this hPSC-derived BBB model exhibits an in vivo-like phenotype, and the benchmarks established here are useful for assessing functionality of other in vitro BBB models.

Protein folding simulations: from coarse-grained model to all-atom model.

Science.gov (United States)

Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

2009-06-01

Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL

Drug Elucidation: Invertebrate Genetics Sheds New Light on the Molecular Targets of CNS Drugs

Directory of Open Access Journals (Sweden)

Donard S. Dwyer

2014-07-01

Full Text Available Many important drugs approved to treat common human diseases were discovered by serendipity, without a firm understanding of their modes of action. As a result, the side effects and interactions of these medications are often unpredictable, and there is limited guidance for improving the design of next-generation drugs. Here, we review the innovative use of simple model organisms, especially Caenorhabditis elegans, to gain fresh insights into the complex biological effects of approved CNS medications. Whereas drug discovery involves the identification of new drug targets and lead compounds/biologics, and drug development spans preclinical testing to FDA approval, drug elucidation refers to the process of understanding the mechanisms of action of marketed drugs by studying their novel effects in model organisms. Drug elucidation studies have revealed new pathways affected by antipsychotic drugs, e.g., the insulin signaling pathway, a trace amine receptor and a nicotinic acetylcholine receptor. Similarly, novel targets of antidepressant drugs and lithium have been identified in C. elegans, including lipid-binding/transport proteins and the SGK-1 signaling pathway, respectively. Elucidation of the mode of action of anesthetic agents has shown that anesthesia can involve mitochondrial targets, leak currents and gap junctions. The general approach reviewed in this article has advanced our knowledge about important drugs for CNS disorders and can guide future drug discovery efforts.