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In silico methods to predict drug toxicity
Current Opinion in Pharmacology, 2013This review describes in silico methods to characterize the toxicity of pharmaceuticals, including tools which predict toxicity endpoints such as genotoxicity or organ-specific models, tools addressing ADME processes, and methods focusing on protein-ligand docking binding. These in silico tools are rapidly evolving.
Alessandra, Roncaglioni +3 more
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In silico Prediction of Chemical Ames Mutagenicity
Journal of Chemical Information and Modeling, 2012Mutagenicity is one of the most important end points of toxicity. Due to high cost and laboriousness in experimental tests, it is necessary to develop robust in silico methods to predict chemical mutagenicity. In this paper, a comprehensive database containing 7617 diverse compounds, including 4252 mutagens and 3365 nonmutagens, was constructed. On the
Congying, Xu +7 more
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Overcoming drug resistance through in silico prediction
Drug Discovery Today: Technologies, 2014Prediction tools are commonly used in pre-clinical research to assist target selection, to optimize drug potency or to predict the pharmacological profile of drug candidates. In silico prediction and overcoming drug resistance is a new opportunity that creates a high interest in pharmaceutical research.
Pablo Carbonell, Jean-Yves Trosset
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In Silico Prediction of hERG Inhibition
Future Medicinal Chemistry, 2015The voltage-gated potassium channel encoded by hERG carries a delayed rectifying potassium current (IKr) underlying repolarization of the cardiac action potential. Pharmacological blockade of the hERG channel results in slowed repolarization and therefore prolongation of action potential duration and an increase in the QT interval as measured on an ...
Yankang, Jing +4 more
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Advances in In-silico B-cell Epitope Prediction
Current Topics in Medicinal Chemistry, 2019Identification of B-cell epitopes in target antigens is one of the most crucial steps for epitopebased vaccine development, immunodiagnostic tests, antibody production, and disease diagnosis and therapy. Experimental methods for B-cell epitope mapping are time consuming, costly and labor intensive; in the meantime, various in-silico methods are ...
Pingping, Sun +5 more
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Towards in silico prediction of immunogenic epitopes
Trends in Immunology, 2003As torrents of new data now emerge from microbial genomics, bioinformatic prediction of immunogenic epitopes remains challenging but vital. In silico methods often produce paradoxically inconsistent results: good prediction rates on certain test sets but not others.
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Predicting Passive Transport In Silico - History, Hype, Hope
Current Topics in Medicinal Chemistry, 2003The development of computational tools for the prediction of passive transport is reviewed with particular reference to four diverse approaches: the rule-of-5, polar surface area, Volsurf and Abraham's General Solvation Equation. To illustrate the current state of the art, several examples of the application of in silico methods in drug design projects
Clark, D., Grootenhuis, P.D.J.
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In Silico Prediction of Post-translational Modifications
2011Methods for predicting protein post-translational modifications have been developed extensively. In this chapter, we review major post-translational modification prediction strategies, with a particular focus on statistical and machine learning approaches.
Chunmei, Liu, Hui, Li
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In silicoprediction of aqueous solubility
Expert Opinion on Drug Discovery, 2006The fundamentals of aqueous solubility, and the factors that affect it, are briefly outlined, followed by a short introduction to quantitative structure-property relationships. Early (pre-1990) work on aqueous solubility prediction is summarised, and a more detailed presentation and critical discussion are given of the results of most, if not all, of ...
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In Silico Prediction of Target-Inhibitor Interaction
2015For a long time people are trying to predict interactions of molecules. The base for this is always a 3D structure of both partners. Based on the increasing numbers of X-Ray structures of proteins with and without bounded molecules algorithms were developed to predict the target-inhibitor interaction based on known structures of proteins.
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