Literature DB >> 23797035

In silico methods to predict drug toxicity.

Alessandra Roncaglioni1, Andrey A Toropov, Alla P Toropova, Emilio Benfenati.   

Abstract

This 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. Nowadays, the interest has shifted from classical studies to support toxicity screening of candidates, toward the use of in silico methods to support the expert. These methods, previously considered useful only to provide a rough, initial estimation, currently have attracted interest as they can assist the expert in investigating toxic potential. They provide the expert with safety perspectives and insights within a weight-of-evidence strategy. This represents a shift of the general philosophy of in silico methodology, and it is likely to further evolve especially exploiting links with system biology.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23797035     DOI: 10.1016/j.coph.2013.06.001

Source DB:  PubMed          Journal:  Curr Opin Pharmacol        ISSN: 1471-4892            Impact factor:   5.547


  13 in total

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Review 3.  Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes.

Authors:  Hannu Raunio; Mira Kuusisto; Risto O Juvonen; Olli T Pentikäinen
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Journal:  J Cheminform       Date:  2017-05-04       Impact factor: 5.514

Review 5.  Three-dimensional bio-printing: A new frontier in oncology research.

Authors:  Nitin Charbe; Paul A McCarron; Murtaza M Tambuwala
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Journal:  Molecules       Date:  2017-07-26       Impact factor: 4.411

7.  In Silico Predictions of Endocrine Disruptors Properties.

Authors:  Melanie Schneider; Jean-Luc Pons; Gilles Labesse; William Bourguet
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8.  High throughput screening against pantothenate synthetase identifies amide inhibitors against Mycobacterium tuberculosis and Staphylococcus aureus.

Authors:  Sayantan Pradhan; Chittaranjan Sinha
Journal:  In Silico Pharmacol       Date:  2018-05-08

Review 9.  In silico toxicology: computational methods for the prediction of chemical toxicity.

Authors:  Arwa B Raies; Vladimir B Bajic
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2016-01-06

10.  Molecular Connectivity Predefines Polypharmacology: Aliphatic Rings, Chirality, and sp3 Centers Enhance Target Selectivity.

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Journal:  Front Pharmacol       Date:  2017-08-28       Impact factor: 5.810

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