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Computational Methods and Tools to Predict Cytochrome P450 Metabolism for Drug Discovery.

07:00 EST 24th November 2018 | BioPortfolio

Summary of "Computational Methods and Tools to Predict Cytochrome P450 Metabolism for Drug Discovery."

In this review we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, including CYP substrate and inhibitor predictors, site of metabolism predictors (i.e. metabolically labile sites within potential substrates) and metabolite structure predictors. We summarise the different approaches taken by these models, such as rule-based methods, machine learning, data mining, quantum chemical methods, molecular interaction fields and docking. We highlight the scope and limitations of each method and discuss future implications for the field of metabolism prediction in drug discovery. This article is protected by copyright. All rights reserved.

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This article was published in the following journal.

Name: Chemical biology & drug design
ISSN: 1747-0285
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