Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by P450s

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DOIResolve DOI: http://doi.org/10.1021/ci3003073
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TypeArticle
Journal titleJournal of Chemical Information and Modeling
ISSN1549-9596
1549-960X
Volume52
Issue9
Pages24712483; # of pages: 13
AbstractThe metabolism of xenobiotics—and more specifically drugs—in the liver is a critical process controlling their half-life. Although there exist experimental methods, which measure the metabolic stability of xenobiotics and identify their metabolites, developing higher throughput predictive methods is an avenue of research. It is expected that predicting the chemical nature of the metabolites would be an asset for designing safer drugs and/or drugs with modulated half-lives. We have developed IMPACTS (In-silico Metabolism Prediction by Activated Cytochromes and Transition States), a computational tool combining docking to metabolic enzymes, transition state modeling, and rule-based substrate reactivity prediction to predict the site of metabolism (SoM) of xenobiotics. Its application to sets of CYP1A2, CYP2C9, CYP2D6, and CYP3A4 substrates and comparison to experts’ predictions demonstrates its accuracy and significance. IMPACTS identified an experimentally observed SoM in the top 2 predicted sites for 77% of the substrates, while the accuracy of biotransformation experts’ prediction was 65%. Application of IMPACTS to external sets and comparison of its accuracy to those of eleven other methods further validated the method implemented in IMPACTS.
Publication date
LanguageEnglish
Peer reviewedYes
NRC publication
This is a non-NRC publication

"Non-NRC publications" are publications authored by NRC employees prior to their employment by NRC.

NPARC number21269047
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Record identifierb6ce2f37-96b1-4ee7-8f80-15e7f43d1833
Record created2013-12-03
Record modified2016-05-09
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