Literature DB >> 19243088

CypScore: Quantitative prediction of reactivity toward cytochromes P450 based on semiempirical molecular orbital theory.

Matthias Hennemann1, Arno Friedl, Mario Lobell, Jörg Keldenich, Alexander Hillisch, Timothy Clark, Andreas H Göller.   

Abstract

CypScore is an in silico approach for predicting the likely sites of cytochrome P450-mediated metabolism of druglike organic molecules. It consists of multiple models for the most important P450 oxidation reactions such as aliphatic hydroxylation, N-dealkylation, O-dealkylation, aromatic hydroxylation, double-bond oxidation, N-oxidation, and S-oxidation. Each of these models is based on atomic reactivity descriptors derived from surface-based properties calculated with ParaSurf and based on AM1 semiempirical molecular orbital theory. The models were trained with data derived from Bayer Schering Pharma's in-house MajorMetabolite Database with more than 2300 transformations and more than 800 molecules collected from the primary literature. The models have been balanced to allow the treatment of relative intramolecular, intra-chemotype, and inter-chemotype reactivities of the labile sites toward oxidation. The models were evaluated with promising hit rates on three public datasets of varying quality in the annotation of the experimental positions. For 39 well-characterized compounds from 14 in-house lead optimization programs, we could detect at least one major metabolite for the three highest-ranked positions in 87 % of the compounds and overall more than 62 % of all major metabolites, with promising true- to false-positive ratios of 0.9.

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Year:  2009        PMID: 19243088     DOI: 10.1002/cmdc.200800384

Source DB:  PubMed          Journal:  ChemMedChem        ISSN: 1860-7179            Impact factor:   3.466


  18 in total

1.  The local electron affinity for non-minimal basis sets.

Authors:  Timothy Clark
Journal:  J Mol Model       Date:  2010-01-10       Impact factor: 1.810

2.  Predicting drug metabolism by CYP1A1, CYP1A2, and CYP1B1: insights from MetaSite, molecular docking and quantum chemical calculations.

Authors:  Preeti Pragyan; Siddharth S Kesharwani; Prajwal P Nandekar; Vijay Rathod; Abhay T Sangamwar
Journal:  Mol Divers       Date:  2014-07-16       Impact factor: 2.943

3.  CYP isoform specificity toward drug metabolism: analysis using common feature hypothesis.

Authors:  M Ramesh; Prasad V Bharatam
Journal:  J Mol Model       Date:  2011-05-12       Impact factor: 1.810

Review 4.  Predicting drug metabolism: experiment and/or computation?

Authors:  Johannes Kirchmair; Andreas H Göller; Dieter Lang; Jens Kunze; Bernard Testa; Ian D Wilson; Robert C Glen; Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2015-04-24       Impact factor: 84.694

5.  Industrial applications of in silico ADMET.

Authors:  Bernd Beck; Tim Geppert
Journal:  J Mol Model       Date:  2014-06-28       Impact factor: 1.810

6.  The unrestricted local properties: application in nanoelectronics and for predicting radicals reactivity.

Authors:  Pavlo O Dral
Journal:  J Mol Model       Date:  2014-02-16       Impact factor: 1.810

7.  SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism.

Authors:  Patrik Rydberg; David E Gloriam; Jed Zaretzki; Curt Breneman; Lars Olsen
Journal:  ACS Med Chem Lett       Date:  2010-03-15       Impact factor: 4.345

8.  Potentially increasing the metabolic stability of drug candidates via computational site of metabolism prediction by CYP2C9: The utility of incorporating protein flexibility via an ensemble of structures.

Authors:  Matthew L Danielson; Prashant V Desai; Michael A Mohutsky; Steven A Wrighton; Markus A Lill
Journal:  Eur J Med Chem       Date:  2011-06-23       Impact factor: 6.514

9.  RS-Predictor models augmented with SMARTCyp reactivities: robust metabolic regioselectivity predictions for nine CYP isozymes.

Authors:  Jed Zaretzki; Patrik Rydberg; Charles Bergeron; Kristin P Bennett; Lars Olsen; Curt M Breneman
Journal:  J Chem Inf Model       Date:  2012-05-29       Impact factor: 4.956

Review 10.  Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Authors:  Johannes Kirchmair; Mark J Williamson; Jonathan D Tyzack; Lu Tan; Peter J Bond; Andreas Bender; Robert C Glen
Journal:  J Chem Inf Model       Date:  2012-02-17       Impact factor: 4.956

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