Literature DB >> 12672233

A model for predicting likely sites of CYP3A4-mediated metabolism on drug-like molecules.

Suresh B Singh1, Lucy Q Shen, Matthew J Walker, Robert P Sheridan.   

Abstract

We have developed a rapid semiquantitative model for evaluating the relative susceptibilities of different sites on drug molecules to metabolism by cytochrome P450 3A4. The model is based on the energy necessary to remove a hydrogen radical from each site, plus the surface area exposure of the hydrogen atom. The energy of hydrogen radical abstraction is conventionally measured by AM1 semiempirical molecular orbital calculations. AM1 calculations show the following order of radical stabilities for the hydrogen atom abstractions: sp2 centers > heteroatom sp3 centers > carbon sp3 centers. Since AM1 calculations are too time intensive for routine work, we developed a statistical trend vector model, which is used to estimate the AM1 abstraction energy of a hydrogen atom from its local atomic environment. We carried out AM1 and trend vector calculations on 50 CYP3A4 substrates whose major sites of metabolism are known in the literature. A plot of the lowest hydrogen radical formation energy versus its sterically accessible surface area exposure for these 50 substrates shows that only those hydrogen atoms with solvent accessible surface area exposure > or = 8.0 A(2) are susceptible to CYP3A4-mediated metabolism. This approach forms the basis for our general model, which predicts sites on drugs that are susceptible to cytochrome P450 3A4-mediated hydrogen radical abstraction followed by a hydroxylation reaction. This model, in conjunction with specific enzyme site binding requirements, can aid in identifying possible sites of metabolism catalyzed by other cytochrome P450 enzymes.

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Year:  2003        PMID: 12672233     DOI: 10.1021/jm020400s

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  22 in total

1.  Empirical regioselectivity models for human cytochromes P450 3A4, 2D6, and 2C9.

Authors:  Robert P Sheridan; Kenneth R Korzekwa; Rhonda A Torres; Matthew J Walker
Journal:  J Med Chem       Date:  2007-06-19       Impact factor: 7.446

Review 2.  Modeling kinetics of subcellular disposition of chemicals.

Authors:  Stefan Balaz
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Review 3.  Computational methods in drug discovery.

Authors:  Gregory Sliwoski; Sandeepkumar Kothiwale; Jens Meiler; Edward W Lowe
Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

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

Review 5.  Current Approaches for Investigating and Predicting Cytochrome P450 3A4-Ligand Interactions.

Authors:  Irina F Sevrioukova; Thomas L Poulos
Journal:  Adv Exp Med Biol       Date:  2015       Impact factor: 2.622

Review 6.  Scaffold-hopping as a strategy to address metabolic liabilities of aromatic compounds.

Authors:  Phillip R Lazzara; Terry W Moore
Journal:  RSC Med Chem       Date:  2019-12-16

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.  IDSite: An accurate approach to predict P450-mediated drug metabolism.

Authors:  Jianing Li; Severin T Schneebeli; Joseph Bylund; Ramy Farid; Richard A Friesner
Journal:  J Chem Theory Comput       Date:  2011-11-08       Impact factor: 6.006

9.  A simple model predicts UGT-mediated metabolism.

Authors:  Na Le Dang; Tyler B Hughes; Varun Krishnamurthy; S Joshua Swamidass
Journal:  Bioinformatics       Date:  2016-06-20       Impact factor: 6.937

10.  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

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