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Research ArticleArticle

Three- and Four-Dimensional-Quantitative Structure Activity Relationship (3D/4D-QSAR) Analyses of CYP2C9 Inhibitors

Sean Ekins, Gianpaolo Bravi, Shelly Binkley, Jennifer S. Gillespie, Barbara J. Ring, James H. Wikel and Steven A Wrighton
Drug Metabolism and Disposition August 2000, 28 (8) 994-1002;
Sean Ekins
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Gianpaolo Bravi
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Shelly Binkley
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Jennifer S. Gillespie
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Barbara J. Ring
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James H. Wikel
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Steven A Wrighton
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Abstract

The interaction of competitive type inhibitors with the active site of cytochrome P450 (CYP) 2C9 has been predicted using three- and four-dimensional quantitative structure activity relationship (3D-/4D-QSAR) models constructed using previously unreported and literature-derived data. 3D-QSAR pharmacophore models of the common structural features of CYP2C9 inhibitors were built using the program Catalyst and compared with 3D- and 4D-QSAR partial least-squares models, which use molecular surface-weighted holistic invariant molecular descriptors of the size and shape of inhibitors. The Catalyst models generated from multiple conformers of competitive inhibitors of CYP2C9 activities contained at least one hydrophobic and two hydrogen bond acceptor/donor regions. Catalyst model 1 was constructed with Ki(apparent) values for inhibitors of tolbutamide and diclofenac 4′-hydroxylation (n = 9). Catalyst model 2 was generated from literature Ki(apparent) values for (S)-warfarin 7-hydroxylation (n = 29), and Catalyst model 3 from literature IC50 values for tolbutamide 4-hydroxylation (n = 13). These three models illustrated correlation values of observed and predicted inhibition for CYP2C9 of r = 0.91, 0.89, and 0.71, respectively. Catalyst pharmacophores generated withKi(apparent) values were validated by predicting the Ki(apparent) value of a test set of CYP2C9 inhibitors also derived from the literature (n = 14). Twelve of fourteen of theseKi(apparent) values were predicted to be within 1 log residual of the observed value using Catalyst model 1, whereas Catalyst model 2 predicted 10 of 14Ki(apparent) values. The corresponding partial least-squares molecular surface-weighted holistic invariant molecular 3D- and 4D-QSAR models for all CYP2C9 data sets yielded predictable models as assessed using cross-validation. These 3D- and 4D-QSAR models of CYP inhibition will aid in future prediction of drug-drug interactions.

Footnotes

  • Send reprint requests to: Sean Ekins, Ph.D., Department of Drug Disposition, Lilly Research Laboratories, Eli Lilly and Co., Lilly Corporate Center, Drop Code 0730, Indianapolis, IN 46285. E-mail:ekins_sean{at}lilly.com

  • ↵1 Present address: Glaxo Wellcome Research and Development, Medicines Research Center, Gunnels Wood Road, Stevenage, Hertfordshire, SG1 2NY, UK.

  • Abbreviations used are::
    CYP
    cytochrome P450
    CoMFA
    comparative molecular field analysis
    3D-QSAR
    3 dimensional-quantitative structure activity relationship
    4D-QSAR
    4 dimensional-quantitative structure activity relationship
    LOO
    leave one out
    MS-WHIM
    molecular surface-weighted holistic invariant molecular
    PLS
    partial least squares
    5RG×100
    five random groups repeated up to 100 times
    • Received January 31, 2000.
    • Accepted May 9, 2000.
  • The American Society for Pharmacology and Experimental Therapeutics
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Drug Metabolism and Disposition: 28 (8)
Drug Metabolism and Disposition
Vol. 28, Issue 8
1 Aug 2000
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Research ArticleArticle

Three- and Four-Dimensional-Quantitative Structure Activity Relationship (3D/4D-QSAR) Analyses of CYP2C9 Inhibitors

Sean Ekins, Gianpaolo Bravi, Shelly Binkley, Jennifer S. Gillespie, Barbara J. Ring, James H. Wikel and Steven A Wrighton
Drug Metabolism and Disposition August 1, 2000, 28 (8) 994-1002;

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Research ArticleArticle

Three- and Four-Dimensional-Quantitative Structure Activity Relationship (3D/4D-QSAR) Analyses of CYP2C9 Inhibitors

Sean Ekins, Gianpaolo Bravi, Shelly Binkley, Jennifer S. Gillespie, Barbara J. Ring, James H. Wikel and Steven A Wrighton
Drug Metabolism and Disposition August 1, 2000, 28 (8) 994-1002;
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