PT - JOURNAL ARTICLE AU - Sean Ekins AU - Gianpaolo Bravi AU - Shelly Binkley AU - Jennifer S. Gillespie AU - Barbara J. Ring AU - James H. Wikel AU - Steven A Wrighton TI - Three- and Four-Dimensional-Quantitative Structure Activity Relationship (3D/4D-QSAR) Analyses of CYP2C9 Inhibitors DP - 2000 Aug 01 TA - Drug Metabolism and Disposition PG - 994--1002 VI - 28 IP - 8 4099 - http://dmd.aspetjournals.org/content/28/8/994.short 4100 - http://dmd.aspetjournals.org/content/28/8/994.full SO - Drug Metab Dispos2000 Aug 01; 28 AB - 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. The American Society for Pharmacology and Experimental Therapeutics