Three- and four-dimensional quantitative structure activity relationship analyses of cytochrome P-450 3A4 inhibitors

The program Catalyst was used to build three-dimensional quantitative struc ture activity relationship (3D-QSAR) pharmacophore models of the structural features common to competitive-type inhibitors of cytochrome P-450 (CYP) 3 A4. These were compared with 3D- and four-dimensional (4D)-QSAR partial lea st-squares (PLS) models built using molecular surface-weighted holistic inv ariant molecular (MS-WHIM) descriptors for size and shape of the inhibitor. The Catalyst pharmacophore model generated from multiple conformers of com petitive inhibitors of GYP3A4-mediated midazolam 1'-hydroxylation (n = 14) yielded a high correlation of observed and predicted Ki values of r = 0.91. Similarly, PLS MS-WHIM was used to produce 3D- and 4D-QSARs for this data set and produced models that were statistically predictable after cross-val idation. Two additional Catalyst pharmacophores were constructed from liter ature K-1, values (n = 32) derived from the inhibition of CYP3A-mediated cy closporin A metabolism and C-50 data (n = 22) from the inhibition of CYP3A4 -mediated quinine 3-hydroxylation. These Catalyst pharmacophores illustrate d correlations of observed and predicted inhibition for CYP3A4 of r = 0.77 and 0.92, respectively, The corresponding 4D-QSARs generated by PLS MS-WHIM for these data sets were of comparable quality as judged by cross-validati on. Both K-1 pharmacophores generated with Catalyst were also validated by predicting the K-i(apparent) Values of a test set of eight GYP3A4 inhibitor s not included rn either model. In seven of eight cases, the residuals of t he predicted K-i(apparent) Values were within 1 log unit of the observed va lues. The 3D- and 4D-QSAR models produced in this study suggest the utility of future in silico prediction of CYP3A4-mediated drug-drug interactions.