A refined 3-dimensional QSAR of cytochrome P4502C9: Computational predictions of drug interactions

A ligand-based model is reported that predicts the K-i values for cytochrom e P450 2C9 (CYP2C9) inhibitors. This CoMFA model was used to predict the af finity of 14 structurally diverse compounds not in the training set and app ears to be robust. The mean error of the predictions is 6 mu M. The experim entally measured K-i values of the 14 compounds range from 0.1 to 48 mu M. Leave-one-out cross-validated partial least-squares gives a q(2) value of b etween 0.6 and 0.8 for the various models which indicates internal consiste ncy. Random assignment of biological data to structure leads to negative q( 2) values. These models are useful in that they establish a pharmacophore f or binding to CYP2C9 that can be tested with site-directed mutagenesis. The se models can also be used to screen for potential drug interactions and to design compounds that will not bind Do this enzyme with high affinity.