Abstract

Using in vitro data, we previously built Catalyst 3-dimensional quantitative structure activity relationship (3D-QSAR) models that qualitatively rank and predict IC₅₀ values for P-glycoprotein (P-gp) inhibitors. These models were derived and tested with data for inhibition of digoxin transport, calcein accumulation, vinblastine accumulation, and vinblastine binding. In the present study, 16 inhibitors of verapamil binding to P-gp were predicted using these models. These inhibition results were then used to generate a new pharmacophore that consisted of one hydrogen bond acceptor, one ring aromatic feature, and two hydrophobes. This model predicted the rank order of the four data sets described previously and correctly ranked the inhibitory potency of a further four verapamil metabolites identified in the literature. The degree of similarity in rank ordering prediction by these inhibitor pharmacophore models generated to date confirms a likely overlap in the sites to which the three P-gp substrates used in these studies (verapamil, vinblastine, and digoxin) bind. Alignment of the three substrate probes indicated that they are likely to bind the same or overlapping sites within P-gp. Important features on these substrates include multiple hydrophobic and hydrogen bond acceptor features, which are widely dispersed and in agreement among most of the five inhibitor pharmacophores we have described so far. These 3D-QSAR models will be useful for future prediction of likely substrates and inhibitors of P-gp.