Optimizing Targeted Inhibitors of P-Glycoprotein Using Computational and Structure-Guided Approaches.

Overexpression of ABC transporters like P-glycoprotein (P-gp) has been correlated with resistances in cancer chemotherapy. Intensive efforts to identify P-gp inhibitors for use in combination therapy have not led to clinically approved inhibitors to date. Here, we describe computational approaches combined with structure-based design to improve the characteristics of a P-gp inhibitor previously identified by us. This hit compound represents a novel class of P-gp inhibitors that specifically targets and inhibits P-gp ATP hydrolysis while not being transported by the pump. We describe here a new program for virtual chemical synthesis and computational assessment, ChemGen, to produce hit compound variants with improved binding characteristics. The chemical syntheses of several variants, efficacy in reversing multidrug resistance in cell culture, and biochemical assessment of the inhibition mechanism are described. The usefulness of the computational predictions of binding characteristics of the inhibitor variants is discussed and compared to more traditional structure-based approaches.