3D QSAR pharmacophore based virtual screening and molecular docking for identification of potential HSP90 inhibitors

Abstract

Chemical features based 3D pharmacophore models were developed for HSP90 based on the known inhibitors using Discovery Studio V2.1. An optimal pharmacophore model was brought forth and validated using a decoy set, external test set and Fischer's randomization method. The best five features pharmacophore model, Hypo1, includes two hydrogen bond acceptors, three hydrophobic features, which has the highest correlation coefficient (0.93), cost difference (73.88), low RMS (1.24), as well as it shows a high goodness of fit and enrichment factor. Hypo1 was used as a 3D query for virtual screening to retrieve potential inhibitors from Maybridge and Scaffold databases. The hit compounds were subsequently subjected to molecular docking studies and finally, 36 compounds were obtained based on consensus scoring function.