3D-QSAR CoMFA and CoMSIA studies for design of potent human steroid 5α-reductase inhibitors

Abstract

3D-QSAR studies were performed on a set of sixty-one 6-azasteroidal human steroid 5α-reductase inhibitors. The models developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodologies employing atom and centroid based alignment were reliable and significant having good predictive r 2 value. CoMSIA model developed by a combination of steric, electrostatic, hydrophobic and hydrogen bond donor showed good relative and predictive properties. The predictive power of the models was assessed using an external test set of 10 compounds. The best model had shown cross validation r 2 (0.702) with 7 optimum components, non-cross-validation r 2 (0.956), F value (86.158), predicted r 2 (0.704), standard error of estimate (0.165). Further the CoMFA/CoMSIA contour plots show a preference toward the C-17 substituents and indicate that bulky group at C-17 is an important requirement for exhibiting 5α-reductase inhibition. These developed models could be used to design and optimise the more potent 6-aza steroidal inhibitors of 5α-reductase enzyme. The 3D-QSAR studies involving comparative molecular field analysis and comparative molecular similarity indices analysis on a series of 6-azasteroids as 5α-reductase inhibitors is reported.