QSAR and docking studies of coumarin derivatives as potent HIV-1 integrase inhibitors

Abstract Human immunodeficiency virus integrase (HIV-1IN) is an emerging and potential drug target for anti-HIV therapy. It is an enzyme essential for 3′ processing and integration step in the life cycle of HIV. In the present study a series of coumarin derivatives (containing 26 compounds) as HIV-1IN inhibitors was subjected to quantitative structure–activity relationship (QSAR) analysis. For building the regression models two different variable selection approaches namely, genetic function approximation (GFA) and sequential multiple linear regression (SQ-MLR) were used and compared to predict the HIV-1IN inhibition activity. Based on prediction, the best validation model for 3′ processing inhibition activity with squared correlation coefficient ( r 2 ) = 0.8965, cross validated correlation coefficient ( Q 2 ) = 0.8307 and external prediction ability pred_r 2  = 0.5400 showed that Henry’s law Constant (HLC), Partition Coefficient (PC) and Dipole moment-Z component (D3) were the positive contributors, whereas for integration inhibition activity, parameters r 2  = 0.8904, Q 2  = 0.8174 and pred_r 2  = 0.7159 showed HLC, Logarithm of Partition Coefficient (Log  P ) and Dipole moment-Y component (D2) contributed positively to the activity. The binding mode pattern of the compounds to the binding site of integrase enzyme was confirmed by docking studies. The results of the present study may be useful for designing more potent HIV-1IN inhibitors.