A Mechanism-based 3D-QSAR and DFT Approach for the Prediction of H5N1 Entry Inhibitory Potency of 3-O-β-chacotriosyl Ursolic Acid Derivatives

In this work, 25 3-O-β-chacotriosyl ursolic acid derivatives were employed to achieve the highly reliable and predictive 3 D-QSAR models by Co MFA and Co MSIA methods, respectively. The predictive capabilities of two constructed CoMFA and CoMSIA models were verified by the leave-one-out cross-validation method. The results showed that the cross-validated coefficient(q2) and non-cross-validated coefficient(R2) were 0.559, 0.981 in the CoMFA model and 0.696, 0.978 in the CoM SIA model, respectively, which suggests that these two models are robust and have good exterior predictive capabilities. Furthermore, based on the contour maps information of two models, ten novel inhibitors with higher inhibitory potency were designed, and the quantum chemical calculation of density functional theory(DFT) was performed to investigate the mechanism why the designed molecules have stronger inhibitory activity than the lead compound. The calculations show that the C-50 position of lead compound is a key active site for the enhancement of inhibitory activity, and it should be introduced into the large electron withdrawing group, which would result in generating potent and selective H5 N1 entry inhibitors. We expect that the results in this paper could provide important information to develop new potent H5 N1 entry inhibitors.