Abstract

Background: Glycoprotein120 (GP120) is an emerging target nowadays to design novel human immunodeficiency virus-1 (HIV-1) entry inhibitors. It plays a crucial role in the first stage of viral attachment through binding to CD4 receptors of host cell but currently there is no approved drug in the market targeting this HIV-1 GP120. Thus, there is an urge of novel lead molecules as GP120-CD4 binding inhibitors.

Methods: To design such novel molecules, 3D-QSAR studies were performed on a series of 48 reported indole glyoxamide derivatives using two different alignment methods. Best significant CoMFA and CoMSIA models were obtained using 35 molecules in training set by distill alignment.

Results: CoMFA model gave 0.698 cross-validated coefficient (q2) and 0.921 conventional coefficient (r2) while CoMSIA outperformed with 0.732 q2 and 0.946 r2. Validation of both the models using 13 molecules test set resulted in satisfactory predicted correlation coefficient (r2 pred) values of 0.625 and 0.761 for CoMFA and CoMSIA, respectively.

Conclusion: Interpretation of CoMFA and CoMSIA contour maps along with the docking results of all 48 compounds into a Phe43 cavity of GP120 revealed many helpful structural insights to improve the activity of newly designed indole glyoxamide derivatives as GP120-CD4 inhibitors for the treatment of HIV-1 infection.

Keywords: CoMFA, CoMSIA, Molecular Docking, 3D-QSAR, HIV-1, GP120.

Graphical Abstract