3D-QSAR analysis of human immunodeficiency virus entry-1 inhibitors by CoMFA and CoMSIA

Abstract

3D-QSAR studies namely CoMFA, CoMFA region focusing and CoMSIA have been carried out on a series (36 compounds) of HIV-1 entry inhibitors. An alignment rule for the compounds was defined using Distill in SYBYL 7.3. Models were validated using a data set obtained by dividing the data set into a training set and test set using hierarchical clustering, based on the CoMFA fields and biological activities ( pIC 50). The best predictions were obtained with a CoMFA region-focusing model (q 2 = 0.719, r pred 2 = 0.911), CoMFA standard model (q 2 = 0.660, r pred 2 = 0.890), and CoMSIA (steric and hydrophobic) model (q 2 = 0.521, r pred 2 = 0.794). The statistical parameters from the models indicate that the data are well fitted and have high predictive ability. Moreover, the resulting 3D CoMFA/CoMSIA contour maps provide useful guidance for designing highly active inhibitors.