Computational Studies on HIV-1 Protease Inhibitors:  Influence of Calculated Inhibitor−Enzyme Binding Affinities on the Statistical Quality of 3D-QSAR CoMFA Models

Abstract

A theoretical study was performed on a set of 38 human immunodeficiency type 1 (HIV-1) protease inhibitors that are structurally similar to the AIDS drug Indinavir. Comparison between the computed binding energies and experimental activity data (pIC(50)) found a high degree of correlation (r(2)() = 0.82). Three-dimensional quantitative structure-activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) yielded predicted activities that were in excellent agreement with the corresponding experimentally determined values. Inclusion of the calculated enzyme-inhibitor binding energy as an additional descriptor in the CoMFA model yielded a significant improvement in the internal predictive ability of our model (q(2)() = 0.45 to q(2)() = 0.69). Separate CoMFA models were constructed to evaluate the influence of different alignment schemes (Atom Fit and Field Fit) and different partial atomic charge assignment schemes (Discover CVFF, Gasteiger-Marsili, and AM1-ESP) on the statistical quality of the models.