Three-dimensional quantitative structure-activity relationship study on cyclic urea derivatives as HIV-1 protease inhibitors: Application of comparative molecular field analysis

Three-dimensional quantitative structure-activity relationship (3D-QSAR) mo dels have been developed using comparative molecular field analysis (CoMFA) on a large data set (118 compounds) of diverse cyclic urea derivatives as protease inhibitors against the human immunodeficiency virus type 1 (HIV-1) . X-ray crystal structures of HIV-1 protease bound with this class of inhib itors were used to derive the most probable bioactive conformations of the inhibitors. The enzyme active site was used as a constraint to limit the nu mber of possible conformations that are sterically accessible. The test set s have been created keeping in mind structural diversity as well as the uni form simple statistical criteria (mean, standard deviation, high and low va lues) of the protease inhibitory activities of the molecules compared to th e training sets. Multiple predictive models have been developed with the tr aining sets (93 compounds in each set) and validated with the corresponding test sets (25 compounds in each set). All the models yielded high predicti ve correlation coefficients (q(2) from 0.699 to 0.727), substantially high fitted correlation coefficients (r(2) from 0.965 to 0.973), and reasonably low standard errors of estimates (S from 0.239 to 0.265). The steric and el ectrostatic effects have approximately equal contributions, 45% and 55% (ap proximately), respectively, toward explaining protease inhibitory activitie s. This analysis yielded models with significant information on steric and electrostatic interactions clearly discerned by the respective coefficient contour plots when overlapped on the X-ray structure of the HIV-1 protease. The HINT CoMFA study revealed significant contribution of hydrophobicity t oward protease inhibitory activity. The 3D visualization technique utilizin g these contour plots as well as the receptor site geometry may significant ly improve our understanding of the inhibitor-protease (HIV-1) interactions and help in designing compounds with improved activity.