Computational studies of HIV-1 integrase inhibition

HIV-1 integrase is an enzyme that catalyzes the insertion of viral DNA into host DNA. Currently it is recognized as an attractive therapeutic target against AIDS. In this study, computational approaches have been employed to study HIV-1 integrase inhibition.; Eleven classes of inhibitors with a variety of structures and biological activities were selected for computational studies. First, cluster analysis assigned inhibitors into two clusters based on numerical descriptors that reflect inhibitor structures. Quantitative structure-activity relationship (QSAR) development was successfully performed for the two clusters separately. These results are consistent with previous studies indicating that more than one binding site might exist. These models were used to search for potential inhibitors through combinatorial chemistry. Several compounds were found to have higher predicted activities compared with known inhibitors.; Molecular Field Analysis (three-dimensional QSAR) was accomplished for the two clusters of inhibitors. Two WFA models were developed with higher predictive capability than those of conventional QSAR and applied to test new compounds found using combinatorial chemistry. Structural alignment of inhibitors from separate clusters found several possible three-point pharmacophores for the two clusters. These pharmacophores resemble pharmacophores previously published based on several individual inhibitor classes.; Eleven representative inhibitors have been selected for docking. The docking results indicate that there are two possible binding regions and structures from the same clusters have the same favorable binding site except for one inhibitor, which has two energetically similar binding sites. The results all support the hypothesis that two binding sites exist.