4D-QSAR Models of HOE/BAY-793 Analogues as HIV-1 Protease Inhibitors

Abstract

HIV-1 protease is a homodimer composed of monomer subunits, each containing 99 amino acids with a single catalytic Asp residue. Four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis was applied to a series of 32 C 2 -symmetric diol inhibitors of HIV-1 protease. The 4D-QSAR approach can be applied to both receptor-dependent (RD) and receptor-independent (RI) problems. In the first scheme, the geometry of the receptor (molecular target, usually an enzyme) is available. By contrast, in the second scheme, the geometry of the receptor is not available or is not included in the data necessary to the analysis. Twenty-eight compounds belong to the training set, and four to the test set, which was used for external validation. These compounds are analogues of inhibitor HOE/ BAY-793, important for its outstanding potency in vitro and, especially, in HIV-1 infected cell culture. Five thousand conformations of each analogue were sampled by molecular dynamic simulation for 50 ps at a constant temperature of 300 K. For each of the three trial alignments, each conformation was placed in a 2 grid cell lattice. Optimized 4D-QSAR models were constructed by genetic algorithm (GA) optimization and partial least squares (PLS) fitting, and evaluated by the leave-one-out cross-validation method. The models developed in this analysis suggest that alignment 3 yields the best results, both statistically and qualitatively. The 4D-QSAR models developed in this study suggest novel molecular regions to be explored in the search for better anti-HIV agents to inhibit HIV-1 protease.

Synthesis, Biological Evaluation, and Molecular Simulation of Chalcones and Aurones as Selective MAO‐B Inhibitors

“…During decades, computational methodologies such as quantitative structure–activity relationships (QSAR) or molecular modeling (MM) have been useful tools to advance in the understanding of drug–receptor interactions . In the present work, 3D‐QSAR and docking evaluations were used to rationalize both the experimental results and the structural requirements necessary to design new ligands.…”