"Discovery and Optimization of Coumarin Derivatives as HIV-1 Reverse Transcriptase Inhibitors: A Comprehensive QSAR, Molecular Docking, and ADMET Study"

Abstract

This study presents comprehensive Two-Dimensional (2D) and Three-Dimensional (3D) Quantitative Structure–Activity Relationship (QSAR) analyses to investigate the chemical composition of coumarin analogues and their effectiveness as anti-HIV agents. The analysis utilized Partial Least Squares Regression (PLSR) analysis for 2D QSAR modeling and k Nearest Neighbor Molecular Field Analysis (kNN MFA) for 3D QSAR modeling, incorporating simulated annealing variable selection for model refinement. Subsequently, New Chemical Entities (NCEs) were strategically designed based on the insights gleaned from the QSAR studies. The designed NCEs were then subjected to detailed investigation through molecular docking studies to evaluate their binding affinities with the Reverse Transcriptase enzyme, a key target in HIV treatment. Additionally, the Absorption, Distribution, Metabolism, and Excretion (ADME) properties of these designed compounds were predicted to assess their pharmacokinetic profiles. This integrated approach not only sheds light on the structural features essential for potent anti-HIV activity but also contributes to the rational design of novel Coumarin derivatives with improved therapeutic potential.