The 3D-QSAR Study, Molecular Docking, and ADMET Analysis of Darunavir Derivatives of HIV-1 Protease Inhibitors - Fang, Rui-Jing; Zhang, Yan-Jun; Wang, Wei-Xian; Wu, Tian-Le; Zhang, Shuai-Jun; He, Yi-Yang; Xiong, Fei; Wang, Zhong-Hua (Letters in Drug Design & Discovery, 2024)
BackgroundAcquired Immunodeficiency Syndrome (AIDS) is one of most prevalent infectious diseases in the world, and HIV-1 protease (PR) is a vital target of drug design. Nowadays, three-dimensional quantitative structure-activity relationships (3D-QSAR) are applied to help design new protease inhibitions (PIs).ObjectiveThe primary objective of this study is to apply the 3D-QSAR study to a series of 42 derivatives of Darunavir (DRV) and to design new molecules possessing high antivirus activity.MethodsPartial Least Squares (PLS) were used to cross-validate the dataset of compounds, and the optimal number of principal components (ONC), cross-validate coefficient (q2), standard error of estimate (SEE), non-cross-validated correlation coefficient (R2) and fisher test value (F) were calculated to assess model robustness. In this study, the CoMSIA-DAH model (q2=0.754, r2= 0.988, rpred2=0.57) possessed the highest predicted activity. Newly designed molecules were analyzed by docking studies with compound 25 taken as a template.ResultsWithin eight newly designed drugs, compound N02 possessed the highest antivirus activity (IC50=0.00461 nM) predicted by the CoMSIA-DAH model. The Surflex-Dock module of SYBYL-X 2.0 was used to affirm the predicted anti-PR activity of the newly designed compounds and the results of docking complex structure could be visualized. All newly designed molecules were in agreement with CSore above four and the docking study revealed that Asp29, Asp30, Ile50, Asp124, Asp128, Asp129 and Ile149 were critical residues in the process of inhibiting PR.ConclusionOne of the main aspects of this study is the successful design of a series of molecules with excellent investigatory values, which elucidates explicit quantitative structure-activity relationships of DRV derivatives and will provide significant suggestions for future pharmaceutical research.
Keywords: 3D-QSAR