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Updated: Jun 12, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
QSAR study of carboxylic acid derivatives as HIV-1 Integrase inhibitors
Zhengjun Cheng1, Yuntao Zhang, Weizhong Fu
1Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province, China West Normal University, Nanchong 637002, China.
Abstract:
QSAR studies have been carried out on carboxylic acid derivatives as HIV-1 Integrase inhibitors using 3D-MoRSE (3D-Molecular Representation of Structure based on Electron diffraction) descriptors. The stepwise multiple linear regression (stepwise-MLR) and replacement method (RM) methods are used to select descriptors which are responsible for the inhibitory activity of these compounds. Mathematical models are obtained by support vector machine (SVM), back-propagation neural networks (BPNN) and multiple linear regression (MLR). Leave-one-out, Leave-many-out (7% and 18%) cross-validation and external validation are carried out with the aim of evaluating the predictive ability of the models. The values of their respective squared correlations coefficients are 0.731, 0.664, 0.523 and 0.766, respectively. Our best QSAR model reveals the polarizability, mass as the most influencing atomic properties in the structures of the carboxylic acid derivatives.
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Structure-Activity Relationships and Drug Design
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...

