QSAR study of carboxylic acid derivatives as HIV-1 Integrase inhibitors

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.

QSAR studies of a series of HIV-1 Integrase inhibitors are performed based on six different methods: stepwise-MLR, stepwise-BPNN, stepwise-SVM, RM-MLR, RM-BPNN, RM-SVM. Moreover, RM-SVM is the best models for predicting new HIV-1 Integrase inhibitors.Figure optionsDownload as PowerPoint slide