In Silico study for investigating and predicting the activities of 7-Hydroxy-1,3-dioxo-2,3-dihydro-1H-pyrrolo[3,4-c]pyridine-4-carboxylate Derivatives as Potent Anti-HIV Agents

Abstract

In this study a QSAR was carried out on a data set of 7-Hydroxy-1,3-dioxo-2,3-dihydro-1Hpyrrolo[3,4-c]pyridine-4-carboxylate Derivatives to investigate their activities on HIV-1. Genetic Function Algorithm(GFA) and Multi Linear Regression Analysis (MLRA) were used to select the optimum descriptors and to generate the correlation QSAR model that relate their activities against HIV with the molecular structures of the derivatives. After the internal validation, the model was found to have a squared correlation coefficient (R 2) of 0.9334, adjusted squared correlation coefficient (R 2 adj) of 0.9134 and leave one out cross validated coefficient (LOO-Q 2 cv) value of 0.8604. The external validation (R 2 pred) set used for confirming the predictive power of the model was 0.8935. Y randomization value of 0.6463 was used to confirm the robustness of the model. The robustness and stability of the model obtained by validation of the test set also confirmed that the model can be used to design and synthesize other 7-Hydroxy-1,3-dioxo-2,3dihydro-1H-pyrrolo[3,4-c]pyridine-4-carboxylate Derivatives with improved Anti-HIV activities.