| dc.description.abstract | HIV-1 integrase is an extremely important nominee in developing new and effective drugs especially naphthyridine compounds against acquired immune deficiency syndrome. The quantitative structure-activity relationship (QSAR) modeling is the most powerful method in computer-aided drug design and will be used to help the design of new naphthyridine derivatives. Different computational 2D-QSAR procedures applied to predict the relationship between the computational descriptors of naphthyridine derivatives with their HIV-1 integrase inhibition activities. Four different models including stepwise-MLR, consensus stepwise-MLR, GAPLS-MLR, and consensus GAPLS-MLR with appropriate correlation between the calculated and experimental biological activities (pIC(50)) against HIV-1 integrase were generated. Predictive QSAR models were obtained with R (training) (2) values of 0.848, 0.862, 0.709, and 0.751 as well as R (test) (2) values of 0.521, 0.651, 0.502, and 0.775 for stepwise-MLR, consensus stepwise-MLR, GAPLS-MLR, and consensus GAPLS-MLR models, respectively. QSAR models are high efficiency in prediction of the pIC(50) in comparison with other models because of concerning the combination of "quantum and molecular mechanical" descriptors. Combination of "quantum" and "molecular mechanical" descriptors improved our models with high efficient test set activity prediction potency. The obtained results provided useful information for understanding the effects of polarizability, electronegativity, and especially functional groups such as aromatic nitrogens that are important for the activities of naphthyridine compounds. The developed QSAR models will be efficient for the rational design of potent naphthyridine derivatives against HIV-1 integrase activity. | |
