3-Dimensional QSAR and molecular docking studies of a series of indole analogues as inhibitors of human non-pancreatic secretory phospholipase A2.

Background: Design and development of new drugs is simplified and made more cost-effective because of the advances in the concepts of Quantitative Structure-Activity Relationship (QSAR) studies. A methodology of QSAR studies is one of the approaches to the rational drug design. Methods: 3-Dimensional QSAR studies were performed on a series of indole analogues as inhibitors of human non-pancreatic secretory phospholipaseA2 (PLA2) by using Scigress explorer software suite. Docking studies of these compounds were also performed to understand the interactions with amino acid residues of PLA2 protein. Results: The multiple linear regression analysis was used to correlate the physicochemical descriptors with the PLA2 inhibitory activity of 20 training set of compounds and the best QSAR model was developed. The best model was validated using leave-one-out method and found to be statistically significant, with coefficient of determination (r2) of 0.788. This model was further used to predict the PLA2 inhibitory activity of 12 test set of compounds. Docking analysis revealed that most of the compounds formed H-bond interactions with amino acid residues of PLA2 protein (PDB ID: 1DB4). Predicted pIC50 value of one of the test compounds was 7.454 and it showed H-bond interactions with Asp48, Cys44, His27, Gly29 and Gly31 residues. Conclusion: The present study shall help in rational drug design and synthesis of new selective PLA2 inhibitors with predetermined affinity and activity and provides valuable information for the understanding of interactions between PLA2 and the novel indole analogue compounds.

3-Dimensional quantitative structure-activity relationship and molecular docking studies of tetrasubstituted pyrazole derivatives as inhibitors of cyclooxygenase-2.

Background: Design and development of new drugs is simplified and made more cost-effective because of the advances in the concepts of Quantitative Structure-Activity Relationship (QSAR) studies. A methodology of QSAR studies is one of the approaches to the rational drug design. Methods: 3-Dimensional QSAR studies were performed on a series of tetrasubstituted pyrazole derivatives by using Scigress Explorer software suite. Docking studies of these compounds were also performed to understand the interactions with amino acid residues of COX-2 protein. Results: The multiple linear regression analysis was used to correlate the physicochemical descriptors with the COX-2 inhibitory activity of 24 training set of compounds and the best QSAR model was developed. The best model was validated using leave-one-out method and found to be statistically significant, with coefficient of determination (r2) of 0.835. This model was further used to predict the COX-2 inhibitory activity of 10 test set of compounds. Docking analysis revealed that most of the compounds formed H-bond interactions with amino acid residues of COX-2 protein (PDB ID: 1CX2). Predicted pIC50 value of one of the test compounds was 7.048 and it showed H-bond interactions with His90 & Tyr355 residues. Conclusion: The present study shall help in rational drug design and synthesis of new selective COX-2 inhibitors with predetermined affinity and activity and provides valuable information for the understanding of interactions between COX-2 and the novel tetrasubstituted pyrazole derivative compounds.

Surface area grid in modeling of anti hiv activity of tibo derivatives.

Due to their role in the inhibition of non nucleoside reverse transcriptase, 4,5,6,7-Tetrahydro- 5-methylimidazo[4,5,1-jk][1,4]benzodiazepin-2(1H)-ones (TIBO) derivatives present a significant importance as a potent chemotherapeutic agent against the AIDS disease. In this work, we report our attempt to find out the other factors required in quantitative structure-activity relationship for a set of 89 TIBO derivatives. In vitro Anti HIV activity of TIBO derivatives logIC50 expressed as log1/C values were considered as a biological activity parameter. The QSAR study of the dataset of 89 TIBO derivatives was performed using different parameters namely Topological, physicochemical, hydrophobic descriptors and indicator parameters. Multiple regression analysis performed to obtain QSAR model and to capture the descriptor other than the logP. The QSAR study highlights the logP, Is and surface area grid (SAG) descriptors, that affect the anti HIV activity of these TIBO derivatives. SAG is found as the cofactor working with hydrophobicity of TIBO derivatives. Eventually, the study provides a strong foundation to design new and more potent inhibitors of HIV-1 RT.