ABSTRACT:
Inhibitors of HDACs are an important emerging class of drugs for the treatment of cancers. 3-Dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a series of N-(2-aminophenyl)-benzamide derivatives by using Scigress Explorer software. The multiple linear regression analysis was used to correlate the physicochemical descriptors with the anti-HDAC2 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 0.735696. This model was further used to predict the anti-HDAC2 activity of 29 test set of compounds. We also performed docking of these 29 test set of compounds using Molegro Virtual Docker software and found that most of the compounds formed H-bond interactions with amino acid residues. Predicted pIC50 value of one of the test compounds was 7.358 and it showed H-bond interactions with HDAC2 protein (PDB ID: 3MAX). This study shall help in rational drug design and synthesis of new selective HDAC2 inhibitors with predetermined affinity and activity and provides valuable information for the understanding of interactions between HDAC2 and the novel compounds.