DESIGN OF POTENTIAL ANTITUBERCULAR AGENTS CONTAINING UREA ANALOGUES, USING PHARMACOPHORE OPTIMIZATION BY MOLECULAR MODELING STUDIES

Tuberculosis disease has been the leading cause of morbidity and mortality among the infectious diseases. To address these issues, research and developmental activities to develop novel and potent new chemical entities are necessary. Molecular modelling studies are an approach which is used to narrow down a library containing an extraordinarily high number of random molecules into a smaller list of the potentially effective inhibitors. Two dimensional 2D and three dimensional 3D Quantitative Structure activity relationship (QSAR) studies were performed for correlating chemical composition of 1, 3-disubstituted urea analogues and antitubercular activity using Multiple Linear Regression (MLR) Analysis. The developed QSAR models were found to be statistically significant with respect to training (r2>0.7), cross-validation (q2>0.5), and external validation (pred_r2>0.5). The best model shows r 2 = 0.9743, q2 = 0.9134 and Pred_r2 = 0.5650. Binding affinities of designed NCEs were studied on Epoxide Hydrolase at specific binding site using docking studies and their ADME properties were also predicted. All the designed compounds show better affinity to the receptor site than the reference compound i.e. thioacetazon. This study will help for the synthesis of potential antitubercular agents. Keywords: Epoxide hydrolase, 2D QSAR, 3D QSAR, Docking, ADME Prediction.