IDENTIFICATION OF POTENT VIRTUAL LEADS AS TOPOISOMERASE-II INHIBITORS USING PHARMACOPHORE MODELLING, MOLECULAR DOCKING AND ADME STUDIES

Topoisomerase enzymes are highly expressed in cells which undergo rapid multiplication. Inhibition of this enzyme represents a potential therapeutic approach for diseases such as cancer. In order to understand the structure activity correlation of 2, 4, 6 pyridine based topoisomerase inhibitor, we have carried out a combined pharmacophore modelling, 3D-QSAR studies, molecular docking and virtual screening studies. A five point pharmacophore with hydrogen bond acceptor (A), hydrogen bond donor (D) and three aromatic rings (R 5, R 6, R 7) was used to derive a predictive atom based 3d-qsar model. The generated model had showed good correlation coefficient for training set and test set (R²=0.91and Q²=0.827). It was also validated using enrichment factor (EF) and goodness of hit score (GH score) and was used for virtual screening of compounds from ‘zinc drug like database’. Docking study of the hits retrieved from virtual screening revealed the binding affinity of these inhibitors at the active site of topoisomerase enzyme. In silico ADME predictions was also performed. These findings provide a set of guidelines for designing compounds with better topoisomerase inhibitory potential.