The search for a suitable cancer treatment has been going on for the last few decades for the effective treatment. Now, computational biology has emerged as a novel tool to improve the domain of computer aided drug designing. The present study reports a ligand based pharmacophore computational modeling that elucidates important pharmacophoric features helpful for the inhibition of topoisomerase II activity of cancer. A six featured pharmacophore model of topoisomerase II has been generated via 10 training sets of reported topoisomerase II inhibitors ligands in Molecular Operating Environment 2009.10. pharmacophore constructing tool. The generated pharmacophore model was then validated by the 24 test set database of the reported naphthoquinone inhibitors. Later the validated pharmacophore model was then used to virtually screen the possible hit compounds from the ZINC drug database by using ZINCpharmer tool. The virtually screened hits were filtered by Lipinski’s rule of five and further assessed through molecular docking and ADMET studies. The results of docking and interaction studies were validated through binding score analysis and ADMET profiling. Seven hits (ZINC ID’s: 00000903, 02570830, 02012726, 00001402, 02040199, 01481831, and 00006923) of different scaffolds having interactions with important active site residues of topoisomerase II were predicted. It can be concluded from the finding of the present study that predicted hits could serve as potential candidates in the development of novel and potent topoisomerase II inhibitors. The present modeling explores the significant role of the predicted hits towards blocking the replication of cancer.
