In-silico identification of novel Topoisomerase-I inhibitors: Application of ligand based pharmacophore modeling and chemical database mining

Supriya Singh; Sarvesh Paliwal; Anubhuti P; ey; Sucheta Das; Rajeev Singh

Abstract

In-silico identification of novel Topoisomerase-I inhibitors: Application of ligand based pharmacophore modeling and chemical database mining

Author(s): Supriya Singh, Sarvesh Paliwal,Anubhuti Pandey, Sucheta Das and Rajeev Singh

In recent year’s topoisomerase I inhibitors like indenoisoquinolines have become important new lead for rational design of anticancer drugs due to their greater physiological and DNA-enzyme cleavage complexes stabilities. As a starting point a complete pharmacophore based 3D-QSAR study was performed on a series of 104 indenoisoquinolines and their derivatives. The best pharmacophore model consisted of one Hydrophobe (HY), one Positive Ionizable (PI) and one Ring Aromatic (RA) charecterstics which are a necessary requirement for good topoisomerase I inhibitory activity. The model was validated using Fischer randomization test and by internal and external data set of 38 and 27 compounds, respectively exhibiting r2 of 0.663 and 0.66. The validated pharmacophore model was used to screen NCI and Maybridge database resulting in identification of 21 novel topoisomerase I inhibitors. Since all the 21 compounds obeyed Lipinski’s rule of five, it is envisaged that these structurally diverse compounds have great potential for their development as anti-cancer agents.

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