Pharmacophore-based in silico high-throughput screening to identify novel topoisomerase-I inhibitors

Abstract

Topoisomerase-I (TOP-I) has emerged as a potential target for the design and development of anticancer compounds. TOP-I inhibitors have shown promise in the treatment of various cancers including renal cell cancer, whose exact cause is yet to be known. Recent studies indicate that indenoisoquinolines can provide greater stability to drug-topoisomerase-DNA cleavage complexes, which makes them a more appropriate anticancer class of compounds compared to camptothecin. In view of such significance, a three-dimensional pharmacophore model has been developed using a training set of 36 indenoisoquinoline-based topoisomerase inhibitors. The validated best model consists of three chemical features: one hydrophobic, one positive ionizable, and one ring aromatic with good correlation values of r ²_(training)  = 0.827 and r ²_(test)  = 0.702. Furthermore, 98 % validation by CatScramble method and a good r ² of 0.703 from 22 external test set compounds have testified the universal applicability of the generated model. Validated three feature pharmacophore model has been used to screen the chemical database from the National Cancer Institute (NCI) leading to the identification of 17 druggable TOP-I inhibitors which can be raised into drug candidates after further evaluation.