Emerging drug discovery paradigm in non small cell lung cancer: pharmacophore modeling, atom-based 3D- QSAR and virtual screening of novel EGFR inhibitors

Abstract

EGFR is a significant drug target approached in the domain of the wide prevailing cancer type, non- small cell lung cancer and search for its potent inhibitor is an emerging opportunity in cancer drug discovery. Computational framework of our study outsmarts the existing strategies and new insight into EGFR inhibitors. To figure out the higher biological behavior of the N-benzyl-N-(X-2-hydroxybenzyl)-N0-phenylureas and thioureas derivatives, functional spots requirement were substantially discovered using pharmacophore modeling and atom- based 3D-QSAR. Having the eye on five crucial pharmacophore features AADHR: namely two acceptors (A), one hydrogen bond donor (D), one hydrophobic group (H), one aromatic ring (R), then unique pharmacophore was identified. As the succession of this pharmacophore concept, statistical parameters for better construction of best model, correlation coefficient R² =0.9803 for training set compounds and Q²=0.7099 for test set compounds were outcome of the atom based 3D-QSAR analysis. Then we engaged with virtual screening method to screen existing drug molecules of zinc database to identify exceedingly capable inhibitor for EGFR. Ultimately, scaffold with distinct qualities for drug-like species, top four of them were reported.

KEYWORDS: EGFR inhibitors, pharmacophore modeling, atom-based 3D-QSAR, PHASE, glide.