Exploration of potential EGFR inhibitors: a combination of pharmacophore-based virtual screening, atom-based 3D-QSAR and molecular docking analysis

Abstract

Epidermal growth factor receptor (EGFR) protein tyrosine kinases are over expressed in several human cancers and considered as a promising target for developing novel anticancer drugs. In this study, the ligand-based pharmacophore mapping and atom-based 3D-QSAR approach was carried out on a series of 40 novel pyrrolo[3, 2-d]pyrimidine derivatives acting as EGFR inhibitors. The best pharmacophore hypothesis AAADRR.295 was selected and an atom-based 3D-QSAR model was generated by applying partial least-squares algorithm. The developed model was validated and used as a 3D query in sequential virtual screening study to filter five chemical databases. The obtained compounds were further filtered according to Lipinski rule of five and fitness score. Subsequently, a multistep molecular docking study was employed on the retrieved hits and finally, 12 compounds were prioritized as potential leads against EGFR, which exhibited high docking scores, correlated binding mode to experimentally proven compounds and constructive drug-like properties. The results of this study provide detailed structural insights and emphasize the important binding features of these compounds, which may assists in the design and development of novel EGFR inhibitors.