Pharmacophore modeling, 3D-QSAR, docking and ADME prediction of quinazoline based EGFR inhibitors

Abstract

Pharmacophore modeling, molecular docking and in silico ADME prediction have been performed for quinazoline based EGFR inhibitors. This study has been carried out to determine the binding mode and drug likeliness nature of compounds. A five point model (AAARR.7) was generated using 64 compounds. The generated model was found to be statistically significant as it had a high correlation coefficient (R2 = 0.9433), cross validation coefficient (Q2 = 0.8493) and F value of 97.10 at 6 component PLS factor. The results of external validation were also indicative of high predictive power (R2 = 0.86). The generated model also passed Tropsha’s test for predictive ability and Y-randomization test. The Domain of Applicability (APD) of the model was also successfully defined to ascertain that a given prediction can be considered reliable. In order to evaluate the effectiveness of the docking protocol, co-crystallized ligand was extracted from the ligand binding domain of the protein and was re-docked into the same position. The conformer obtained on re-docking and the co-crystallized ligand were superimposed and the root mean square deviation between the two was found to be 1.005 Å. Outcomes of this study provide an insight for designing novel EGFR inhibitors. Keywords: 3D-QSAR, Molecular docking, Quinazoline, Epidermal growth factor receptor