Rational computational Design of new-Generation EGFR tyrosine kinase (EGFR-TK) inhibitors

A library of 45 novel compounds, derivatives of 2,3-diphenyl-2,3-dihydro-1H-quinazolin-4-one, were designed as potential EGFR inhibitors. This work describes in-silico study utilizing structure-based drug design (SBDD) and ligand-based drug design (LBDD) methodologies, incorporating Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) profiling, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations. ADMET profile of all the compounds were evaluated. A predictive 3D-QSAR model showed R(Alanazi et al., 2016²), $R_{\mathrm{pred}}^2$, and Q² values as 0.95, 0.62, and 0.52, respectively. The designed compounds showed binding affinities ranging from −6.9 to −8.4 kcal/mol when docked against the target protein (PDBID-6LUD). Top inhibitors included compounds 12, 13, 15, 26, 27, 28, 29, 30, 43, and 45 which demonstrated binding affinities more than −8.0 kcal/mol. Out of those, highest docking score was for compound 12 (−8.4 kcal/mol), surpassing the known anticancer drug Vandetanib (−8.0 kcal/mol). In addition, 100 ns MD simulations validated the stability of the protein-ligand complexes, confirming the potential of the selected compounds as potent EGFR inhibitor.