Integration of pharmacophore-based virtual screening, molecular docking, ADMET analysis, and MD simulation for targeting EGFR: A comprehensive drug discovery study using commercial databases

Abstract

The epidermal growth factor receptor (EGFR), a crucial component of cellular signaling pathways, is frequently dysregulated in a range of cancers. EGFR targeting has become a viable approach in the development of anti-cancer medications. This study employs an integrated approach to drug discovery, combining multiple computational methodologies to identify potential EGFR inhibitors. The co-crystal ligand for the EGFR protein (R85) (PDB ID: 7AEI) was employed as a model for developing pharmacophore hypotheses. Nine databases underwent a ligand-based virtual screening, and 1271 hits meeting the screening criteria were chosen. EGFR protein crystal structure was obtained from the PDB database (PDB ID: 7AEI) and prepared. The hit compounds identified during virtual screening were docked to the prepared EGFR receptor to predict binding affinities by using the glide tool's standard precision mode. The top ten compounds were chosen, and their affinities of binding ranged from -7.691 to -7.338 kcal/mol. The ADMET properties of the selected compounds were predicted, and three compounds MCULE-6473175764, CSC048452634, and CSC070083626 showed better QPPCaco values compared to other identified compounds, so these were selected for further stability analysis. To confirm the stability of the protein-ligand complexes, a 200 ns molecular dynamics (MD) simulation was run using the binding sites of the top three compounds against the EGFR receptor. These results suggest that the selected compounds may be lead compounds in suppressing the biological activity of EGFR, additional experimental investigation is required.