Computational Screening of Anticancer Phytochemicals From IMPPAT2.0 Database: Molecular Docking and Molecular Dynamics Evaluation Against EGFR and FGFR3

Abstract

EGFR and FGFR3 are receptor tyrosine kinases that regulate cell growth and survival, and their dysregulation contributes to cancer progression. In this study, phytochemicals from the IMPPAT 2.0 database were screened in silico using FDA‐approved anticancer drugs as reference molecules, followed by evaluation against EGFR and FGFR3. The workflow included ligand‐based virtual screening, drug‐likeness assessment, toxicity prediction, DFT optimization, molecular docking, molecular dynamics simulations, and ADMET profiling. Four candidates–‐IMPHY005097, IMPHY005655, IMPHY014154, and IMPHY017537–‐were shortlisted based on drug‐likeness and safety filters. Their geometries were optimized and docked against EGFR (PDB: 6JZ0, 4JQ7) and FGFR3 (PDB: 6LVM, 7DHL). Among the four compounds, IMPHY005655 showed the strongest binding to both targets and a higher predicted affinity toward 7DHL than its native ligand, while maintaining comparable affinity in EGFR complexes. Electronic properties were evaluated at the DFT/B3LYP/6‐311++G(d,p) level. MD simulations (200 ns) of 6JZ0‐IMPHY005655 and 7DHL‐IMPHY005655 supported stable complex formation, based on RMSD, RMSF, hydrogen bonding, radius of gyration, and SASA trends. Comparison with the native ligands (CKO and H6X) showed that IMPHY005655 exhibits improved drug‐likeness along with more favorable pharmacokinetic and toxicity predictions. These findings identify IMPHY005655 as a promising computational lead with potential dual EGFR/FGFR3 targeting and support further experimental validation.