Unraveling potential EGFR kinase inhibitors: Computational screening, molecular dynamics insights, and MMPBSA analysis for targeted cancer therapy development

Abstract

EGFR is critical for tumor angiogenesis and cancer progression, but existing treatments like erlotinib face limitations such as acquired resistance and side effects. To address these issues, this study employs structure-based drug design techniques including virtual screening, molecular docking, and molecular dynamics simulations to identify new small molecule inhibitors targeting the EGFR kinase domain. From an initial selection of 633,000 compounds from diverse databases, top candidates were identified based on their binding affinity and stability. The virtual screening and docking analyses revealed compounds with higher binding scores than erlotinib. Molecular dynamics simulations and Anisotropic Network Model (ANM) analysis uniquely report that EGFR undergoes significant conformational shifts: inward flap movements in the bound state stabilize a closed conformation, while outward movements in the free state result in a more open conformation. Among the identified inhibitors, compounds such as JFD00243, NPA015124, and others exhibited strong binding affinities and stable interactions with both active and inactive forms of EGFR. Notably, JFD00243 was effective in targeting EGFR in both active and inactive conformations. These findings suggest that the identified inhibitors could potentially overcome current treatment limitations and improve targeted cancer therapies by effectively inhibiting EGFR-mediated tumor angiogenesis.