Computational investigation of hepatocyte growth factor receptor-ligand interactions for the identification of novel therapeutic inhibitors

Abstract

The hepatocyte growth factor receptor (HGFR), also known as c-MET, is a critical receptor tyrosine kinase that plays a central role in regulating various physiological processes, including organ development, tissue regeneration, and wound healing. Its abnormal activation has been linked to several cancers, making it a prime target for therapeutic interventions. This study aims to investigate the molecular binding interactions between the c-MET receptor and its ligand, hepatocyte growth factor (HGF), using molecular docking and dynamics simulation approaches, using computational techniques including molecular docking, molecular dynamics simulations, and electronic property analysis via MMGBSA and DFT methods. The molecular docking and dynamics simulations revealed that (2R)-3-[4-[[2-fluoro-3-(trifluoromethyl)phenyl]methoxy]phenyl]-2-(oxaloamino)propanoic acid and 3-[4-[[2-fluoro-3-(trifluoromethyl)phenyl]methoxy]phenyl]-2-(oxaloamino)propanoic acid exhibit strong binding affinities with the c-MET receptor, with key contributions from electrostatic and hydrophobic interactions. Post-simulation analysis showed a slight reduction in the HOMO-LUMO energy gap, indicating improved electronic interactions and enhanced stability of the ligand-receptor complex. These findings suggest that dynamic simulations optimize the binding poses and stability of the MET-HGF interaction. The binding free energies (ΔG_bind) of (2R)-3-[4-[[2-fluoro-3-(trifluoromethyl)phenyl]methoxy]phenyl]-2-(oxaloamino)propanoic acid and 3-[4-[[2-fluoro-3-(trifluoromethyl)phenyl]methoxy]phenyl]-2-(oxaloamino)propanoic acid were calculated to assess their affinity for MET, with both complexes demonstrating significant binding stability, primarily through electrostatic and hydrophobic interactions. Further analysis revealed a decrease in the HOMO-LUMO energy gap post-simulation, indicating enhanced electronic coupling and improved stability in the ligand-receptor interaction. These findings underscore the critical role of dynamic simulations in refining binding poses and stabilizing ligand-receptor interactions. The promising binding stability of these compounds highlights their potential as next-generation c-MET inhibitors, paving the way for the development of targeted therapies against MET-driven cancers. With further in vitro and in vivo validation, these computational insights could contribute to the advancement of precision medicine, offering new hope for patients with aggressive malignancies.