Computational assessment of natural compounds as potential hexokinase 2 inhibitors

Hexokinase 2 (HK2), a central enzyme in the glycolytic pathway, is frequently overexpressed in malignant cells, contributing to enhanced glucose metabolism and tumor progression. Despite its recognized role in cancer metabolism, effective and selective HK2 inhibitors from natural sources remain underexplored. This study aimed to identify promising natural product inhibitors of HK2 through an integrated computational approach. A diverse set of 100 natural compounds-including phenolics, terpenoids, alkaloids, and anthraquinones-was virtually screened using Glide XP docking to predict binding affinities. Subsequent molecular dynamics (MD) simulations and MM-GBSA binding free energy calculations were performed to validate docking results and evaluate complex stability over time. Notably, several phenolics, particularly salvianolic acid A, salvianolic acid B, verbascoside, quercetin, and hyperoside, exhibited strong binding affinities and favorable interaction profiles. Salvianolic acid A recorded the best docking score (- 9.58 kcal/mol), while hyperoside showed exceptional structural stability during 30 ns MD simulations and a competitive MM-GBSA binding energy (- 42.35 kcal/mol), approaching that of the native ligand (- 55.51 kcal/mol). Structural interaction analysis revealed that hyperoside formed persistent hydrogen bonds with key catalytic residues of HK2 (Glu742, Asp657, Glu708), supporting its potential as a lead scaffold. These findings highlight the value of phenolic natural products as potential HK2 inhibitors and lay the groundwork for future anticancer drug development targeting cancer-specific metabolic pathways.