Network Pharmacology Integrated With Quantum‐Polarized Ligand Docking and Molecular Simulation Revealed the Anti‐Diabetic Potential of Curcumin

Abstract Diabetes mellitus is a chronic metabolic disorder affecting millions of people worldwide and causes serious complications such as diabetic nephropathy. Curcumin, a natural polyphenol derived from turmeric, has demonstrated antidiabetic, anti‐inflammatory, and antioxidant properties. However, the molecular mechanisms underlying curcumin's anti‐diabetic effects remain incompletely understood. This study employed network pharmacology, molecular docking, and simulation techniques to explore the potential targets, and key pathways of curcumin in the treatment of diabetes. Using SwissTarget prediction and Superpred databases, we predicted the molecular targets for curcumin, while diabetes‐associated genes were obtained from DisGeNet. We identified 60 common targets for curcumin in diabetes. Protein‐protein interaction (PPI) analysis revealed three sub‐networks and ten hub genes with AKT1, TNF‐α, EGFR, and STAT3 identified as key hub genes that could serve as potential biomarkers. Gene enrichment analysis indicated that these genes primarily regulate insulin resistance and other metabolic pathways. Quantum‐polarized ligand docking (QPLD) showed that curcumin establishes multiple hydrogen and hydrophobic interactions with the essential amino acids of these hub targets. Molecular simulation results demonstrated stable dynamic behavior, a compact structure, and variations in residue flexibility. Binding free energy calculations using MM/GBSA and MM/PBSA methods validate curcumin's strong binding to the potential targets. Total binding free energy using MM/GBSA ranged from −21.35 to −30.94 kcal/mol while MM/PBSA calculations showed total binding free energy values between −19.80 and −26.66 kcal/mol. Altogether, this study provides valuable insights into the molecular targets of curcumin in diabetes and lays the foundation for future advancements in diabetes treatment.