Network Pharmacology, Molecular Docking, and Molecular Dynamics Study to Explore the Effect of Resveratrol on Type 2 Diabetes.

Abstract

This network pharmacology study represents a significant step in understanding the potential of Resveratrol as an antidiabetic agent and its molecular targets. Targets for Type 2 diabetes were obtained from the MalaCards and DisGeNET databases, while targets for Resveratrol were sourced from the STP and CTD databases. Subsequently, we performed matching to identify common disease-compound targets. The identified genes were analyzed using the ShinGO-0.76.3 database for functional enrichment analysis and KEGG pathway mapping. A protein-protein interaction network was then constructed using Cytoscape software, and hub genes were identified. These hub genes were subjected to molecular docking and dynamic simulations using AutoDock Vina and Gromacs software. According to functional enrichment and KEGG pathway analysis, Resveratrol influences insulin receptors, endoplasmic reticulum functions, and oxidoreductase activity and is involved in the estrogen and HIF-1 pathways. Ten hub genes were identified, including ESR1, PTGS2, SRC, NOS3, MMP9, IGF1R, CYP19A1, MTOR, MMP2, and PIK3CA. The proteins associated with these genes exhibited high interaction with Resveratrol in the molecular docking analysis, and molecular dynamics showed a stable interaction of Resveratrol with ESR1, MMP9, PIK3CA, and PTGS2. In conclusion, our work enhances the understanding of the antidiabetic activity of Resveratrol, which future studies should experimentally corroborate.