Network Pharmacology and Molecular Docking Combined with in vitro α-Amylase and α-Glucosidase Assays to Assess Anti-diabetic Properties of Curcuma longa

Background

This study investigates the antidiabetic effects of Curcuma longa extract using in vitro enzyme assays, network pharmacology, and in silico molecular docking to elucidate its molecular mechanisms.

Materials and Methods

From 133 Curcuma longa phytochemicals screened via TCMSP, 52 underwent ADMET and toxicity analysis using Protox-3, Superpred, and SwissTargetPrediction. Ethanol-based Soxhlet extraction was performed on the rhizome. Compounds were filtered by ADME/toxicity profiles, and their protein targets were retrieved. Diabetes-related targets from GeneCards were overlapped with compound targets using Venny 2.0, identifying 157 common targets. A Protein-Protein Interaction (PPI) network was constructed in Cytoscape (STRING, confidence ≥0.700), with hub targets identified via CytoHubba. Gene ontology and KEGG analyses highlighted key pathways. The network output was validated by molecular docking using CB-DOCK2 and the docking interactions were validated by molecular dynamics simulation using GROMACS. In vitro antidiabetic effects were assessed using α-amylase and α-glucosidase assays.

Results

Six phytochemicals (Campesterol, Stigmasterol, Curcumenol, Curcumol, Curcumin, Procurcumadiol) showed favorable ADME/toxicity profiles. From 253 potential targets, 179 were refined, and 3,756 diabetes-related targets (Gene Importance Score >55%) were identified from 20,752. Overlapping revealed 157 common targets, forming a PPI network (186 nodes, 259 edges). Ten hub genes (e.g., AKT1, ESR1, STAT3) were identified, with curcumin showing strong docking interactions with STAT3, AKT1, and ESR1. The molecular docking and MD simulation results indicate a stable Curcumin-STAT3 complex with consistent RMSD, minimal ligand deviation, sustained hydrogen bonds, and stable Rg and SASA over 10 ns. In vitro assays demonstrated dose-dependent inhibition of α-amylase and α-glucosidase, comparable to acarbose.

Conclusion

Curcuma longa ethanol extract exhibits antidiabetic effects, supported by network pharmacology, molecular docking, and enzyme assays, highlighting key protein targets and pathways.