Combining Experimental and Computational Approaches to Elucidate the Anti-T2DM Potential of Eriobotrya japonica Flower: In vitro Enzyme Inhibition, Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Objectives

To investigate the anti-T2DM potential and mechanism of Eriobotrya japonica (loquat) flower using an integrated approach combining in vitro assays, network pharmacology, molecular docking, and Molecular Dynamics (MD) simulation.

Materials and Methods

The α-glucosidase inhibitory activity of 70% ethanol extracts from 18 batches of loquat flowers was evaluated. Active components and targets were identified via network pharmacology, with core targets discerned through Protein-Protein Interaction (PPI) network analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Molecular docking validated interactions between key components and targets, and their ADMET properties were predicted. MD simulation assessed the binding stability and affinity of the quercetin-AKT1 complex.

Results

All extracts inhibited α-glucosidase concentration-dependently. Network pharmacology identified 8 active components (e.g., Quercetin, Ursolic acid) and 196 common targets, including core targets TP53, AKT1, STAT3, and TNF. Enrichment analyses implicated pathways in lipid metabolism, atherosclerosis, and hormone response. Molecular docking confirmed stable binding (energy < -7 kcal/mol). ADMET predictions indicated favorable pharmacokinetics. MD simulations demonstrated exceptional stability and strong binding affinity (-43.06 kcal/mol) for the quercetin-AKT1 complex, primarily driven by van der Waals interactions.

Conclusion

Loquat flower exerts anti-diabetic effects via multi-component, multi-target, and multi-pathway mechanisms, involving enzyme inhibition and modulation of insulin resistance and inflammation pathways. MD simulations provided atomic-level validation of the key interaction, robustly supporting the proposed multifaceted mechanism.