Integrating network pharmacology, molecular docking, and molecular dynamics to explore the antidiabetic mechanism of Physalis angulata L.

Abstract

Diabetes mellitus is a chronic metabolic disorder that continues to rise globally, leading to severe health complications and economic burdens. Despite the availability of synthetic antidiabetic drugs, their side effects, limited efficacy, and long-term complications have driven interest in natural products as potential alternatives. Physalis angulata L. has been traditionally used for its anti-inflammatory, antioxidant, and hypoglycemic properties, but its molecular mechanisms in diabetes management remain unclear. This study employed network pharmacology (NP), molecular docking, and molecular dynamics (MD) simulations to systematically explore the bioactive compounds in Physalis angulata L. and their interactions with key diabetic targets. NP was utilized to predict compound-target interactions, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses to identify metabolic pathways involved in diabetes regulation. The predicted protein–protein interaction (PPI) networks were visualized using Cytoscape, revealing key targets linked to glucose metabolism and insulin sensitivity. To validate these predictions, molecular docking was performed to assess the binding affinity and stability of Physalis angulata L. metabolites with diabetic target proteins. The top-ranked compounds were further analyzed through MD simulations during a 50 ns simulation period, with root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) analysis confirming their structural stability within the receptor binding sites. Binding free energy calculations using MM-PBSA provided additional validation of ligand-receptor interactions. The results identified quercetin and myricetin as the most promising multi-target antidiabetic compounds, exhibiting strong and stable interactions with multiple key diabetic receptors. This study highlights the potential of Physalis angulata L. as a natural source for diabetes treatment, demonstrating the effectiveness of computational approaches in identifying bioactive compounds with multi-target therapeutic potential.