Mechanistic Insights Into for Diabetes Treatment via Network Pharmacology and Validation.

PURPOSE

There is an urgent need to develop antidiabetic medications with minimal side effects and low toxicity. , a food-medicine homologous in China, has been used to treat diabetes. This study was aimed to explore the active ingredients and mechanism of in the treatment of diabetes.

MATERIALS AND METHODS

Relevant compounds and targets of Ganoderma were collected from the TCMSP database, BATMAN-TCM database, relevant literature and PubChem. A diabetes-related target database was constructed using TTD, BATMAN-TCM, and Uniprot. A PPI network and H-C-T-P network were constructed to analyze interactions among these targets. GO and KEGG enrichment analyses were performed using WebGestalt. Molecular docking of the core compounds and key targets was carried out using AutoDock Vina. The predicted key targets were verified via qRT-PCR in PA-induced HepG2 cells, using GLAE (ethanol extract of Ganoderma lucidum) as the treatment.

RESULTS

A total of 58 compounds were screened out in , of which 17 had predicted targets. was involved in metabolic processes, such as lipid binding, insulin secretion, and other pathways. Molecular docking results showed that the core component β-sitosterol had strong binding activity with key targets CASP3, PRKACA, and PGR. Based on the results of network pharmacology, the top 10 targets related to glucose and lipid metabolism were selected for validation. The results indicated that in a high-fat environment, glucose and lipid metabolism in HepG2 cells was improved, with decreased mRNA expression of CASP3, PRKACA, CYP19A1, NR3C1, JUN, and increased expression of PGR and RXRA.

CONCLUSION

Glucose and lipid metabolism are important for the anti-diabetic activity of . A strong interaction of with CASP3, PRKACA, and PGR, which may be related to cell apoptosis, gluconeogenesis and insulin secretion, etc. This study lays the foundational groundwork for future drug development and therapeutic optimization.