Mechanistic Insights Into Ganoderma Lucidum for Diabetes Treatment via Network Pharmacology and Validation - Guo S; Yang L; Zhou J; Luo W; Nie B; Zhong X; Liu D; Kang X (Diabetes, Metabolic Syndrome and Obesity)
Shengxiang Guo,1– 3,* Lan Yang,4,* Jiali Zhou,1– 3 Wu Luo,1– 3 Beibei Nie,1– 3 Xiaohong Zhong,1,5 Dongbo Liu,1– 3,5 Xincong Kang1– 3 1College of Horticulture, Hunan Agricultural University, Changsha, 410128, People’s Republic of China; 2State Key Laboratory of Subhealth Intervention Technology, Changsha, 410128, People’s Republic of China; 3Hunan Provincial Engineering Research Center of Medical Nutrition Intervention Technology for Metabolic Diseases, Hunan Agricultural University, Changsha, 410128, People’s Republic of China; 4School of Pharmacy, North Sichuan Medical College, Nanchong, 637000, People’s Republic of China; 5National Research Center of Engineering Technology for Utilization of Botanical Functional Ingredients, Hunan Agricultural University, Changsha, 410128, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xincong Kang, College of Horticulture, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha, 410128, People’s Republic of China, Tel +86-0731-8461-7068, Email kangxincong@163.com Dongbo Liu, College of Horticulture, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha, 410128, People’s Republic of China, Email chinasaga@163.comPurpose: There is an urgent need to develop antidiabetic medications with minimal side effects and low toxicity. Ganoderma lucidum, a food-medicine homologous in China, has been used to treat diabetes. This study was aimed to explore the active ingredients and mechanism of G. lucidum 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 G. lucidum, of which 17 had predicted targets. G. lucidum 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 G. lucidum. A strong interaction of β-sitosterol 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.Keywords: Ganoderma lucidum, diabetes, insulin resistant, network pharmacology, molecular docking, cell