Research on the Anti-Diabetic Mechanism of Platycodon grandiflorus Based on Network Pharmacology and Molecular Docking
Year: 2025
Type: article
Abstract: 目的：通过网络药理学探究桔梗抗2型糖尿病(T2DM)的治疗机制。方法：利用TCMSP和HERB数据库筛选桔梗活性成分，通过PharmMapper和SwissTargetPrediction数据库获取成分作用靶点，结合GEO和GeneCards数据库获取T2DM相关基因。将共有靶点导入STRING数据库进行蛋白互作分析，使用Cytoscape 3.8.2可视化，并通过Metascape进行GO和KEGG富集分析。分子对接评估活性成分与靶点的结合能力。结果：筛选出27个桔梗活性成分，对应192个药物作用靶点、1815个疾病靶点及74个共有靶点。GO分析显示靶基因参与MAPK信号调控和蛋白质磷酸化等过程；KEGG分析表明桔梗成分通过PI3K-AKT信号通路、胰岛素抵抗及AGE-RAGE糖尿病并发症通路发挥作用。分子对接结果表明，桔梗中的木犀草素、硫胺素等活性成分与核心靶点具有较强结合能力。结论：桔梗通过EGFR、GSK3B、HSP90AA1、PPARG、TLR4等多靶点调控胰岛素受体，协同治疗T2DM。Objective: To explore the therapeutic mechanisms of Platycodon grandiflorus (Platycodon) against type 2 diabetes mellitus (T2DM) using network pharmacology. Methods: Active components of Platycodon were screened using the TCMSP and HERB databases. The targets of these components were obtained through the PharmMapper and SwissTargetPrediction databases, while T2DM-related genes were collected from the GEO and GeneCards databases. Common targets were imported into the STRING database for protein-protein interaction (PPI) analysis, visualized using Cytoscape 3.8.2, and subjected to GO and KEGG enrichment analysis via Metascape. Molecular docking was performed to evaluate the binding affinity between active components and their targets. Results: A total of 27 active components of Platycodon were identified, corresponding to 192 drug targets, 1815 disease targets, and 74 common targets. GO analysis revealed that the target genes were involved in processes such as MAPK signaling regulation and protein phosphorylation. KEGG analysis indicated that Platycodon components exert their effects through the PI3K-AKT signaling pathway, insulin resistance, and the AGE-RAGE diabetic complications pathway. Molecular docking results demonstrated strong binding affinities between Platycodon’s active components (e.g., luteolin and thiamine) and core targets. Conclusion: Platycodon regulates insulin receptors through multiple targets, including EGFR, GSK3B, HSP90AA1, PPARG, and TLR4, synergistically treating T2DM.
Source: Hans Journal of Biomedicine
Author: 雪颖 刘
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410945634