基于网络药理学芪葵颗粒治疗糖尿病肾病的物质基础及作用机制研究

Network pharmacology-based study on material basis and mechanism of Qikui Granules against diabetic nephropathy

目的运用网络药理学方法研究芪葵颗粒治疗糖尿病肾病(DN)的多成分、多靶点、多通路作用机制,旨在为其基础研究及临床应用提供依据。方法通过多个数据库检索并筛选芪葵颗粒活性成分和其作用DN相关靶点,并通过Cytoscape软件分别构建药物、靶点、疾病靶点网络图,利用网络拓扑分析芪葵颗粒治疗DN关键靶点,采用ClueGO插件进行GO、KEGG基因富集分析,得到芪葵颗粒治疗DN的潜在作用通路。结果芪葵颗粒中筛选得到67个活性成分,涉及DN作用靶点212个。网络拓扑分析最终筛选出43个关键靶点,ClueGO富集分析关键靶点主要被富集在IL-17信号通路、HIF-1信号通路、TNF信号通路等49个显著相关通路,涉及神经递质代谢过程、小分子代谢过程、血压和氧化还原酶活性调节等132个显著相关生物过程。结论芪葵颗粒有效成分可调控DN发病重要通路中多个靶点。

Objective This study was designed to explore the"multi-components,multi-targets,multi-pathways"mechanism of Qikui Granules in the treatment of diabetic nephropathy(DN)by network pharmacology,aiming to provide basis for its basic research and clinical application.Methods The active chemical constituents of Qikui Granules and their related targets against diabetic kidney disease were searched and screened by multiple databases.The network maps of drug-disease-targets were constructed by Cytoscape software.The key targets of Qikui Granules against DN were searched by network topology.The GO and KEGG gene enrichment analysis of the key targets for treating DN were performed by using ClueGO.Results The network analysis indicated that 67 active chemical components and 212 targets against DN were established from Qikui Granules.A total of 43 key targets were finally screened by network topology analysis.These targets were mainly enriched in 49 significant related pathways such as IL-17 signaling pathway,HIF-1 signaling pathway,TNF signaling pathway and so on.Also,132 significant related biological processes such as neurotransmitter metabolic processes,positive regulation of small molecule metabolic processes,regulation of blood pressure and oxidoreductase activity were related.Conclusion This study reveals that the active constituents of Qikui Granules could regulate multiple targets in the pathogenesis of diabetic nephropathy,which provides an important basis for further research on its mechanism of action against DN.