张王宁, 高耀, 李科, 钞建宾, 秦雪梅, 李爱平. 基于网络药理学的黄芪总黄酮治疗肾病综合征的机制研究J. 药学学报, 2018,53(9): 1429-1441. doi: 10.16438/j.0513-4870.2018-0251
引用本文: 张王宁, 高耀, 李科, 钞建宾, 秦雪梅, 李爱平. 基于网络药理学的黄芪总黄酮治疗肾病综合征的机制研究J. 药学学报, 2018,53(9): 1429-1441. doi: 10.16438/j.0513-4870.2018-0251
ZHANG Wang-ning, GAO Yao, LI Ke, CHAO Jian-bin, QIN Xue-mei, LI Ai-ping. Exploration into the mechanism of total flavonoids of Astragali Radix in the treatment of nephrotic syndrome based on network pharmacologyJ. Acta Pharmaceutica Sinica, 2018,53(9): 1429-1441. doi: 10.16438/j.0513-4870.2018-0251
Citation: ZHANG Wang-ning, GAO Yao, LI Ke, CHAO Jian-bin, QIN Xue-mei, LI Ai-ping. Exploration into the mechanism of total flavonoids of Astragali Radix in the treatment of nephrotic syndrome based on network pharmacologyJ. Acta Pharmaceutica Sinica, 2018,53(9): 1429-1441. doi: 10.16438/j.0513-4870.2018-0251

基于网络药理学的黄芪总黄酮治疗肾病综合征的机制研究

Exploration into the mechanism of total flavonoids of Astragali Radix in the treatment of nephrotic syndrome based on network pharmacology

  • 摘要: 构建黄芪总黄酮活性成分-作用靶点网络和蛋白相互作用网络,对靶点涉及的功能和通路进行分析,探讨黄芪总黄酮治疗肾病综合征的作用机制。采用1H NMR和LC-MS辨识黄芪总黄酮化学成分,检索TCMSP与TCMID数据库获取黄芪总黄酮主要活性成分,利用PharmMapper服务器、SEA、SIB、HOME-NCBI-GENE、GeneCards和OMIM数据库预测和筛选黄芪总黄酮治疗肾病综合征的作用靶点。采用Cytoscape软件构建活性成分-作用靶点网络与蛋白相互作用网络图,采用ClueGO软件对靶点进行GO富集分析及KEGG通路分析,通过BioGPS数据库对靶点所属的组织分布进行归属,并通过Systems Dock Web Site对成分与靶点进行分子对接验证。筛选得到黄芪总黄酮29个活性成分,涉及50个作用靶点。网络分析结果表明,黄芪总黄酮主要涉及炎症反应过程、氧化应激过程、凋亡与自噬等生物过程,通过调节AGE-RAGE、PI3K/Akt、VEGF、IL-17和MAPK等信号通路来发挥治疗肾病综合征的作用。本研究体现了黄芪总黄酮多成分、多靶点、多途径的作用特点,为进一步开展黄芪总黄酮治疗肾病综合征作用机制的研究提供了新思路和新方法。

     

    Abstract: This study was designed to explore the mechanism of total flavonoids of Astragali Radix (TFA) in treating nephrotic syndrome through establishing the active components-targets network and protein-protein interaction (PPI) networks and analyzing the functions and pathways involved in the targets. The main active ingredients of TFA were obtained by 1H NMR and LC-MS, TCMSP and TCMID database. PharmMapper, SEA, SIB, HOME-NCBI-GENE, GeneCards and OMIM were used to predict and screen the active components of TFA. The Cytoscape software was used to construct the active components-targets network and protein-protein interactions network. The relation between the main active ingredients and targets were validated by Systems Dock Web Site. The GO and KEGG pathways involved in the targets were analyzed by ClueGO software. The target organ distribution was assigned by the BioGPS database. The results showed that 29 active components and 50 targets of TFA were screened and predicted. The network results showed that the TFA were mainly involved in biological processes such as inflammatory reaction process, oxidative stress process,apoptosis and autophagy, and played a role in the regulation of AGE-RAGE, PI3K/Akt, VEGF, IL-17 and MAPK signaling pathways to treat the nephrotic syndrome. This study reflects the characteristics of multi-components, multi-targets and multi-pathways of TFA, which provides new ideas and clues for further research on the mechanism of anti-nephrotic syndrome effects of TFA.

     

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