Exploration into the Molecular Mechanism of Sanjie Zhentong Capsulse in the Treatment of Endometriosis Based on Network Pharmacology and Molecular Docking
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维普
万方数据
目的:基于网络药理学及分子对接挖掘散结镇痛胶囊治疗子宫内膜异位症的有效成分、作用靶点、信号通路以探索其分子生物学机制.方法:通过TCMSP数据库检索散结镇痛胶囊的有效成分;检索子宫内膜异位症疾病相关靶点,得到散结镇痛胶囊和子宫内膜异位症的交集靶点;利用Cytoscape、STRING数据库构建蛋白互作用网络(protein-protein interaction,PPI)筛选核心蛋白;通过David数据库完成基因本体(gene ontology,GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析;利用AutoDock完成关键成分与靶点分子对接验证.结果:筛选出散结镇痛胶囊54个化合物和943个靶点,内膜异位症靶点1088个,获得两者交集基因231个,筛选获得VEGFA、ALB、Akt1、MAPK3、SRC等45个核心靶点.分子对接显示β-谷甾醇与AKT1、SRC,紫檀芪与Akt1、MAPK3分子结合更稳定.结论:散结镇痛胶囊可通过多成分、多靶点、多通路协同作用治疗子宫内膜异位症,机制可能为有效成分及靶点作用于HIF-1信号通路、雌激素信号通路、TNF信号通路有关.
Objective:To explore the main effective components,targets and signaling pathways of Sanjie Zhentong capsule in the treatment of endometriosis based on network pharmacology and molecular docking,and to explore its potential biological mechanism.Methods:The effective components of Sanjie Zhentong capsule were searched through TCMSP database;The related targets of endometriosis were searched to obtain the intersection targets of Sanjie Zhentong capsule and endometriosis,The PPI network was constructed using Cytoscape and STRING databases to screen for core proteins;GO and KEGG enrichment analysis was completed by using David database;docking verification of key components and target molecules was performed using AutoDock.Results:All 54 compounds and 943 targets of Sanjie Zhentong capsule were screened,as well as 1088 targets of endome-triosis,231 intersection genes,and 45 core targets including VEGFA,ALB,Akt1,MAPK3 and SRC.Molecular docking showed that β-sitosterol and Akt1,SRC and pterostilbene had a more stable binding with AKT1 and MAPK3 molecules.Conclusion:Sanjie Zhentong capsule could treat endometriosis through multi-component,multi-target and multi-channel synergy,and its mechanism may be related to the effects of effective components and targets on HIF-1 signaling pathway,estrogen signaling pathway and TNF signaling pathway.
维普
万方数据
