基于网络药理学探究丹参-赤芍-益母草治疗慢性心力衰竭的作用机制

Mechanism of salvia miltiorrhiza-radix paeoniae rubra-herba Leonuri on chronic heart failure based on network pharmacology

目的 采用网络药理学方法研究丹参、赤芍、益母草治疗心力衰竭(CHF)的药用成分、作用靶点及作用机制。方法 在GeneCard和OMIM数据库中列出了疾病目的靶点。TCMSP和SwissTargetPrediction数据库列出药物成分和靶点。使用Venny软件得出其交叉靶点。利用STRING数据库构建蛋白质-蛋白质关系,通过图像处理得到PPI网络关系图。借助Cytoscape生成“CHF-交叉靶点-药物成分”网络图。利用HIPLOT平台对位点进行GO分析和KEGG通路富集分析。结果 文章预测了102个活性成分和101个交叉靶点,其中主要靶点为:MAP激酶、信号转导和转录激活子3、丝氨酸/苏氨酸蛋白激酶等。GO分析结果表明,其与信号传导受体激活物活性、受体配体活性、生长因子受体结合等的发生有关。KEGG通路富集分析:与AGE-RAGE信号通路、PI3K-Akt信号通路、癌蛋白多糖等相关。结论 本文初步阐述了丹参-赤芍-益母草治疗CHF的主要作用靶点和作用途径,为今后治疗CHF提供临床参考价值。

Objective The medicinal ingredients, target and mechanism of salvia miltiorrhiza, Radix Paeoniae and Leonurus in treating heart failure(CHF) were studied by network pharmacology.Methods TCMSP and Swiss Target Prediction database were used to collect drug components and targets. Disease targets were collected from GeneCard and OMIM databases. Using Venny software to obtain the common target of both. The protein-protein interaction relationship was constructed using STRING database, and the graph was processed to get PPI network graph. Using Cytoscape to draw“Drug composition-intersection TARGET-CHF” network. The common targets were analyzed by GO and KEGG pathway enrichment using HIPLOT platform.Results Totally 102 active components 101 cross targets were predicted, including MAP kinase, signal transducer and activator of transcription 3, serine/threonine protein kinase and so on. The results of GO analysis were related to the activities of signal receptor activator, receptor ligand and growth factor receptor binding. The results of KEGG pathway enrichment analysis were related to AGE-RAGE, PI3K-Akt and cancer proteoglycan pathways.Conclusion The main target and pathway of salvia miltiorrhiza-radix paeoniae rubra-herba Leonuri in the treatment of CHF were preliminarily clarified in this paper, which can provide clinical reference value for the treatment of CHF in the future.