网络药理学预测麻黄治疗哮喘的抗炎作用机制

doi:10.6040/j.issn.1671-7554.0.2018.1089

摘要/Abstract

摘要： 目的探讨运用网络药理学方法预测麻黄治疗哮喘的抗炎靶点及其相关信号通路,发现哮喘的发病机制。方法在TCMSP数据库中搜索并筛选麻黄的活性成分,运用PharmMapper数据库预测活性成分的作用靶点,并进行分子对接。应用cytoscape3.6.1软件构建麻黄活性成分-预测靶点网络,并对网络拓扑结构进行分析。TTD数据库中搜索抗炎靶点,建立蛋白互作网络,并与麻黄活性成分-预测靶点网络融合,筛选活性成分作用的抗炎靶点。构建麻黄抗炎靶点对抗哮喘的体内反应网络,筛选与哮喘发病相关的抗炎靶点。使用Enrichr数据库以及cytoscape3.6.1对预测的麻黄治疗哮喘的抗炎靶点进行KEGG生物通路富集分析。结果筛选出23个化合物,对应156个靶点蛋白,其中表皮活性生长因子受体(EGFR)、E选择素(SELE)、巨噬细胞迁移抑制因子(MIF)、有丝分裂原激活蛋白激酶14(MAPK 14)4个靶点可能是麻黄治疗哮喘的重要抗炎靶点。KEGG分析得到的与这些抗炎靶点相关的主要信号通路有上皮细胞信号通路等。结论 EGFR、SELE、MIF、MAPK14可能是麻黄在哮喘治疗中发挥抗炎作用的主要靶点,控制哮喘发生和发展,延缓病情恶化,可考虑整体控制这些抗炎靶点以及信号通路网络,而不仅仅是针对单一途径、疾病的关键靶点。

关键词: 哮喘, 麻黄, 网络药理学, 抗炎, 靶点预测, 通路

Abstract: Objective To explore the pathogenesis of asthma by predicting the anti-inflammatory targets and related signaling pathway of ephedra therapy based on network pharmacology. Methods The active ingredients of ephedra were searched and screened in TCMSP database. The targets of ingredients were predicted with PharmMapper and molecular docking was performed. Then ingredients-targets network was established and analyzed with cytoscape3.6.1. The anti-inflammatory targets in TTD database were searched to build PPI network, which was merged with the ingredients-targets network to screen anti-inflammatory targets connected with ephedra. The vivo reaction network of ephedra anti-inflammatory targets against asthma was constructed to screen anti-inflammatory targets related to asthma. KEGG enrichment analysis was performed with Enrichr database and cytoscape3.6.1. Results Altogether 23 active ingredients were screened and 156 targets were obtained. Epidermal active growth factor receptor(EGFR), E-selectin(SELE), macrophage migration inhibitory factor(MIF), mitogen-activated protein kinase 14(MAPK14)might be the important anti- 山东大学学报 (医学版)57卷1期 -陈欧,等.网络药理学预测麻黄治疗哮喘的抗炎作用机制 \=-inflammatory targets of ephedra treatment of asthma. All these pathways had epithelial cell signaling pathways. Conclusion The anti-inflammatory mechanism of ephedra treatment of asthma may be related to EGFR, SELE, MIF, MAPK14 and their signaling pathways. To prevent the exacerbation of asthma, instead of a single pathway or a single target, all these targets and their signaling pathways should be controlled holistically.

Key words: Asthma, Ephedra, Network pharmacology, Anti-inflammatory, Target prediction, Pathway

中图分类号:

R725.4

陈欧,李国勇,刘爱红,朱晓波,陈少杰,王一彪. 网络药理学预测麻黄治疗哮喘的抗炎作用机制[J]. 山东大学学报 (医学版), 2019, 57(1): 55-61.

CHEN Ou, LI Guoyong, LIU Aihong, ZHU Xiaobo, CHEN Shaojie, WANG Yibiao. Anti-inflammatory mechanism of ephedra treatment of asthma based on network pharmacology[J]. Journal of Shandong University (Health Sciences), 2019, 57(1): 55-61.

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