郑爽,何丽清,储开博.基于网络药理学探讨小青龙汤治疗慢性肾小球肾炎的潜在作用机制[J].浙江中医药大学学报,2021,45(7):801-808. |
基于网络药理学探讨小青龙汤治疗慢性肾小球肾炎的潜在作用机制 |
Exploration of Xiaoqinglong Decoction for Treatment of Chronic Glomerulonephritis Based on Network Pharmacology |
DOI:10.16466/j.issn1005-5509.2021.07.021 |
中文关键词: 小青龙汤 慢性肾小球肾炎 网络药理学 VEGF信号通路 HIF-1信号通路 TNF信号通路 PI3K/AKT信号通路 作用机制 |
英文关键词: Xiaoqinglong Decoction chronic glomerulonephritis network pharmacology VEGF signaling pathway HIF-1 sigraling pathway TNF signaling pathway P13K/AKT signaling pathway mechanism of action |
基金项目:山西中医药大学科技创新能力培育计划项目(2019PY-122) |
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中文摘要: |
[目的]运用网络药理学方法探讨小青龙汤治疗慢性肾小球肾炎的潜在作用机制。[方法]借助中药系统药理学数据库与分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,TCMSP)收集小青龙汤的活性化合物及其作用靶点,借助在线人类孟德尔遗传(Online Mendelian Inheritance in Man,OMIM)数据库和基因组注释数据平台(genome annotation database platform,GeneCard)收集慢性肾小球肾炎的疾病靶点,通过韦恩图2.1确定交集基因;将交集基因导入String 11.0平台,构建蛋白质相互作用(protein protein interaction,PPI)网络;利用DAVID 6.7数据库和Omicshare Tool软件进行基因本体(gene ontology,GO)富集分析和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)富集分析。[结果]获得有效化合物149种,药物靶点2 447个,疾病靶点2 425个;得到潜在靶点154个,通过构建“化合物-靶点”网络图,确定小青龙汤治疗慢性肾小球肾炎的核心成分40个、核心靶点40个。核心成分为槲皮素、山奈酚、β-谷甾醇、柚皮素、木犀草素、黄芩苷、卡维丁、隐品碱等;核心靶点为前列腺素G/H合酶2(prostaglandin G/H synthase 2,PTGS2)、半胱天冬酶-3(caspase-3,CASP3)、雌激素受体1(estrogen receptor 1,ESR1)、一氧化氮合酶2(nitric oxide synthase 2,NOS2)、雄激素受体(androgen receptor,AR)、丝裂原活化蛋白激酶14(mitogen-activated protein kinase 14,MAPK14)等。GO富集分析显示小青龙汤通过血管生成、血管内皮细胞迁移的正调控、脂多糖介导的信号通路、类固醇激素受体活性、细胞外调节蛋白激酶的正调控等生物过程发挥治疗作用,KEGG富集分析显示了血管内皮生长因子(vascular endothelial growth factor,VEGF)信号通路、缺氧诱导因子-1(hypoxia-inducible factor-1,HIF-1)信号通路、肿瘤坏死因子(tumor necrosis factor,TNF)信号通路、磷脂酰肌醇激酶-蛋白激酶B(phosphatidylinositide 3-kinases-protein kinase B,PI3K-Akt)信号通路和Toll样受体信号通路共5条信号通路。[结论]网络药理学方法研究提示,小青龙汤可能通过调节VEGF信号通路、HIF-1信号通路、TNF信号通路及PI3K/AKT信号通路等发挥抗炎作用,治疗慢性肾小球肾炎。 |
英文摘要: |
[Objective] Using network pharmacology method to explore the potential mechanism of Xiaoqinglong Decoction(XQLD) on chronic glomerulonephritis(CGN). [Methods]Using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) to search the active compound and its targets of XQLD; Online Mendelian Inheritance in Man(OMIM) database and Genome Annotation Database Platform(GeneCard) were used to collect disease targets of CGN. Get the intersection between the disease genes and the medicine genes by using Wayne Figure 2.1; input these intersection genes into the String 11.0 platform to build a protein-protein interaction(PPI) network; using the DAVID 6.7 database and Omicshare Tool for gene ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. [Results] Totally 149 effective compounds and 2 447 disease targets, including 154 CGN related targets were screened out. By constructing a “compound-target” network diagram, 40 key components and 40 key targets of XQLD in the treatment of CGN are found. The key components are quercetin, kaempferol, β-sitosterol, naringenin, luteolin, baicalin, carvedin, cryptopine, etc.; the core target is prostaglandin G /H synthase 2(PTGS2), caspase-3(CASP3), estrogen receptor 1(ESR1), nitric oxide synthase 2(NOS2), androgen receptor(AR), mitogen-activated protein kinase 14(MAPK14), etc. GO enrichment analysis shows items including angiogenesis, positive regulation of blood vessel endothelial cell migration, lipopolysaccharide-mediated signaling pathway, steroid hormone receptor activity, positive regulation of extracellular regulated protein kinase 1(ERK1) and extracellular regulated protein kinase 2(ERK2) cascade, etc. KEGG pathway analysis shows 5 pathways including vascular endothelial growth factor(VEGF) signaling pathway, hypoxia-inducible factor-1(HIF-1) signaling pathway, tumor necrosis factor(TNF) signaling pathway, phosphatidylinositide 3-kinases-protein kinase B(PI3K-Akt) signaling pathway and Toll-like receptor signaling pathway. [Conclusion] This study used network pharmacology method to predict and screen the target of XQLD on CGN and its potential mechanism initially. XQLD may play an anti-inflammatory effect and treat CGN by regulating VEGF signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, as well as PI3K/Akt signaling pathway. |
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