黄芪汤治疗慢传输型便秘的作用机制初探  

Preliminary study on the mechanism of Huangqi Decoction in treating slow transit constipation

作　　者：陈华显[1,2,3] 杨超新 肖国中 郑逸晖 雷鸣远 林宏城 Chen Huaxian;Yang Chaoxin;Xiao Guozhong;Zheng Yihui;Lei Mingyuan;Lin Hongcheng(Department of Colorectal Surgery,The Sixth Affiliated Hospital,Sun Yat-sen University,Guangzhou Guangdong 510655,China;Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases,Guangzhou Guangdong 510655,China;Biomedical Innovation Center,The Sixth Affiliated Hospital,Sun Yat-sen University,Guangzhou Guangdong 510655,China)

机构地区：[1]中山大学附属第六医院肛肠外科,广东广州510655 [2]广东省结直肠盆底疾病研究重点实验室,广东广州510655 [3]广州市黄埔区中六生物医学创新研究院,广东广州510655

出　　处：《结直肠肛门外科》2024年第5期570-577,共8页Journal of Colorectal & Anal Surgery

基　　金：国家自然科学基金面上项目(82174369);广东自然科学基金杰出青年项目(2022B1515020003);国家自然科学基金青年项目(82405397);国家资助博士后研究人员计划(GZC20233247);国家临床重点专科。

摘　　要：目的通过网络药理学、分子对接技术及免疫印迹试验,初步探讨黄芪汤治疗慢传输型便秘的作用机制。方法使用TCMSP和SymMap数据库筛选黄芪汤的活性成分和潜在作用靶点,在GeneCards数据库和DisGeNET数据库中检索慢传输型便秘相关靶点,绘制韦恩图取黄芪汤与慢传输型便秘的交集靶点。使用Cytoscape软件绘制“中药-活性成分-靶点-疾病”网络图。使用STRING数据库和Cytoscape软件构建蛋白互作(PPI)网络图,并筛选核心靶点。运用clusterProfiler包对核心靶点进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)功能富集分析。使用AutoDock Vina进行分子对接,PyMOL可视化结果。通过免疫印迹试验检测脂多糖(LPS)+不同浓度的黄芪汤处理的LS174T细胞中p65和p-p65蛋白表达水平。结果通过网络药理学分析得到黄芪汤活性成分174种,潜在作用靶点521个,慢传输型便秘相关靶点1041个,黄芪汤与慢传输型便秘的交集靶点84个。“中药—活性成分—靶点—疾病”网络图显示,黄芪汤排名前5位的活性成分为乙酸、槲皮素、木犀草素、山奈酚、花生四烯酸。核心PPI网络图显示,黄芪汤治疗慢传输型便秘的核心靶点为IL6、IL1B、TNF、IL10、CCL2、ICAM1、TLR4、IFNG、IL1A、MMP9。转录相关靶点为RELA、RB1、NFKBIA、STAT1、RUNX1T1、PPARG、PPARA、RUNX2、PGR、SREBF1。GO功能富集分析结果显示,交集基因主要富集在细菌来源的分子的反应、炎症反应的调控、细胞因子产生的正向调控等生物过程(BP)上,细胞因子受体结合、细胞因子活性等分子功能(MF)上,膜筏、膜微结构域等细胞成分(CC)上。KEGG功能富集分析结果显示,交集基因主要与TNF、MAPK、PI3K-Akt、NF-κB等信号通路有关。分子对接结果显示,黄芪汤的活性成分乙酸、槲皮素、木犀草素、山奈酚、花生四烯酸与p65蛋白具有较好的结合性。免疫印迹试验结果显示,LPS处理组�Objectives To explore the mechanism of Huangqi Decoction in the treatment of slow-transit constipation(STC)is based on network pharmacology,molecular docking technology and Western blot.Methods TCMSP and SymMap databases were used to screen the active ingredients and potential targets of Huangqi Decoction.STC-related targets were searched in GeneCards database and DisGeNET database,and the intersection targets of Huangqi Decoction and STC were obtained by drawing Venn diagram.Use Cytoscape software to construct the“herbal-active ingredients-target-disease”network diagram.The protein interaction(PPI)network diagram was constructed using STRING database and Cytoscape software and core targets were screened.The Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)functional enrichment analyses were performed for core targets using the clusterProfiler package.AutoDock Vina and Py-MOL were used for the molecular docking and the visualization of results.The expression levels of p65 and p-p65 in LS174T cells treated with lipopolysaccharide(LPS)+different concentrations of Huangqi Decoction were detected by Western blot.Results Through network pharmacological analysis,174 active ingredients and 521 potential targets of Huangqi Decoction,1,041 STC-related targets,84 intersection targets of Huangqi Decoction and STC were obtained.The network diagram of“herbal-active ingredients-target-disease”showed that the top 5 active ingredients of Huangqi Decoction were acetic acid,quercetin,luteolin,kaempferol,and arachidonic acid.The core PPI network showed that the core targets of STC treated by Huangqi Decoction were IL6,IL1B,TNF,IL10,CCL2,ICAM1,TLR4,IFNG,IL1A and MMP9.Transcription-related targets RELA,RB1,NFKBIA,STAT1,RUNX1T1,PPARG,PPARA,RUNX2,PGR,SREBF1.The results of GO functional enrichment analysis showed that intersection genes were mainly concentrated in biological processes(BP)such as response to molecule of bacterial origin,regulation of inflammatory response,and positive regulation of cytokine produ

关 键 词：慢传输型便秘 黄芪汤 网络药理学 分子对接 实验验证 

分 类 号：R657.1[医药卫生—外科学]