摘要
目的:基于网络药理学探讨复方黄柏液涂剂治疗肛周湿疹的作用机制。方法:本研究依托中药系统药理学数据库和分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,TCMSP),筛选出复方黄柏液涂剂5味中药(连翘、黄柏、金银花、蒲公英、蜈蚣)的化合物及有效靶点,运用Cytoscape软件构建中药-活性成分-靶点网络;在GeneCards数据库中查找“湿疹”疾病相关基因,筛选后共获得相关基因1150个,药物和疾病共有靶点82个。使用String数据库获得蛋白质-蛋白质相互作用(PPI)关系,用Cytoscape软件可视化。根据PPI网络的度值,找出关键作用靶点,采用Metascape网站进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路富集分析。结果:与肛周湿疹相关的化合物-潜在靶点网络共包含20个靶点,涉及免疫调节因子、炎症趋化因子、核受体共激活因子、转录因子等。结论:本研究结果验证和预测了复方黄柏液涂剂治疗肛周湿疹的作用机制及分子靶点,为进一步研究提供了科学依据。
Objective:Based on network pharmacology,the action mechanism of compound Huangbo(Phellodendron chinense schneid)solution on perianal eczema was discussed.Methods:The active ingredients and effective targets of five TCM medicines[Lianqiao(Forsythia),Huangbo,Jinyinhua(Honeysuckle),Pugongying(Dandelion),and Wugong(Centipede)]of compound Huangbo solution were screened out by TCMSP.A network of TCM medicine-active ingredients-targets was constructed by Cytoscape software.The genes related to eczema were screened in GeneCards database,and a total of 1150 genes were obtained.There were 82 common targets for drugs and diseases.The PPI network was obtained by String database and was visualized through Cytoscape software.According to“Degree”value of PPI network,key targets were identified.The GO and KEGG pathway enrichment analysis was carried out through Metascape website.Results:The active ingredient-potential target network related to perianal eczema contained a total of 20 targets,involving immunoregulatory factors,inflammatory chemokine factors,nuclear receptor co-activation factors,transcription factors and so on.Conclusion:The results of this study verify and predict the action mechanism and molecular targets of compound Huangbo solution(复方黄柏液)in treating perianal eczema,and provide a scientific basis for further research.
出处
《中医临床研究》
2022年第4期38-41,共4页
Clinical Journal Of Chinese Medicine
基金
山西省太原市肛肠整复学术流派传承工作室(2020PY-LP-11)。
关键词
网络药理学
复方黄柏液涂剂
肛周湿疹
靶点预测
蛋白质相互作用网络
Network pharmacology
Compound Huangbo solution
Perianal eczema
Target prediction
Protein-protein interaction network