摘要
目的:基于网络药理学和生物信息学探讨白头翁汤(BTWT)治疗溃疡性结肠炎(UC)的分子网络调控机制。方法:通过检索中药系统药理学数据库和分析平台(TCMSP),筛选BTWT的入血活性成分和作用靶点;通过GEO数据库获取UC患者与健康人群的显著性差异表达基因;采用Cytoscape构建BTWT活性成分-靶点网络;采用Bisogenet构建BTWT作用靶点蛋白质-蛋白质交互作用(PPI)网络及UC特异性基因PPI网络并提取这两个网络的交集,获得BTWT治疗UC的PPI网络及特征性基因;采用DAVID数据库对BTWT治疗UC的特征性基因进行基因本体(GO)和KEGG信号通路分析;运用Cytohubba筛选BTWT治疗UC的关键靶点。结果:在TCMSP中共检索到与BTWT相关的化学成分247个,依据ADEM参数筛选得到活性成分53个,其中入血活性成分37个,通过检索配对分析,这些成分对应的靶点有643个;从GEO数据库获得UC表达谱数据芯片GSE87466,经过筛选分析得到UC患者特异性表达差异基因279个;进一步分析得到1705个特征性基因参与BTWT治疗UC的过程;GO分析和KEGG通路分析结果表明,BTWT治疗UC主要涉及细胞质、细胞核、细胞连接等分子组成,生物学过程主要包括细胞增殖、迁移和凋亡等,分子功能主要涉及蛋白特异性结合、蛋白酪氨酸激酶活性等;主要富集于MAPK信号通路、趋化因子信号通路、TNF信号通路等;从特征性基因网络中筛选出NTRK1、TP53、APP等10个关键靶点。结论:本研究从网络药理学和生物信息学角度揭示了中药治疗疾病多成分、多靶点和多途径的特点,探究得到BTWT治疗UC的关键靶点及可能分子机制,可为BTWT治疗UC的基础实验与临床研究提供理论依据。
OBJECTIVE To investigate the molecular network regulation mechanism of Bai-Tou-Weng-Tang(BTWT)in the treatment of Ulcerative Colitis(UC)based on network pharmacology and bioinformatics.METHODS The active components and targets of BTWT were screened by searching the pharmacology database and analysis platform of traditional Chinese medicine system(TCMSP);the significantly differentially expressed genes between UC patients and healthy people were obtained by GEO database;the active component-target network of BTWT was constructed by Cytoscape;the protein-protein interaction(PPI)network and UC-specific gene PPI network of BTWT target were constructed by Bisogenet and the intersection of these two networks was extracted to obtain the PPI network and characteristic genes of BTWT in the treatment of UC;the characteristic genes of BTWT in the treatment of UC were analyzed by gene ontology(GO)and KEGG signaling pathway using DAVID database;the key targets of BTWT in the treatment of UC were screened by Cytohubba.RESULTS A total of 247 chemical constituents related to BTWT were retrieved in TCMSP.According to ADEM parameters,and 53 active constituents were screened out,of which 37 were active ingredients in blood.By retrieving pair analysis,643 corresponding targets of these constituents were identified.The data chip GSE87466 of UC expression profile was obtained from GEO database.279 differentially expressed genes(177 up-regulated genes and 102 down-regulated genes)were identified.Through further extraction,1705 characteristic genes involved in the treatment of UC with BTWT were obtained.GO analysis and KEGG pathway analysis showed that BTWT treatment of UC mainly involved in cytoplasm,nucleus,cell junction and other molecular components.The biological process mainly included cell proliferation,migration,and apoptosis.Molecular function mainly involved in protein specific binding,protein tyrosine kinase activity and so on.These genes were mainly concentrated in MAPK signaling pathway,P13K-Akt signaling pathway,chemokine signaling pathway,ErbB receptor signaling pathway,TNF signaling pathway,and neurotrophic signaling pathway.Ten key targets of NTRK1,TP53,APP,EGFR,CuL3,ESR1,FN1,MCM2,HSP90AB1,and UBC were screened from the characteristic gene network.CONCLUSION From the perspective of network pharmacology and bioinformatics,this study reveals the characteristics of multi-component,multi-target and multi-pathway of traditional Chinese medicine in the treatment of diseases,and explores the key targets and possible molecular mechanisms of BTWT in the treatment of UC,which can provide theoretical basis for the basic experiment and clinical research of BTWT in the treatment of UC.
作者
宋厚盼
陈小娟
曾梅艳
陈新怡
朱晓彤
杨焘
李亮
蔡雄
彭清华
SONG Hou-pan;CHEN Xiao-juan;ZENG Mei-yan;CHEN Xin-yi;ZHU Xiao-tong;YANG Tao;LI Liang;CAI Xiong;PENG Qing-hua(Hunan Provincial Key Laboratory of TCM diagnostics,2.College of TCM,3.Medical college,Hunan University of Chinese Medicine,Hunan Changsha 410208,China)
出处
《中国医院药学杂志》
CAS
北大核心
2020年第10期1098-1105,共8页
Chinese Journal of Hospital Pharmacy
基金
国家自然科学基金(编号:81703920)
中国博士后科学基金资助项目(编号:2019M662790)
湖南省自然科学基金(编号:2019JJ50442)
湖南省教育厅科学研究项目一般项目(编号:19C1426)
湖南中医药大学校级科研基金(编号:2018XJJJ28)
湖南中医药大学青年教师科研基金(编号:201610)
湖南省研究生科研创新项目(编号:2018-25)。
关键词
白头翁汤
溃疡性结肠炎
网络药理学
生物信息学
作用机制
Bai-Tou-Weng-Tang
ulcerative colitis
network pharmacology
bioinformatics
mechanism of action
