基于数据挖掘及网络药理学探讨中药灌肠治疗慢性肾疾病的核心中药及机制  

The core traditional Chinese medicines and mechanism of traditional Chinese medicine enema treatment of chronic kidney disease based on data mining and network pharmacology

作　　者：崔移明 彭贵军[2] 胡心 贺林玉 吴玉 CUI Yiming;PENG Guijun;HU Xin;HE Linyu;WU Yu(The First Clinical Medical College of Henan University of Traditional Chinese Medicine,Zhengzhou 450000;Department of Nephrology,The First Affiliated Hospital of Henan University of Traditional Chinese Medicine,Zhengzhou 450000,China)

机构地区：[1]河南中医药大学第一临床医学院,河南郑州450000 [2]河南中医药大学第一附属医院肾病科,河南郑州450000

出　　处：《西安交通大学学报（医学版）》2022年第2期286-296,共11页Journal of Xi’an Jiaotong University（Medical Sciences）

基　　金：河南省中医药科学研究专项课题(No.2018JDZX016)。

摘　　要：目的基于数据挖掘及网络药理学,分析和挖掘中国知网(CNKI)平台期刊刊发的中药灌肠治疗慢性肾脏病(chronic kidney disease,CKD)有效中药处方的用药规律,寻找高频核心中药,预测核心中药的潜在靶点,以探讨核心中药治疗CKD的作用机制。方法以CNKI为数据来源,检索中药灌肠治疗CKD的中医临床文献,采用SPSS Modeler 18.0统计软件,进行统计处理和关联规则分析,采用IBM SPSS Statistics 21统计软件进行聚类分析,应用BATMAN-TCM及TCMSP检索药物的有效成分及靶点,通过Genecards、OMIN、Drugbank、DisGenet、TTD、PharmGkb数据库检索疾病相关靶点,利用Venny平台筛选疾病、药物交集靶点,利用STRING数据库获取相关文件,利用Cytoscape 3.8.2软件进行可视化分析,使用Metascape数据库进行富集分析,使用微生信网站绘制气泡图,利用AutoDockTools-1.5.6软件进行分子对接预测。结果筛选有效率≥85%的中药灌肠方,共筛选出有效处方276首,涉及120味中药,19味中药频次≥10,得到18个核心药物组合,聚类分析可分成4类。可视化网络分析示“大黄、蒲公英、牡蛎、丹参、附子”关联度较高,位居核心地位,对5种核心药物的潜在靶点进行预测,得到“药物-疾病”交集靶点659个,核心靶点173个,其中“MAPK1、AKT1、STAT3”等为关键靶点,“Progesterone、neocryptotanshinone ii、Emodin”等为核心药物治疗本病的关键成分,预测其可能作用于PI3K-Akt信号通路、MAPK信号通路、Jak-STAT信号通路等发挥作用。分子对接表明关键成分与关键靶点结合活性较好。结论基于数据挖掘及网络药理学,中药灌肠治疗CKD主要以大黄为主药,辅助温阳化瘀泄浊类药物,其核心药物的关键成分可通过调控PIK3R1等关键靶点,作用于PI3K-Akt等信号通路发挥作用;本研究为中药灌肠治疗CKD提供新思路及为临床组方用药提供用药策略,为后续进一步研究提供基础。Objective To analyze and mine the prescription rules of traditional Chinese medicine enema treatment of chronic kidney disease(CKD)in CNKI platform journals based on data mining and network pharmacology so as to find high-frequency core Chinese medicines and predict the potential targets of core Chinese medicines and explore the mechanism of action of core Chinese medicines in the treatment of CKD.Methods Taking CNKI as the data source,we retrieved the clinical literature of traditional Chinese medicine enema in the treatment of CKD.SPSS modeler 18.0 statistical software was used for statistical processing and association rule analysis.IBM SPSS statistics 21 statistical software was used for cluster analysis.BATMAN-TCM and TCMSP were used to retrieve the effective components and related targets of drugs.Genecards,OMIN,Drugbank,DisGenet,TTD,and PharmGkb databases were used to retrieve disease-related targets,and Venny platform was used to screen disease and drug intersection targets.We used STRING database to obtain relevant documents,Cytoscape 3.8.2 software for visual analysis,Metascape database for enrichment analysis,Wechat website to draw bubble diagram,and AutoDockTools-1.5.6 software for molecular docking prediction.Results We selected 276 effective prescriptions involving 120 traditional Chinese medicines.The frequency of 19 traditional Chinese medicines was more than 10.Totally 18 core drug combinations were obtained.Cluster analysis could be divided into four categories.The visual net-work analysis shows that“rhubarb,dandelion,oyster,Salvia miltiorrhiza and aconite”are highly correlated and occupy the core position.Through the prediction of the potential targets of five core drugs,659“drug disease”intersection targets and 173 core targets were obtained,of which“MAPK1,AKT1 and STAT3”are the key targets,“progesterone,neocryptotanshinoneⅡand emodin”.It is predicted that it may play a role in“PI3 K Akt signal pathway,MAPK signal pathway,JAK-STAT signal pathway”.Molecular docking showed

关 键 词：慢性肾脏病 网络药理学 GO KEGG 中药灌肠 分子对接 

分 类 号：R285.5[医药卫生—中药学]