The core traditional Chinese medicines and mechanism of traditional Chinese medicine enema treatment of chronic kidney disease based on data mining and network pharmacology
- VernacularTitle: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
- Author:
Yiming CUI
1
;
Guijun PENG
2
;
Xin HU
1
;
Linyu HE
1
;
Yu WU
1
Author Information
- Publication Type:Journal Article
- Keywords: chronic kidney disease; network pharmacology; GO; KEGG; Chinese medicine enema; molecular docking
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2022;43(2):286-296
- CountryChina
- Language:Chinese
- Abstract: 【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， neocryptotanshinone Ⅱ and emodin”. It is predicted that it may play a role in “PI3K Akt signal pathway， MAPK signal pathway， JAK-STAT signal pathway”. Molecular docking showed that the key components have good binding activity with key targets. 【Conclusion】 Based on data mining and network pharmacology， traditional Chinese medicine enema treatment of CKD mainly uses rhubarb as the main drug， assisting warming yang to remove blood stasis and turbidity relief drugs. The key components of its core drug can act on PI3K-Akt by regulating key targets such as PIK3R1. Signal pathways and other pathways play a role in providing new ideas for the treatment of this disease with traditional Chinese medicine enema， medication strategies for clinical prescriptions， and a basis for follow-up further research.
