Mechanism of Xiao Banxiatang in Preventing Chemotherapy-induced Nausea and Vomiting Based on Network Pharmacology

Si-qi CHEN; Ke NIE

doi:10.13422/j.cnki.syfjx.20192304

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Mechanism of Xiao Banxiatang in Preventing Chemotherapy-induced Nausea and Vomiting Based on Network Pharmacology

Data Mining | 更新时间：2021-02-09

- Mechanism of Xiao Banxiatang in Preventing Chemotherapy-induced Nausea and Vomiting Based on Network Pharmacology
- Chinese Journal of Experimental Traditional Medical Formulae Vol. 26, Issue 3, Pages: 156-165(2020)
- 作者机构：
  
  广东药科大学　中药学院，广州　 510006
- 作者简介：
- 基金信息：
- DOI：10.13422/j.cnki.syfjx.20192304
  CLC： R2-0; R22; R285.5; R289
- Published：05 February 2020，
  
  Published Online：20 August 2019，
  
  Received：29 May 2019，
- 稿件说明：
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Si-qi CHEN, Ke NIE. Mechanism of Xiao Banxiatang in Preventing Chemotherapy-induced Nausea and Vomiting Based on Network Pharmacology. [J]. Chinese Journal of Experimental Traditional Medical Formulae 26(3):156-165(2020)
DOI：

Si-qi CHEN, Ke NIE. Mechanism of Xiao Banxiatang in Preventing Chemotherapy-induced Nausea and Vomiting Based on Network Pharmacology. [J]. Chinese Journal of Experimental Traditional Medical Formulae 26(3):156-165(2020) DOI： 10.13422/j.cnki.syfjx.20192304.

摘要

目的：

运用网络药理学探讨小半夏汤防治化疗性恶心呕吐机制。

方法：

通过药物作用靶点数据库(TTD)，Drugbank数据库和DisGeNET数据库收集化疗性恶心呕吐的靶点，经Uniprot数据库对靶点基因进行标准化；在中药系统药理学数据库与分析平台数据库(TCMSP)中按口服生物利用度(OB)≥30%，类药性(DL)≥0.14条件并结合文献研究筛选出半夏、生姜的有效成分，通过PubChem数据库，ALOGPS2.1数据库和SwissTargetPrediction数据库收集半夏、生姜靶点并经Uniprot数据库标准化；通过DRAR-CPI数据库对重要成分6-姜酚进行分子反向对接；通过DAVID 6.8数据库进行基因本体(GO)分析和京都基因与基因组百科全书(KEGG)通路分析；通过Cytoscape3.2.1软件绘制关系图并进行网络拓扑参数分析；通过ImageGP工具绘制GO和KEGG气泡图。

结果：

获得化疗性恶心呕吐148个靶点，小半夏汤27个有效成分，其中22个与化疗性恶心呕吐相关，38个防治靶点，GO分析67个生物学过程，11个细胞组分，18个分子功能，21条KEGG通路，包括环腺苷酸(cAMP)信号通路、钙离子信号通路及Rap1信号通路等。

结论：

基于网络药理学对化疗性恶心呕吐、小半夏汤进行分析，为探讨小半夏汤防治化疗性恶心呕吐机制提供思路。

Abstract

Objective:

To explore the mechanism of Xiao Banxiatang in preventing and treating chemotherapy-induced nausea and vomiting by using network pharmacology.

Method:

The targets of chemotherapy-related nausea and vomiting were collected by therapeutic target database (TTD)

Drugbank database and DisGeNET database. The target genes were normalized by Uniprot database. The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was selected according to oral bioavailabilityc (OB) ≥ 30%

drug-likeness (DL) ≥ 0.14 and the literature research. The active constituents of pinellia ternata and ginger were collected through the PubChem database

the ALOGPS2.1 database and the Swiss Target Prediction database

and the target of ginger was collected and standardized through the Uniprot database

the molecular inverse docking of the important component 6-gingerol was carried out through the DRAR-CPI database

gene ontology (GO) analysis and kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed through DAVID 6.8 database

and relationship diagrams were drawn by Cytoscape 3.2.1 software and network topology parameters were analyzed

GO and KEGG bubble maps were drawn by ImageGP tool.

Result:

A total of 148 targets for chemotherapeutic nausea and vomiting

and 27 active ingredients of Xiao Banxiatang were collected

including 22 associated with chemotherapeutic nausea and vomiting

38 control targets

67 biological processes based on GO analysis

11 cell components

18 molecular functions

21 KEGG pathways

involving cyclic Adenosine monophosphate (cAMP) signaling pathway

calcium signaling pathway

Rap1 signaling pathway.

Conclusion:

Based on network pharmacology

chemotherapy-related nausea and vomiting and Xiao Banxiatang were analyzed to provide ideas for the prevention and treatment of chemotherapy-induced nausea and vomiting.

关键词

小半夏汤化疗性恶心呕吐网络药理学通路富集靶点相互作用

Keywords

Xiao Banxiatangchemotherapy-related nausea and vomitingnetwork pharmacologypathway enrichmenttarget interaction

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