Mechanism of Wulingsan in Treatment of Rheumatoid Arthritis Based on Network Pharmacology

Kai QIAN; Yan-yi DU; Long-yin HAN; Zhen-quan WEI; Wen-guang HUANG; Li-ying ZENG; Shu-di XU; Min-ying LIU; Chang-song LIN

doi:10.13422/j.cnki.syfjx.20191802

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Mechanism of Wulingsan in Treatment of Rheumatoid Arthritis Based on Network Pharmacology

Data Mining | 更新时间：2021-02-09

- Mechanism of Wulingsan in Treatment of Rheumatoid Arthritis Based on Network Pharmacology
- Chinese Journal of Experimental Traditional Medical Formulae Vol. 25, Issue 19, Pages: 138-146(2019)
- 作者机构：
  
  1.广州中医药大学，广州　 510405；
  2.广州中医药大学　第一附属医院，广州　 510405
- 作者简介：
- 基金信息：
- DOI：10.13422/j.cnki.syfjx.20191802
  CLC： R2-0; R22; R285.5; R289
- Received：15 March 2019，
  
  Published Online：04 June 2019，
  
  Published：05 October 2019
- 稿件说明：
移动端阅览
Kai QIAN, Yan-yi DU, Long-yin HAN, et al. Mechanism of Wulingsan in Treatment of Rheumatoid Arthritis Based on Network Pharmacology[J]. Chinese journal of experimental traditional medical formulae, 2019, 25(19): 138-146.
DOI：

Kai QIAN, Yan-yi DU, Long-yin HAN, et al. Mechanism of Wulingsan in Treatment of Rheumatoid Arthritis Based on Network Pharmacology[J]. Chinese journal of experimental traditional medical formulae, 2019, 25(19): 138-146. DOI： 10.13422/j.cnki.syfjx.20191802.

摘要

目的：

采用网络药理学的方法，对五苓散(WLS)治疗类风湿关节炎(RA)的作用机制进行研究探讨。

方法：

通过在中药系统药理学数据库(TCMSP)平台对五苓散进行活性成分筛选、在DragBank数据库进行靶点预测，应用Cytoscape 3.2.1软件构建成分-靶点网络；在TTD，DrugBank及DisGenet数据库中进行检索，获取疾病靶点；构建韦恩图，得到五苓散治疗RA的作用靶点；并进行基因本体(GO)功能注释和东京基因组百科全书(KEGG)通路富集分析；构建五苓散中药-成分-靶点-信号通路网络，使用Network Analyzer进行网络特征分析。

结果：

研究显示共挖掘到五苓散中52种成分及297个潜在靶点，RA疾病1 845个相关靶点，得到五苓散-疾病共同靶点49个，共同作用靶点主要富集于322个生物过程和31条信号通路上。

结论：

五苓散可能是通过调节前列素内环氧化物合成酶2(PTGS2)，转化生长因子-

(TGF-

)，半胱氨酸天冬氨酸蛋白水解酶-3(Caspase-3)，转录因子p65(RELA)，孕激素受体(PGR)等靶点，调控癌症相关通路，肿瘤坏死因子(TNF)信号通路，白细胞介素17(IL-17)信号通路，核转录因子-

B(NF-

B)信号通路，Th17细胞分化等通路，从而抑制炎症反应、调节免疫功能及调控细胞凋亡来治疗类风湿关节炎。

Abstract

Objective:

To study the mechanism of Wulingsan (WLS) in the treatment of rheumatoid arthritis (RA) by network pharmacology.

Method:

The active components of WLS were screened on traditional Chinese medicine systems pharmacology(TCMSP) platform

and the targets were predicted in DragBank database. The " component-target" network was constructed by Cytoscape 3.2.1 software. Disease targets were searched in TTD

DrugBank and DisGenet databases. The Venn diagram was built to extract the target of WLS in the treatment of RA

and the gene oesthetics(GO) function annotation and Kyoto Encyclopedin of Genes and Genomes(KEGG) signal pathway enrichment analysis were performed by cluego plugin. The TCM-component-target-pathway network of WLS was constructed

and the network feature analysis was made by Network Analyzer.

Result:

Totally 52 components and 297 potential targets in WLS and 1 845 targets relating to RA were excavated

and 49 common targets of WLS-RA were obtained. The common targets were mainly enriched in 322 biological processes and 31 signaling pathways.

Conclusion:

WLS may regulate targets

such as prostaglandin epoxide synthase 2 (PTGS2)

transforming growth factor-

(TGF-

)

cysteine aspartate protein-3 (Caspase-3)

transcription factor p65 (RELA)

progesterone receptor (PGR)

and adjust cancer-related pathways

tumor necrosis factor(TNF) signaling pathways

interleukin-17(IL-17) signaling pathways

nuclear factor-

B(NF-

B) signaling pathways

Th17 cell differentiation

so as to inhibit the inflammatory response

regulate immune function and adjust apoptosis to treat rheumatoid arthritis.

关键词

Keywords

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