Mechanism of action of Scutellaria baicalensis in treating rheumatoid arthritis：An analysis based on network pharmacology and molecular docking

doi:10.3969/j.issn.2096-3351.2021.04.003

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Mechanism of action of Scutellaria baicalensis in treating rheumatoid arthritis：An analysis based on network pharmacology and molecular docking

更新时间：2023-04-16

- Mechanism of action of Scutellaria baicalensis in treating rheumatoid arthritis：An analysis based on network pharmacology and molecular docking
- Journal of Southwest Medical University Vol. 44, Issue 4, Pages: 314-324(2021)
- 作者机构：
  
  安徽中医药大学中医学院,合肥,230038
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.2096-3351.2021.04.003
  CLC：
- Published：2021，
  
  Published Online：20 July 2021，
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Mechanism of action of Scutellaria baicalensis in treating rheumatoid arthritis：An analysis based on network pharmacology and molecular docking. [J]. Journal of Southwest Medical University 44(4):314-324(2021)
DOI：

Mechanism of action of Scutellaria baicalensis in treating rheumatoid arthritis：An analysis based on network pharmacology and molecular docking. [J]. Journal of Southwest Medical University 44(4):314-324(2021) DOI： 10.3969/j.issn.2096-3351.2021.04.003.

摘要

目的利用网络药理学和分子对接探索黄芩治疗类风湿关节炎（rheumatoidarthritis，RA）的作用机制。方法运用中药系统药理学分析平台（TCMSP）筛选黄芩的有效成分及相应的靶蛋白，通过Genecards、OMIM数据库筛选出RA的靶点，利用Venn在线软件获取药物与疾病的共同靶点，并使用Cytoscape3.7.2软件构建“有效成分-靶点-疾病”网络图。使用String数据库绘制蛋白互作（PPI）网络，利用Cytoscape中的CytoNCA对RA靶点进行打分，得到网络核心靶蛋白，并与筛选后的黄芩潜在有效成分逐一进行分子对接。最后利用David数据库对有效作用靶点进行GO功能和KEGG通路富集分析。结果筛选出黄芩化合物共计36个，有效作用靶点96个。通过Venn图获得44个药物-疾病共同靶点，PPI网络发现IL-6、VEGFA、PTGS2、FOS、JUN、MMP9等为黄芩治疗RA的关键靶点。GO功能分析发现75个条目，涉及生长因子活性、生物合成过程调控、酶活性、转录因子活性及受体活性、细胞因子活性等方面。KEGG通路分析发现24个条目，涉及细胞凋亡、PI3K-AKT、MAPK、HIF-1、破骨细胞分化、细胞衰老、趋化因子等信号通路。分子对接结果显示PTGS2、ESR1、RELA分别与黄连碱、表小檗碱、刺槐素等多个黄芩活性成分具有较好的结合性，提示黄芩可通过PTGS2、ESR1、RELA干预RA的活动。结论黄芩通过多成分、多靶点、多途径发挥治疗RA作用，为研究其物质基础及作用机制奠定了基础，为临床用药提供了新思路。

Abstract

Objective To analyze the mechanism of action of Scutellaria baicalensis in the treatment of rheu⁃matoid arthritis（RA）using network pharmacology and molecular docking. Methods We screened for effective components of S. baicalensis and the corresponding target proteins through the Traditional Chinese Medicine Sys⁃tems Pharmacology Database and Analysis Platform，and screened for the targets of RA through the GeneCards and Online Mendelian Inheritance in Man databases. Online Venn software was used to determine the common targets of the drug and the disease. Cytoscape 3.7.2 software was used to visualize the effective component-target-disease net⁃work. A protein-protein interaction（PPI）network was plotted using the String database. CytoNCA，a plugin of Cyto⁃scape，was used to score the targets of RA to determine the core target proteins of the network. Molecular docking was conducted for the core target proteins and the potential active components of S. baicalensis screened out. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed on the effective targets using

关键词

黄芩类风湿关节炎网络药理学作用机制信号通路

Keywords

Scutellaria baicalensisRheumatoid arthritisNetwork pharmacologyMechanism of actionSignaling pathway

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