基于网络药理学的青蒿抗风湿作用机制研究

Research on anti-rheumatic mechanism of Artemisiae annuae herba based on network pharmacology

摘要:

目的：基于网络药理学预测青蒿抗风湿的有效成分及作用机制。方法：通过TCMSP数据库筛选青蒿的主要活性成分；运用Gene Cards和OMIM数据库检索风湿作用靶基因，并将其与活性成分作用靶点相互映射获得青蒿活性成分抗风湿靶点，通过STRING平台构建蛋白互作网络。运用DAVID 6.7数据库对青蒿活性成分抗风湿靶点进行GO分类与KEGG通路富集分析，并运用Cytoscape 3.6.1软件构建青蒿活性成分-靶点-信号通路网路预测模型。结果：预测得到青蒿抗风湿的有效成分18个、有效靶点84个，推断其作用机制可能与B细胞受体信号通路、NOD样受体信号通路、T细胞受体信号通路、Toll样受体信号通路等有关，且其中PTGS2、RELA、AR、NOS2、AKT1、MAPK1这6个靶点基因可能起关键性作用。结论：青蒿中山奈酚、槲皮素及木樨草素等活性成分可能通过PTGS2、RELA、AR、NOS2、AKT1、MAPK1 等靶点调节多条信号通路，从而发挥抗风湿作用。

Abstract:

Objective：To predict the effective components and active mechanism of Artemisiae annuae herba against rheumatism based on network pharmacology. Methods：The main active components of the Artemisiae annuae herba were screened by TCMSP database. Furthermore，the target genes were searched by Gene Cards and OMIM database. Meanwhile，the anti-rheumatic target of active components of Artemisiae annuae herba was obtained by mapping it with the active components targets，and the protein-protein interaction network was constructed through the STRING platform. The anti-rheumatic targets of active constituents of Artemisiae annuae herba were classified by GO and analyzed by KEGG pathway enrichment using DAVID 6.7 database，and the prediction model of artemisia annua herba active constituents-target-signal pathway network was constructed by using Cytoscape 3.6.1 software. Results：In this study，a total of 18 effective components and 84 effective targets were predicted，and its mechanism may be related to B cell receptor signaling pathway，NOD-like receptor signaling pathway，T-cell receptor signaling pathway，Toll-like receptor signaling pathway，etc. Among these pathways，six target genes，PTGS2，RELA，AR，NOS2，AKT1，MAPK1，may play crucial roles. Conclusion：The active ingredients such as kaempferol，quercetin and luteolin may regulate multiple signaling pathways through targets such as PTGS2，RELA，AR，NOS2，AKT1 and MAPK1，to play an anti-rheumatic role.