Abstract: Objective To explore the mechanism of andrographis paniculata treatment for coronavirus disease 2019 (COVID-19) based on network pharmacology. Methods The TCMSP database was used to screen active pharmaceutical ingredients and targets of andropona paniculata. The GeneCards database was applied to search the target of COVID-19. The Uniprot database was applied to standardize the target protein genes. Intersection targets of drug targets and disease targets were taken to obtain potential therapeutic targets, therapeutic targets were imported into String database to construct protein interaction network diagram, and Cytoscape-V3.8.0 software was used for visual analysis. Metascape and DAVID databases were used for GO and KEGG enrichment analysis of treatment targets. Results It was found that there were 24 main active components of Andrographis paniculus, 66 drug targets corresponding to the active components, 259 disease targets for COVID-19, and 18 potential therapeutic targets were obtained from the intersection. Through the construction of protein interaction network diagram, it was concluded that the the most interaction genes were TNF, MAPK14, CASP3, IL6, and PPARG. Two of the most important genes, PPARG and NOS2, are most closely related to the target and the drug. A total of 157 biological processes, 25 molecular functions and 15 cell components were obtained through GO enrichment analysis, mainly including cell response to LPS, glucocorticoid response, inflammatory response, DNA damage, etc. KEGG enriched 86 pathways, such as endogenous and exogenous apoptosis signaling pathway, NOD receptor signaling pathway, influenza A signaling pathway, etc. Conclusion This study suggests that andrographis paniculorum can treat COVID-19 through multiple targets and pathways, and its mechanism may be related on anti-inflammatory, immunological and anti-apoptotic.

Key words: network pharmacology, andrographis paniculata, COVID-19

摘要： 目的 通过网络药理学的方法查找穿心莲重要的活性成分和作用靶点,探讨穿心莲治疗新型冠状病毒性肺炎（COVID-19）的作用机制。方法 应用TCMSP数据库筛选穿心莲的药物活性成分和作用靶点、GeneCards数据库搜索新型冠状病毒性肺炎的靶点,利用Uniprot数据库将靶点蛋白基因标准化。将药物靶点与疾病靶点取交集靶点得到潜在治疗靶点,将治疗靶点导入String数据库构建蛋白相互作用网络图,并利用Cytoscape-v3.8.0软件进行可视化分析。使用metascape和DAVID数据库对治疗靶点进行GO和KEGG富集分析研究。结果 研究发现,穿心莲的主要活性成分共24个,活性成分相对应的药物靶点共66个,COVID-19的疾病靶点共259个,取交集得到潜在治疗靶点共18个。通过构建蛋白交互作用网络图,得出交互作用最多的基因为TNF、MAPK14、CASP3、PPARG。PPARG、NOS2作为其中两个最重要的基因,在靶点与药物之间联系最为紧密。通过GO富集分析共得出157条生物学过程,25条分子功能和15条细胞组分,主要包括细胞对脂多糖的反应、糖皮质激素应答反应、炎症应答反应、DNA损伤等;KEGG富集共得出86条通路,如内外源性细胞凋亡信号通路、NOD样受体信号通路、甲型流感信号通路等。结论 本研究提示穿心莲可通过多靶点、多通路发挥抗炎、调节免疫、抗细胞凋亡的作用,进而起到治疗新型冠状病毒肺炎的作用。

关键词: 网络药理学, 穿心莲, 新型冠状病毒肺炎