Exploring mechanism and experimental validation of Gubiao Fanggan Modified Formula in preventing influenza virus in immunosuppressive mice based on network pharmacology
Objective:To invastigate the targets and signaling pathways of Gubiao Fanggan Modified Formula in regulating the defense against influenza A virus in immunosuppressed mice by network pharmacology,and the key targets were verified by immuno-suppressive mice model.Methods:TCMSP database was used to search the active ingredients of Gubiao Fanggan Modified Formula,and GeneCard,OMIM,PharmGkb databases were used to obtain the potential targets of the active ingredients to prevent influenza,and take their intersection targets were taken;STRING11.5 database was used to make protein-protein interaction network analyzed and finded the core targets;Cytoscape3.8.1 was used to build a traditional Chinese medicine-ingredient-disease target network,and GO enrichment analysis and KEGG enrichment analysis were performed.Intraperitoneal injection of cyclophosphamide was used to construct a mouse model of immune function suppression,normal group,model control group,Gubiao Fanggan Modified Formula group and oseltamivir group were set up,followed by prophylactic administration,and influenza virus intervention was performed on the fourth day.After 7 days of intragastric administration,the key targets were verified by mouse spleen index,HE staining,RT-qPCR and immunohistochemistry.Results:There were 82 active ingredients in five traditional Chinese medicines in Gubiao Fanggan Modi-fied Formula,and 72 common targets of drugs and diseases such as IL-6,TNF-α,IL-2,etc,mainly involving IL-17,TNF and AGE-RAGE signaling pathway.Gubiao Fanggan Modified Formula could increase spleen index and significantly reduce mRNA and protein expressions of IL-6 and TNF-α in spleen tissue of mice(P<0.05 or P<0.01).Conclusion:Gubiao Fanggan Modified Formula may regulate body's immune function through targets such as IL-6 and TNF-α,thereby preventing influenza virus infection.
国家科技期刊平台
NSTL
万方数据
