Molecular Mechanism of Jingfang Mixture Against H1N1 Influenza Based on Network Pharmacology and Experimental Verification
10.13422/j.cnki.syfjx.20220815
- VernacularTitle:基于网络药理学和实验验证探索荆防合剂治疗甲型H1N1流感的作用机制
- Author:
Wen-ting NI
1
;
Da-long MA
2
;
Jun-jing SHAO
1
;
Yi-ming YIN
1
;
Fang-shu ZHAO
1
;
Bao-hong LI
1
;
Yun-hong SUN
1
;
Xiao-qing WANG
1
;
Xiao-ping ZHANG
1
;
Jing-zhen TIAN
1
Author Information
1. Shandong University of Traditional Chinese Medicine，Jinan 250355，China
2. The Affiliated Hospital of Qingdao University，Qingdao 266005，China
- Publication Type:Journal Article
- Keywords:
Jingfang mixture;
H1N1 influenza;
network pharmacology;
molecular docking;
experimental verification
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2022;28(12):200-209
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo predict the potential targets and mechanism of Jingfang mixture in the treatment of H1N1 influenza and provide references for clinical application of Jingfang mixture. MethodThe active components and targets of Jingfang mixture against H1N1 influenza were screened out by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform（TCMSP），SwissTargetPrediction， and TargetNet. The targets of H1N1 influenza were obtained from GeneCards，Online Mendelian Inheritance in Man （OMIM）， and DisGeNET and standardized by UniProt KB. The intersection targets were obtained by Venny 2.1.0. The "drug-component-target" network was constructed with Cytoscape 3.2.1 and analyzed for the topological attributes. The intersection targets were uploaded to STRING 11.5 to obtain the protein-protein interaction （PPI） network. Gene Ontology （GO） enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） analysis were carried out by Metascape. Finally，the top active components ranked by degree were docked to the core targets by Autodock vina and visually analyzed by PyMOL. Balb/c female rats were used for experimental verification. Hematoxylin-eosin（HE） staining was used to observe the pathological changes in lung tissues. Enzyme-linked immunosorbent assay（ELISA）was used to detect the levels of tumor necrosis factor-α（TNF-α），interleukin-10（IL-10）， and interleukin-17（IL-17）. Real-time fluorescence-based quantitative polymerase chain reaction（Real-time PCR） and Western blot were used to detect the mRNA and protein expression levels in lung tissues. ResultThere were 144 active components in Jingfang mixture. A total of 421 target genes of Jingfang mixture and 2 956 targets of H1N1 influenza were identified，including 199 common targets. Topological analysis showed that the core components of Jingfang mixture against H1N1 influenza included quercetin，luteolin， and kaempferol，and the core targets included prostaglandin-endoperoxide synthase 2（PTGS2），estrogen receptor alpha（ESR1），inducible nitric oxide synthase 2（iNOS2），peroxisome proliferator-activated receptorγ（PPARγ），and cyclooxygenase-1（PTGS1）. GO enrichment yielded 697 items in biological process （BP） （P<0.01）， 59 items in molecular function （MF）（P<0.01）， and 21 items in cellular component （CC） （P<0.01）. A total of 132 signaling pathways （P<0.01） were obtained by KEGG enrichment analysis， including phosphatidylinositol 3-kinases（PI3K）/protein kinase B（Akt） signaling pathway and mitogen-activated protein kinase（MAPK） signaling pathway，most of which were related to the regulation of immune inflammation. Molecular docking showed that the binding energy of the active components of Jingfang mixture to the core targets was less than -5.0 kcal·mol-1，indicating good binding activity. HE staining showed that the lung tissues were significantly improved after drug intervention，and Real-time PCR and Western blot showed that Jingfang mixture could reduce the mRNA and protein expression of PI3K and Akt in lung tissues. ConclusionJingfang mixture can play an anti-viral effect against the influenza A virus through multiple components，multiple targets， and multiple pathways. The active components quercetin，luteolin， and kaempferol may control the inflammation and regulate immunity on the PI3K/Akt，MAPK， and other signaling pathways by acting on targets such as PTGS2，ESR1，iNOS2，PPARγ， and PTGS1.
