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10.1016/j.jep.2021.114098

http://scihub22266oqcxt.onion/10.1016/j.jep.2021.114098
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suck abstract from ncbi


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pmid33831468      J+Ethnopharmacol 2021 ; 275 (ä): 114098
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  • In silico analysis of the potential mechanism of a preventive Chinese medicine formula on coronavirus disease 2019 #MMPMID33831468
  • Wu H; Gong K; Qin Y; Yuan Z; Xia S; Zhang S; Yang J; Yang P; Li L; Xie M
  • J Ethnopharmacol 2021[Jul]; 275 (ä): 114098 PMID33831468show ga
  • ETHNOPHARMACOLOGICAL RELEVANCE: With the spread of Coronavirus Disease (2019) (COVID-19), combination with traditional Chinese medicine (TCM) has been widely used as a prevention and therapy strategy in China. Xin guan No.1 (XG-1) prescription is a preventive formula recommended by the Hunan Provincial Administration of TCM to prevent the pandemic of COVID-19. AIM OF THE STUDY: To explore the potential preventive mechanisms of XG-1 against COVID-19 in the combination of network pharmacology approach, single-cell RNA expression profiling analysis, molecular docking and retrospective study. MATERIALS AND METHODS: Encyclopedia of Traditional Chinese Medicine (ETCM) database was used to determine the meridian tropism, active components and target genes of XG-1. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis were conducted by R Cluster Profiler package (3.14.3). Single cell RNA sequencing (scRNA-seq) data of human lung (GSE122960) was downloaded from Gene Expression Omnibus (GEO) database and analyzed by R Seurat package (3.1.2). Cytoscape (3.7.2) was used to construct the interaction network. The main ingredients in XG-1 were identified by HPLC- Q-TOF- MS and used for molecular docking with COVID-19 3CL hydrolytic enzyme and angiotensin converting enzyme II (ACE2). A retrospective study of 47 close contact participants from Dongtang Community of Hunan Province was conducted to evaluated the preventive effect of XG-1. RESULTS: According to the network pharmacology analysis, XG-1 formula was closely related to lung-, spleen- and stomach-meridians and include a total of 206 active components and 853 target genes. GO and KEGG pathway enrichment revealed that XG-1 mainly regulated cellular amino acid metabolism process and neuroactive ligand-receptors interaction. The scRNA-seq profiling showed that angiotensin converting enzyme 2 (ACE2) was principally expressed in alveolar type 2 epithelial cells (AT2). 153 genes were up-regulated in AT2 cells expressing ACE2 and 12 genes were obtained by intersecting with XG-1 target genes, of which 3 were related to immunity. Five main chemical ingredients were detected in XG-1 sample by HPLC-Q-TOF-MS. The molecular docking showed that Rutin, Liquiritin and Astragaloside ? had a good affinity with COVID-19 3CL hydrolytic enzyme and ACE2. Compared with participants who didn't take XG-1, preventive treatment with XG-1gradules resulted in a significant lower rate of testing positive for SARS-CoV-2 nucleic acid (P < 0.0001). CONCLUSION: The present study showed that XG-1 exerts a preventive effect in close contacts against COVID-19. The underlying mechanism may be related to modulate immunity response through multiple components, pathways, and several target genes co-expressed with ACE2. These findings provide preliminary evidences and methodological reference for the potential preventive mechanism of XG-1 against COVID-19.
  • |*COVID-19 Drug Treatment[MESH]
  • |*Medicine, Chinese Traditional[MESH]
  • |Adult[MESH]
  • |Animals[MESH]
  • |Antiviral Agents/*therapeutic use[MESH]
  • |COVID-19/genetics/metabolism/*prevention & control/virology[MESH]
  • |Databases, Genetic[MESH]
  • |Drugs, Chinese Herbal/*therapeutic use[MESH]
  • |Female[MESH]
  • |Gene Expression Profiling[MESH]
  • |Gene Regulatory Networks[MESH]
  • |Host-Pathogen Interactions[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Protein Interaction Maps[MESH]
  • |RNA-Seq[MESH]
  • |Retrospective Studies[MESH]
  • |SARS-CoV-2/*drug effects/pathogenicity[MESH]
  • |Signal Transduction[MESH]
  • |Transcriptome[MESH]


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