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Network Pharmacology and Molecular Docking of Shiwei Qingwen Decoction Reveal TNF as a Potential Target for Alleviating Mild COVID-19 Symptoms
Natural Product Communications ; 17(10), 2022.
Article in English | Web of Science | ID: covidwho-2089021
ABSTRACT

Objective:

Shiwei Qingwen decoction (SWQWD) is effective in preventing COVID-19. This study examined the active components of SWQWD and its potential targets for preventing COVID-19. The study used network pharmacology and molecular docking technology to verify the role of SWQWD targets through animal experiments and explored the mechanisms that enhance immunity to alleviate mild COVID-19 symptoms.

Methods:

First, SWQWD- and COVID-19-related targets were retrieved from TCMSP, GeneCards, and OMIM databases. Second, protein-protein interaction networks were established using the String database. The drug active ingredient target network was constructed in Cytoscape to identify the core target proteins. Third, Gene Ontology (GO) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the SWQWD mechanism of action. Finally, the targets were validated by molecular docking in an acute lung injury (ALI) rat model.

Results:

The SWQWD compound target network contained 79 compounds and 277 targets, coinciding with the 73 targets of COVID-19. The most important gene in the core subnetwork was a tumor necrosis factor (TNF). The 3 most potent compounds, quercetin, kaempferol, and luteolin, can enter the active pockets of TNF and have potential therapeutic roles in COVID-19.

Conclusion:

Quercetin, kaempferol, and luteolin in SWQWD may enhance immunity by regulating multiple TNF signal pathways. After administering SWQWD, the content of tumor necrosis factor-alpha was significantly reduced in the bronchoalveolar lavage fluid (BALF) of ALI rats in comparison to the model group. We believe SWQWD is able to prevent and control COVID-19 through the target of TNF.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Natural Product Communications Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Natural Product Communications Year: 2022 Document Type: Article