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Exploring active compounds of Jinhua Qinggan Granules for prevention of COVID-19 based on network pharmacology and molecular docking
Non-conventional | WHO COVID | ID: covidwho-379968
ABSTRACT

Objective:

To explore the effective chemical constituents of Jinhua Qinggan Granules for treatment of coronavirus disease 2019 (COVID-19).

Methods:

The compounds and action targets of eleven herbal medicines in Jinhua Qinggan Granules were collected via TCMSP. The genes corresponding to the targets were queried by the UniProt database, then the “herbal medicine-compound-target” network was established by Cytoscape software. The gene ontology (GO) function enrichment analysis and KEGG pathway enrichment analysis were performed by DAVID to predict their mechanism. Molecular docking was used to analyze the binding force of the core effective compounds in the “herbal medicine-compound-target” network with SARS-CoV-2 3CL hydrolase and angiotensin converting enzyme II (ACE2).

Results:

The “herbal medicine-compound-target” network contained 154 compounds and 276 targets, and the key targets involved PTGS2, HSP90AB1, HSP90AA1, PTGS1, NCOA2, etc. GO function enrichment analysis revealed 278 items, including ATP binding, transcription factor activation and regulation of apoptosis process, etc. KEGG pathway enrichment screened 127 signaling pathways, including TNF, PI3K/Akt and HIF-1 signaling pathways related to lung injury protection. The results of molecular docking showed that formononetin, stigmasterol, beta-sitosterol, anhydroicaritin and other key compounds have a certain degree of affinity with SARS-CoV-2 3CL hydrolase and ACE2.

Conclusion:

The effective compounds in Jinhua Qinggan Granules regulate multiple signaling pathways via binding ACE2 and acting on targets such as PTGS2, HSP90AB1, HSP90AA1, PTGS1, NCOA2 for the prevention of COVID-19.
Full text: Available Collection: Databases of international organizations Database: WHO COVID Type of study: Prognostic study Topics: Traditional medicine Document Type: Non-conventional

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Full text: Available Collection: Databases of international organizations Database: WHO COVID Type of study: Prognostic study Topics: Traditional medicine Document Type: Non-conventional