Therapeutic Mechanism of Xiaoqinglong Decoction against COVID-19 Based on Network Pharmacology and Molecular Docking Technology.


Journal

Combinatorial chemistry & high throughput screening
ISSN: 1875-5402
Titre abrégé: Comb Chem High Throughput Screen
Pays: United Arab Emirates
ID NLM: 9810948

Informations de publication

Date de publication:
2022
Historique:
received: 29 10 2021
revised: 20 11 2021
accepted: 14 12 2021
pubmed: 2 3 2022
medline: 28 9 2022
entrez: 1 3 2022
Statut: ppublish

Résumé

A xiaoqinglong decoction (XQLD) has been proven effective in treating severe coronavirus disease 2019 (COVID-19) cases; however, the mechanism remains unclear. In the current study, we used network pharmacology and molecular docking technology to identify the effective components, potential targets, and biological pathways of XQLD against COVID-19. Public databases were searched to determine the putative targets of the active compounds of XQLD and COVID-19-related targets. STRING and Cytoscape were used to establish the protein-protein interaction network and drug component, along with the target-pathway network. The DAVID database was used to enrich the biological functions and signaling pathways. AutoDock Vina was used for virtual docking. We identified 138 active compounds and 259 putative targets of XQLD. Biological network analysis showed that quercetin, beta-sitosterol, kaempferol, stigmasterol, and luteolin may be critical ingredients of XQLD, whereas VEGFA, IL-6, MAPK3, CASP3, STAT3, MAPK1, MAPK8, CASP8, CCL2, and FOS may be candidate drug targets. Enrichment analysis illustrated that XQLD could function by regulating viral defense, inflammatory response, immune response, and apoptosis. Molecular docking results showed a high affinity between the critical ingredients and host cell target proteins. This study uncovered the underlying pharmacological mechanism of XQLD against COVID-19. These findings lay a solid foundation for promoting the development of new drugs against severe acute respiratory syndrome coronavirus-2 infection and may contribute to the global fight against the COVID-19 pandemic.

Sections du résumé

BACKGROUND
A xiaoqinglong decoction (XQLD) has been proven effective in treating severe coronavirus disease 2019 (COVID-19) cases; however, the mechanism remains unclear.
OBJECTIVE
In the current study, we used network pharmacology and molecular docking technology to identify the effective components, potential targets, and biological pathways of XQLD against COVID-19.
METHODS
Public databases were searched to determine the putative targets of the active compounds of XQLD and COVID-19-related targets. STRING and Cytoscape were used to establish the protein-protein interaction network and drug component, along with the target-pathway network. The DAVID database was used to enrich the biological functions and signaling pathways. AutoDock Vina was used for virtual docking.
RESULTS
We identified 138 active compounds and 259 putative targets of XQLD. Biological network analysis showed that quercetin, beta-sitosterol, kaempferol, stigmasterol, and luteolin may be critical ingredients of XQLD, whereas VEGFA, IL-6, MAPK3, CASP3, STAT3, MAPK1, MAPK8, CASP8, CCL2, and FOS may be candidate drug targets. Enrichment analysis illustrated that XQLD could function by regulating viral defense, inflammatory response, immune response, and apoptosis. Molecular docking results showed a high affinity between the critical ingredients and host cell target proteins.
CONCLUSION
This study uncovered the underlying pharmacological mechanism of XQLD against COVID-19. These findings lay a solid foundation for promoting the development of new drugs against severe acute respiratory syndrome coronavirus-2 infection and may contribute to the global fight against the COVID-19 pandemic.

Identifiants

pubmed: 35227178
pii: CCHTS-EPUB-121177
doi: 10.2174/1386207325666220228154231
doi:

Substances chimiques

Drugs, Chinese Herbal 0
Interleukin-6 0
Kaempferols 0
Stigmasterol 99WUK5D0Y8
Quercetin 9IKM0I5T1E
Caspase 3 EC 3.4.22.-
Luteolin KUX1ZNC9J2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2264-2277

Informations de copyright

Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Auteurs

Hai-Li Li (HL)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

Jian-Peng Zhou (JP)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

Jing-Min Deng (JM)

Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

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Classifications MeSH