Network pharmacology research of mechanism of Maxing Shigan Decoction in treating COVID-19

Xian-Fang Wang, Zhi-Yong Du, Qi-Meng Li, Yi-Feng Liu, Shao-Hui Ma, Jui-Wei Cui

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Quant. Biol. ›› 2023, Vol. 11 ›› Issue (1) : 94-103. DOI: 10.15302/J-QB-022-0307
RESEARCH ARTICLE

Network pharmacology research of mechanism of Maxing Shigan Decoction in treating COVID-19

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Abstract

Background: The COVID-19 has a huge negative impact on people’s health. Traditional Chinese Medicine (TCM) has a good effect on viral pneumonia. It is of great practical significance to study its pharmacology.

Methods: The ingredients and targets of each herb in Maxing Shigan Decoction which obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and the related targets of COVID-19 were screened by GeneCards database based on the network pharmacology. Venn was used to analyze the intersection target between active ingredients and diseases. Cytoscape software was used to construct an active ingredient-disease target network. The Protein-Protein Interaction network was constructed by STRING database and Cytohubba was used to screen out the key targets. Gene Ontology (GO) functional enrichment analysis and KEGG pathway analysis were performed by David database.

Results: In this study, a total of 134 active ingredients and 229 related targets, 198 targets of COVID-19 and 48 common targets of drug-disease were chosen. Enrichment items and pathways were obtained through GO and KEGG pathway analysis. The predicted active ingredients were quercetin, kaempferol, luteolin, naringenin, glycyrol, and the key targets involved IL6, MAPK3, MAPK8, CASP3, IL10, etc. The results showed that the active ingredients of Maxing Shigan Decoction acted on multiple targets which played roles in the treatment of COVID-19 by regulating inflammation, immune system and other pathways.

Conclusions: The main contribution of this paper is to use data to mine the principles of the treatment of COVID-19 from the pharmacology of these prescriptions, and the results can be provided theoretical reference for medical workers.

Author summary

This paper studied the mechanism of a classical TCM prescription Maxing Shigan Decoction in the treatment of COVID-19 based on network pharmacology. The main active ingredients of Maxing Shigan Decoction were obtained by analyzing the network, such as quercetin, kaempferol, luteolin, naringenin. The key targets of COVID-19 were obtained, such as IL6, MAPK3, MAPK8, CASP3, IL10. The Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed. It was concluded that multiple active ingredients act on key targets through regulating inflammatory and immune-related signaling pathways, and the mechanism of Maxing Shigan Decoction in treating COVID-19 was expounded, which has some theoretical and practical significance.

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Keywords

network pharmacology / PPI / Maxing Shigan Decoction / COVID-19 / target

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Xian-Fang Wang, Zhi-Yong Du, Qi-Meng Li, Yi-Feng Liu, Shao-Hui Ma, Jui-Wei Cui. Network pharmacology research of mechanism of Maxing Shigan Decoction in treating COVID-19. Quant. Biol., 2023, 11(1): 94‒103 https://doi.org/10.15302/J-QB-022-0307

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ACKNOWLEDGEMENTS

This work was supported by the National Natural Science Foundation of China (Nos. 62072157 and 61802116), the Natural Science Foundation of Henan province (202300410102), the Doctoral program of Henan Institute of Technology (KQ2002), and the Science and Technology Research Key Project of Henan Province (No. 192102210113).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Xian-Fang Wang, Zhi-Yong Du, Qi-Meng Li, Yi-Feng Liu, Shao-Hui Ma and Jui-Wei Cui declare that they have no conflict of interest or financial conflicts to disclose.
All procedures performed in this study were in accordance with the ethical standards of the institution or practice at which the studies were conducted, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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This article is licensed by the CC By under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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2023 The Author (s). Published by Higher Education Press.
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