Integrating network pharmacology and molecular docking to explore the potential mechanism of Xinguan No. 3 in the treatment of COVID-19
Author:
Peng Jiayan1, Zhang Kun2, Wang Lijie1, Peng Fang1, Zhang Chuantao3, Long Kunlan3, Chen Jun3, Zhou Xiujuan3, Gao Peiyang3, Fan Gang12
Affiliation:
1. State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine , Chengdu 611137 , P. R. China 2. School of Ethnic Medicine, Chengdu University of Traditional Chinese Medicine , Chengdu 611137 , P. R. China 3. Department of Critical Care Medicine, Hospital of Chengdu University of Traditional Chinese Medicine , Chengdu 611130 , P. R. China
Abstract
Abstract
Xinguan No. 3 has been recommended for the treatment of coronavirus disease 2019 (COVID-19); however, its potential mechanisms are unclear. This study aims to explore the mechanisms of Xinguan No. 3 against COVID-19 through network pharmacology and molecular docking. We first searched the ingredients of Xinguan No. 3 in three databases (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Traditional Chinese Medicines Integrated Database, and The Encyclopedia of Traditional Chinese Medicine). The active components and their potential targets were predicted through the SwissTargetPrediction website. The targets of COVID-19 can be found on the GeneCards website. Protein interaction analysis, screening of key targets, functional enrichment of key target genes, and signaling pathway analysis were performed through Search Tool for the Retrieval of Interacting Genes databases, Metascape databases, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, the affinity of the key active components with the core targets was verified by molecular docking. The results showed that five core targets had been screened, including MAPK1, NF-κB1, RELA, AKT1, and MAPK14. Gene ontology enrichment analysis revealed that the key targets were associated with inflammatory responses and responses to external stimuli. KEGG enrichment analysis indicated that the main pathways were influenza A, hepatitis B, Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, and TNF signaling pathway. Therefore, Xinguan No. 3 might play a role in treating COVID-19 through anti-inflammatory, immune responses, and regulatory responses to external stimuli.
Publisher
Walter de Gruyter GmbH
Subject
Materials Chemistry,General Chemistry
Reference47 articles.
1. Gao K, Zhu Y, Wang H, Gong X, Yue Z, Lv A, et al. Network pharmacology reveals the potential mechanism of Baiying Qinghou decoction in treating laryngeal squamous cell carcinoma. Aging (Albany NY). 2021;13(24):26003–21. 10.18632/aging.203786. 2. Li LQ, Huang T, Wang YQ, Wang ZP, Liang Y, Huang TB, et al. COVID‐19 patients’ clinical characteristics, discharge rate, and fatality rate of meta‐analysis. J Med Virol. 2020;92(6):577–83. 3. Ochani R, Asad A, Yasmin F, Shaikh S, Khalid H, Batra S, et al. COVID-19 pandemic: from origins to outcomes. A comprehensive review of viral pathogenesis, clinical manifestations, diagnostic evaluation, and management. Infez Med. 2021;29(1):20–36. 4. Xie J, Ding C, Li J, Wang Y, Guo H, Lu Z, et al. Characteristics of patients with coronavirus disease (COVID‐19) confirmed using an IgM‐IgG antibody test. J Med Virol. 2020;92(10):2004–10. 5. Kevadiya BD, Machhi J, Herskovitz J, Oleynikov MD, Blomberg WR, Bajwa N, et al. Diagnostics for SARS-CoV-2 infections. Nat Mater. 2021;20(5):593–605. 10.1038/s41563-020-00906-z.
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