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Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis

Xuanbai Chengqi Decoction (XBCQD), a classic traditional Chinese medicine, has been widely used to treat COVID-19 in China with remarkable curative effect. However, the chemical composition and potential therapeutic mechanism is still unknown. Here, we used multiple open-source databases and literat...

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Autores principales: Fan, Liming, Feng, Shuai, Wang, Ting, Ding, Xinli, An, Xinxin, Wang, Zhen, Zhou, Kun, Wang, Minjuan, Zhai, Xifeng, Li, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902854/
https://www.ncbi.nlm.nih.gov/pubmed/35258759
http://dx.doi.org/10.1007/s11030-022-10415-7
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author Fan, Liming
Feng, Shuai
Wang, Ting
Ding, Xinli
An, Xinxin
Wang, Zhen
Zhou, Kun
Wang, Minjuan
Zhai, Xifeng
Li, Yang
author_facet Fan, Liming
Feng, Shuai
Wang, Ting
Ding, Xinli
An, Xinxin
Wang, Zhen
Zhou, Kun
Wang, Minjuan
Zhai, Xifeng
Li, Yang
author_sort Fan, Liming
collection PubMed
description Xuanbai Chengqi Decoction (XBCQD), a classic traditional Chinese medicine, has been widely used to treat COVID-19 in China with remarkable curative effect. However, the chemical composition and potential therapeutic mechanism is still unknown. Here, we used multiple open-source databases and literature mining to select compounds and potential targets for XBCQD. The COVID-19 related targets were collected from GeneCards and NCBI gene databases. After identifying putative targets of XBCQD for the treatment of COVID-19, PPI network was constructed by STRING database. The hub targets were extracted by Cytoscape 3.7.2 and MCODE analysis was carried out to extract modules in the PPI network. R 3.6.3 was used for GO enrichment and KEGG pathway analysis. The effective compounds were obtained via network pharmacology and bioinformatics analysis. Drug-likeness analysis and ADMET assessments were performed to select core compounds. Moreover, interactions between core compounds and hub targets were investigated through molecular docking, molecular dynamic (MD) simulations and MM-PBSA calculations. As a result, we collected 638 targets from 61 compounds of XBCQD and 845 COVID-19 related targets, of which 79 were putative targets. Based on the bioinformatics analysis, 10 core compounds and 34 hub targets of XBCQD for the treatment of COVID-19 were successfully screened. The enrichment analysis of GO and KEGG indicated that XBCQD mainly exerted therapeutic effects on COVID-19 by regulating signal pathways related to viral infection and inflammatory response. Meanwhile, the results of molecular docking showed that there was a stable binding between the core compounds and hub targets. Moreover, MD simulations and MM-PBSA analyses revealed that these compounds exhibited stable conformations and interacted well with hub targets during the simulations. In conclusion, our research comprehensively explained the multi-component, multi-target, and multi-pathway intervention mechanism of XBCQD in the treatment of COVID-19, which provided evidence and new insights for further research. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11030-022-10415-7.
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spelling pubmed-89028542022-03-09 Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis Fan, Liming Feng, Shuai Wang, Ting Ding, Xinli An, Xinxin Wang, Zhen Zhou, Kun Wang, Minjuan Zhai, Xifeng Li, Yang Mol Divers Original Article Xuanbai Chengqi Decoction (XBCQD), a classic traditional Chinese medicine, has been widely used to treat COVID-19 in China with remarkable curative effect. However, the chemical composition and potential therapeutic mechanism is still unknown. Here, we used multiple open-source databases and literature mining to select compounds and potential targets for XBCQD. The COVID-19 related targets were collected from GeneCards and NCBI gene databases. After identifying putative targets of XBCQD for the treatment of COVID-19, PPI network was constructed by STRING database. The hub targets were extracted by Cytoscape 3.7.2 and MCODE analysis was carried out to extract modules in the PPI network. R 3.6.3 was used for GO enrichment and KEGG pathway analysis. The effective compounds were obtained via network pharmacology and bioinformatics analysis. Drug-likeness analysis and ADMET assessments were performed to select core compounds. Moreover, interactions between core compounds and hub targets were investigated through molecular docking, molecular dynamic (MD) simulations and MM-PBSA calculations. As a result, we collected 638 targets from 61 compounds of XBCQD and 845 COVID-19 related targets, of which 79 were putative targets. Based on the bioinformatics analysis, 10 core compounds and 34 hub targets of XBCQD for the treatment of COVID-19 were successfully screened. The enrichment analysis of GO and KEGG indicated that XBCQD mainly exerted therapeutic effects on COVID-19 by regulating signal pathways related to viral infection and inflammatory response. Meanwhile, the results of molecular docking showed that there was a stable binding between the core compounds and hub targets. Moreover, MD simulations and MM-PBSA analyses revealed that these compounds exhibited stable conformations and interacted well with hub targets during the simulations. In conclusion, our research comprehensively explained the multi-component, multi-target, and multi-pathway intervention mechanism of XBCQD in the treatment of COVID-19, which provided evidence and new insights for further research. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11030-022-10415-7. Springer International Publishing 2022-03-08 2023 /pmc/articles/PMC8902854/ /pubmed/35258759 http://dx.doi.org/10.1007/s11030-022-10415-7 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Fan, Liming
Feng, Shuai
Wang, Ting
Ding, Xinli
An, Xinxin
Wang, Zhen
Zhou, Kun
Wang, Minjuan
Zhai, Xifeng
Li, Yang
Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis
title Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis
title_full Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis
title_fullStr Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis
title_full_unstemmed Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis
title_short Chemical composition and therapeutic mechanism of Xuanbai Chengqi Decoction in the treatment of COVID-19 by network pharmacology, molecular docking and molecular dynamic analysis
title_sort chemical composition and therapeutic mechanism of xuanbai chengqi decoction in the treatment of covid-19 by network pharmacology, molecular docking and molecular dynamic analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902854/
https://www.ncbi.nlm.nih.gov/pubmed/35258759
http://dx.doi.org/10.1007/s11030-022-10415-7
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