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Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis

INTRODUCTION: Historically traditional Chinese medicine (TCM) has been used as treatment during epidemics. During the recent COVID-19 pandemic patients evidence suggests that the use of TCM has provided health benefits and has been successfully used to control the spread of the disease in China. The...

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Autores principales: Sun, Xiuli, Jiang, Jinhe, Wang, Yang, Liu, Shuying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier GmbH. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598573/
https://www.ncbi.nlm.nih.gov/pubmed/33163124
http://dx.doi.org/10.1016/j.eujim.2020.101242
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author Sun, Xiuli
Jiang, Jinhe
Wang, Yang
Liu, Shuying
author_facet Sun, Xiuli
Jiang, Jinhe
Wang, Yang
Liu, Shuying
author_sort Sun, Xiuli
collection PubMed
description INTRODUCTION: Historically traditional Chinese medicine (TCM) has been used as treatment during epidemics. During the recent COVID-19 pandemic patients evidence suggests that the use of TCM has provided health benefits and has been successfully used to control the spread of the disease in China. The aim of this study was to systematically explore the TCM formulae which have been used for the prevention and treatment of pneumonia or ‘pestilence’ to investigate their compatibility with the Chinese materia medica (CMM) and understand their potential mechanisms in the treatment of COVID-19. METHODS: Frequency analysis was performed to identify high-frequency CMM and CMM groups. Association rules analysis was applied to investigate the compatibility law of CMMs and generate the commonly used CMM groups. RESULTS: A total of 173 prescriptions were collected. The frequency analysis showed that seven out of ten high-frequency CMMs overlapped with Lianhua Qingwen Capsules (LHQWC), and five high-frequency pair-CMMs and four triple-CMMs were included in LHQWC, respectively. Then three groups of CMM were generated from association rules analysis, one of which is Ma Xing Shi Gan Decoction (MXSGD). The results of the protein-protein interaction network and enrichment analysis showed that the potential therapeutic mechanisms of the generated prescriptions were involved in the anti-inflammatory, anti-viral, and neuroprotective effects. CONCLUSION: This study showed the importance of systematic research on TCM prescriptions and provided candidate CMM groups that have the potential to treat COVID-19. In vitro and in vivo experiments should be conducted to validate these network pharmacology results, which can provide more information for the development of potential antiviral drugs from TCM prescriptions. The combination of TCM treatment and modern medical approaches will benefit patients with COVID-19 and help to overcome the current epidemic.
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spelling pubmed-75985732020-11-02 Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis Sun, Xiuli Jiang, Jinhe Wang, Yang Liu, Shuying Eur J Integr Med Research Paper INTRODUCTION: Historically traditional Chinese medicine (TCM) has been used as treatment during epidemics. During the recent COVID-19 pandemic patients evidence suggests that the use of TCM has provided health benefits and has been successfully used to control the spread of the disease in China. The aim of this study was to systematically explore the TCM formulae which have been used for the prevention and treatment of pneumonia or ‘pestilence’ to investigate their compatibility with the Chinese materia medica (CMM) and understand their potential mechanisms in the treatment of COVID-19. METHODS: Frequency analysis was performed to identify high-frequency CMM and CMM groups. Association rules analysis was applied to investigate the compatibility law of CMMs and generate the commonly used CMM groups. RESULTS: A total of 173 prescriptions were collected. The frequency analysis showed that seven out of ten high-frequency CMMs overlapped with Lianhua Qingwen Capsules (LHQWC), and five high-frequency pair-CMMs and four triple-CMMs were included in LHQWC, respectively. Then three groups of CMM were generated from association rules analysis, one of which is Ma Xing Shi Gan Decoction (MXSGD). The results of the protein-protein interaction network and enrichment analysis showed that the potential therapeutic mechanisms of the generated prescriptions were involved in the anti-inflammatory, anti-viral, and neuroprotective effects. CONCLUSION: This study showed the importance of systematic research on TCM prescriptions and provided candidate CMM groups that have the potential to treat COVID-19. In vitro and in vivo experiments should be conducted to validate these network pharmacology results, which can provide more information for the development of potential antiviral drugs from TCM prescriptions. The combination of TCM treatment and modern medical approaches will benefit patients with COVID-19 and help to overcome the current epidemic. Elsevier GmbH. 2020-12 2020-10-29 /pmc/articles/PMC7598573/ /pubmed/33163124 http://dx.doi.org/10.1016/j.eujim.2020.101242 Text en © 2020 Elsevier GmbH. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Paper
Sun, Xiuli
Jiang, Jinhe
Wang, Yang
Liu, Shuying
Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis
title Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis
title_full Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis
title_fullStr Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis
title_full_unstemmed Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis
title_short Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis
title_sort exploring the potential therapeutic effect of traditional chinese medicine on coronavirus disease 2019 (covid-19) through a combination of data mining and network pharmacology analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598573/
https://www.ncbi.nlm.nih.gov/pubmed/33163124
http://dx.doi.org/10.1016/j.eujim.2020.101242
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