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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier GmbH.
2020
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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. |
format | Online Article Text |
id | pubmed-7598573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier GmbH. |
record_format | MEDLINE/PubMed |
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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