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Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) has been widely used as an approach worldwide. Chinese Medicines (CMs) had been used to treat and prevent viral infection pneumonia diseases for thousands of years and had accumulated a large number of clinical experiences and effect...

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Autores principales: Ren, Xia, Shao, Xin-Xin, Li, Xiu-Xue, Jia, Xin-Hua, Song, Tao, Zhou, Wu-Yi, Wang, Peng, Li, Yang, Wang, Xiao-Long, Cui, Qing-Hua, Qiu, Pei-Ju, Zhao, Yan-Gang, Li, Xue-Bo, Zhang, Feng-Cong, Li, Zhen-Yang, Zhong, Yue, Wang, Zhen-Guo, Fu, Xian-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196535/
https://www.ncbi.nlm.nih.gov/pubmed/32376368
http://dx.doi.org/10.1016/j.jep.2020.112932
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author Ren, Xia
Shao, Xin-Xin
Li, Xiu-Xue
Jia, Xin-Hua
Song, Tao
Zhou, Wu-Yi
Wang, Peng
Li, Yang
Wang, Xiao-Long
Cui, Qing-Hua
Qiu, Pei-Ju
Zhao, Yan-Gang
Li, Xue-Bo
Zhang, Feng-Cong
Li, Zhen-Yang
Zhong, Yue
Wang, Zhen-Guo
Fu, Xian-Jun
author_facet Ren, Xia
Shao, Xin-Xin
Li, Xiu-Xue
Jia, Xin-Hua
Song, Tao
Zhou, Wu-Yi
Wang, Peng
Li, Yang
Wang, Xiao-Long
Cui, Qing-Hua
Qiu, Pei-Ju
Zhao, Yan-Gang
Li, Xue-Bo
Zhang, Feng-Cong
Li, Zhen-Yang
Zhong, Yue
Wang, Zhen-Guo
Fu, Xian-Jun
author_sort Ren, Xia
collection PubMed
description ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) has been widely used as an approach worldwide. Chinese Medicines (CMs) had been used to treat and prevent viral infection pneumonia diseases for thousands of years and had accumulated a large number of clinical experiences and effective prescriptions. AIM OF THE STUDY: This research aimed to systematically excavate the classical prescriptions of Chinese Medicine (CM), which have been used to prevent and treat Pestilence (Wenbing, Wenyi, Shiyi or Yibing) for long history in China, to obtain the potential prescriptions and ingredients to alternatively treat COVID-19. MATERIALS AND METHODS: We developed the screening system based on data mining, molecular docking and network pharmacology. Data mining and association network were used to mine the high-frequency herbs and formulas from ancient prescriptions. Virtual screening for the effective components of high frequency CMs and compatibility Chinese Medicine was explored by a molecular docking approach. Furthermore, network pharmacology method was used to preliminarily uncover the molecule mechanism. RESULTS: 574 prescriptions were obtained from 96,606 classical prescriptions with the key words to treat “Warm diseases (Wenbing)”, “Pestilence (Wenyi or Yibing)” or “Epidemic diseases (Shiyi)”. Meanwhile, 40 kinds of CMs, 36 CMs-pairs, 6 triple-CMs-groups existed with high frequency among the 574 prescriptions. Additionally, the key targets of SARS-COV-2, namely 3CL hydrolase (Mpro) and angiotensin-converting enzyme 2(ACE2), were used to dock the main ingredients from the 40 kinds by the LigandFitDock method. A total of 66 compounds components with higher frequency were docked with the COVID-19 targets, which were distributed in 26 kinds of CMs, among which Gancao (Glycyrrhizae Radix Et Rhizoma), HuangQin (Scutellariae Radix), Dahuang (Rhei Radix Et Rhizome) and Chaihu (Bupleuri Radix) contain more potential compounds. Network pharmacology results showed that Gancao (Glycyrrhizae Radix Et Rhizoma) and HuangQin (Scutellariae Radix) CMs-pairs could also interact with the targets involving in immune and inflammation diseases. CONCLUSIONS: These results we obtained probably provided potential candidate CMs formulas or active ingredients to overcome COVID-19. Prospectively, animal experiment and rigorous clinic studies are needed to confirm the potential preventive and treat effect of these CMs and compounds.
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spelling pubmed-71965352020-05-04 Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach Ren, Xia Shao, Xin-Xin Li, Xiu-Xue Jia, Xin-Hua Song, Tao Zhou, Wu-Yi Wang, Peng Li, Yang Wang, Xiao-Long Cui, Qing-Hua Qiu, Pei-Ju Zhao, Yan-Gang Li, Xue-Bo Zhang, Feng-Cong Li, Zhen-Yang Zhong, Yue Wang, Zhen-Guo Fu, Xian-Jun J Ethnopharmacol Article ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) has been widely used as an approach worldwide. Chinese Medicines (CMs) had been used to treat and prevent viral infection pneumonia diseases for thousands of years and had accumulated a large number of clinical experiences and effective prescriptions. AIM OF THE STUDY: This research aimed to systematically excavate the classical prescriptions of Chinese Medicine (CM), which have been used to prevent and treat Pestilence (Wenbing, Wenyi, Shiyi or Yibing) for long history in China, to obtain the potential prescriptions and ingredients to alternatively treat COVID-19. MATERIALS AND METHODS: We developed the screening system based on data mining, molecular docking and network pharmacology. Data mining and association network were used to mine the high-frequency herbs and formulas from ancient prescriptions. Virtual screening for the effective components of high frequency CMs and compatibility Chinese Medicine was explored by a molecular docking approach. Furthermore, network pharmacology method was used to preliminarily uncover the molecule mechanism. RESULTS: 574 prescriptions were obtained from 96,606 classical prescriptions with the key words to treat “Warm diseases (Wenbing)”, “Pestilence (Wenyi or Yibing)” or “Epidemic diseases (Shiyi)”. Meanwhile, 40 kinds of CMs, 36 CMs-pairs, 6 triple-CMs-groups existed with high frequency among the 574 prescriptions. Additionally, the key targets of SARS-COV-2, namely 3CL hydrolase (Mpro) and angiotensin-converting enzyme 2(ACE2), were used to dock the main ingredients from the 40 kinds by the LigandFitDock method. A total of 66 compounds components with higher frequency were docked with the COVID-19 targets, which were distributed in 26 kinds of CMs, among which Gancao (Glycyrrhizae Radix Et Rhizoma), HuangQin (Scutellariae Radix), Dahuang (Rhei Radix Et Rhizome) and Chaihu (Bupleuri Radix) contain more potential compounds. Network pharmacology results showed that Gancao (Glycyrrhizae Radix Et Rhizoma) and HuangQin (Scutellariae Radix) CMs-pairs could also interact with the targets involving in immune and inflammation diseases. CONCLUSIONS: These results we obtained probably provided potential candidate CMs formulas or active ingredients to overcome COVID-19. Prospectively, animal experiment and rigorous clinic studies are needed to confirm the potential preventive and treat effect of these CMs and compounds. Elsevier B.V. 2020-08-10 2020-05-04 /pmc/articles/PMC7196535/ /pubmed/32376368 http://dx.doi.org/10.1016/j.jep.2020.112932 Text en © 2020 Elsevier B.V. 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 Article
Ren, Xia
Shao, Xin-Xin
Li, Xiu-Xue
Jia, Xin-Hua
Song, Tao
Zhou, Wu-Yi
Wang, Peng
Li, Yang
Wang, Xiao-Long
Cui, Qing-Hua
Qiu, Pei-Ju
Zhao, Yan-Gang
Li, Xue-Bo
Zhang, Feng-Cong
Li, Zhen-Yang
Zhong, Yue
Wang, Zhen-Guo
Fu, Xian-Jun
Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach
title Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach
title_full Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach
title_fullStr Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach
title_full_unstemmed Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach
title_short Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach
title_sort identifying potential treatments of covid-19 from traditional chinese medicine (tcm) by using a data-driven approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196535/
https://www.ncbi.nlm.nih.gov/pubmed/32376368
http://dx.doi.org/10.1016/j.jep.2020.112932
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