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Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a new global public health emergency. The therapeutic benefits of Cold‒Damp Plague Formula (CDPF) against COVID-19, which was used to treat “cold‒dampness stagnation in the lung” in Trial Versions 6 and 7 of the “Diagnosis and Treatment Protocol for...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391051/ https://www.ncbi.nlm.nih.gov/pubmed/32754224 http://dx.doi.org/10.1186/s13020-020-00360-8 |
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author | Han, Lin Wei, Xiu-Xiu Zheng, Yu-Jiao Zhang, Li-Li Wang, Xin-Miao Yang, Hao-Yu Ma, Xu Zhao, Lin-Hua Tong, Xiao-Lin |
author_facet | Han, Lin Wei, Xiu-Xiu Zheng, Yu-Jiao Zhang, Li-Li Wang, Xin-Miao Yang, Hao-Yu Ma, Xu Zhao, Lin-Hua Tong, Xiao-Lin |
author_sort | Han, Lin |
collection | PubMed |
description | BACKGROUND: Coronavirus disease 2019 (COVID-19) is a new global public health emergency. The therapeutic benefits of Cold‒Damp Plague Formula (CDPF) against COVID-19, which was used to treat “cold‒dampness stagnation in the lung” in Trial Versions 6 and 7 of the “Diagnosis and Treatment Protocol for COVID-19”, have been demonstrated, but the effective components and their mechanism of action remain unclear. METHODS: In this study, a network pharmacology approach was employed, including drug-likeness evaluation, oral bioavailability prediction, protein‒protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and virtual docking, to predict the bioactive components, potential targets, and molecular mechanism of CDPF for COVID-19 treatment. RESULTS: The active compound of herbs in CDPF and their candidate targets were obtained through database mining, and an herbs—ingredients—targets network was constructed. Subsequently, the candidate targets of the active compounds were compared to those relevant to COVID-19, to identify the potential targets of CDPF for COVID-19 treatment. Subsequently, the PPI network was constructed, which provided a basis for cluster analysis and hub gene screening. The seed targets in the most significant module were selected for further functional annotation. GO enrichment analysis identified four main areas: (1) cellular responses to external stimuli, (2) regulation of blood production and circulation, (3) free radical regulation, (4) immune regulation and anti-inflammatory effects. KEGG pathway analysis also revealed that CDPF could play pharmacological roles against COVID-19 through “multi components‒multi targets‒multi pathways” at the molecular level, mainly involving anti-viral, immune-regulatory, and anti-inflammatory pathways; consequently, a “CDPF—herbs—ingredients—targets—pathways—COVID-19” network was constructed. In hub target analysis, the top hub target IL6, and ACE2, the receptor via which SARS-CoV-2 typically enters host cells, were selected for molecular docking analyses, and revealed good binding activities. CONCLUSIONS: This study revealed the active ingredients and potential molecular mechanism by which CDPF treatment is effective against COVID-19, and provides a reference basis for the wider application and further mechanistic investigations of CDPF in the fight against COVID-19. |
format | Online Article Text |
id | pubmed-7391051 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73910512020-07-30 Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking Han, Lin Wei, Xiu-Xiu Zheng, Yu-Jiao Zhang, Li-Li Wang, Xin-Miao Yang, Hao-Yu Ma, Xu Zhao, Lin-Hua Tong, Xiao-Lin Chin Med Research BACKGROUND: Coronavirus disease 2019 (COVID-19) is a new global public health emergency. The therapeutic benefits of Cold‒Damp Plague Formula (CDPF) against COVID-19, which was used to treat “cold‒dampness stagnation in the lung” in Trial Versions 6 and 7 of the “Diagnosis and Treatment Protocol for COVID-19”, have been demonstrated, but the effective components and their mechanism of action remain unclear. METHODS: In this study, a network pharmacology approach was employed, including drug-likeness evaluation, oral bioavailability prediction, protein‒protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and virtual docking, to predict the bioactive components, potential targets, and molecular mechanism of CDPF for COVID-19 treatment. RESULTS: The active compound of herbs in CDPF and their candidate targets were obtained through database mining, and an herbs—ingredients—targets network was constructed. Subsequently, the candidate targets of the active compounds were compared to those relevant to COVID-19, to identify the potential targets of CDPF for COVID-19 treatment. Subsequently, the PPI network was constructed, which provided a basis for cluster analysis and hub gene screening. The seed targets in the most significant module were selected for further functional annotation. GO enrichment analysis identified four main areas: (1) cellular responses to external stimuli, (2) regulation of blood production and circulation, (3) free radical regulation, (4) immune regulation and anti-inflammatory effects. KEGG pathway analysis also revealed that CDPF could play pharmacological roles against COVID-19 through “multi components‒multi targets‒multi pathways” at the molecular level, mainly involving anti-viral, immune-regulatory, and anti-inflammatory pathways; consequently, a “CDPF—herbs—ingredients—targets—pathways—COVID-19” network was constructed. In hub target analysis, the top hub target IL6, and ACE2, the receptor via which SARS-CoV-2 typically enters host cells, were selected for molecular docking analyses, and revealed good binding activities. CONCLUSIONS: This study revealed the active ingredients and potential molecular mechanism by which CDPF treatment is effective against COVID-19, and provides a reference basis for the wider application and further mechanistic investigations of CDPF in the fight against COVID-19. BioMed Central 2020-07-30 /pmc/articles/PMC7391051/ /pubmed/32754224 http://dx.doi.org/10.1186/s13020-020-00360-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Han, Lin Wei, Xiu-Xiu Zheng, Yu-Jiao Zhang, Li-Li Wang, Xin-Miao Yang, Hao-Yu Ma, Xu Zhao, Lin-Hua Tong, Xiao-Lin Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking |
title | Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking |
title_full | Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking |
title_fullStr | Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking |
title_full_unstemmed | Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking |
title_short | Potential mechanism prediction of Cold-Damp Plague Formula against COVID-19 via network pharmacology analysis and molecular docking |
title_sort | potential mechanism prediction of cold-damp plague formula against covid-19 via network pharmacology analysis and molecular docking |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391051/ https://www.ncbi.nlm.nih.gov/pubmed/32754224 http://dx.doi.org/10.1186/s13020-020-00360-8 |
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