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Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology

BACKGROUND: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effecto...

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Autores principales: Zheng, Wen-jiang, Yan, Qian, Ni, Yong-shi, Zhan, Shao-feng, Yang, Liu-liu, Zhuang, Hong-fa, Liu, Xiao-hong, Jiang, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563914/
https://www.ncbi.nlm.nih.gov/pubmed/33082858
http://dx.doi.org/10.1186/s13040-020-00227-6
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author Zheng, Wen-jiang
Yan, Qian
Ni, Yong-shi
Zhan, Shao-feng
Yang, Liu-liu
Zhuang, Hong-fa
Liu, Xiao-hong
Jiang, Yong
author_facet Zheng, Wen-jiang
Yan, Qian
Ni, Yong-shi
Zhan, Shao-feng
Yang, Liu-liu
Zhuang, Hong-fa
Liu, Xiao-hong
Jiang, Yong
author_sort Zheng, Wen-jiang
collection PubMed
description BACKGROUND: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ on COVID-19 based on network pharmacology. METHODS: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. We used AutoDock vina and PyMOL software for molecular docking. RESULTS: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values > 40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “drug-ingredient-target-pathway” effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than − 4.0 with those top 10 targets. CONCLUSION: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.
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spelling pubmed-75639142020-10-16 Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology Zheng, Wen-jiang Yan, Qian Ni, Yong-shi Zhan, Shao-feng Yang, Liu-liu Zhuang, Hong-fa Liu, Xiao-hong Jiang, Yong BioData Min Research BACKGROUND: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ on COVID-19 based on network pharmacology. METHODS: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. We used AutoDock vina and PyMOL software for molecular docking. RESULTS: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values > 40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “drug-ingredient-target-pathway” effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than − 4.0 with those top 10 targets. CONCLUSION: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease. BioMed Central 2020-10-16 /pmc/articles/PMC7563914/ /pubmed/33082858 http://dx.doi.org/10.1186/s13040-020-00227-6 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
Zheng, Wen-jiang
Yan, Qian
Ni, Yong-shi
Zhan, Shao-feng
Yang, Liu-liu
Zhuang, Hong-fa
Liu, Xiao-hong
Jiang, Yong
Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology
title Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology
title_full Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology
title_fullStr Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology
title_full_unstemmed Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology
title_short Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology
title_sort examining the effector mechanisms of xuebijing injection on covid-19 based on network pharmacology
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563914/
https://www.ncbi.nlm.nih.gov/pubmed/33082858
http://dx.doi.org/10.1186/s13040-020-00227-6
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