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Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches
BACKGROUND: The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics da...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8306236/ https://www.ncbi.nlm.nih.gov/pubmed/34301291 http://dx.doi.org/10.1186/s13020-021-00473-8 |
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author | Wang, Biting Wu, Zengrui Li, Weihua Liu, Guixia Tang, Yun |
author_facet | Wang, Biting Wu, Zengrui Li, Weihua Liu, Guixia Tang, Yun |
author_sort | Wang, Biting |
collection | PubMed |
description | BACKGROUND: The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. METHODS: Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein–protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, considering the concentrations of prototype compounds and metabolites of HQD, the critical compound-liver fibrosis target bipartite network was constructed. RESULTS: 68 compounds including 17 prototype components and 51 metabolic products were collected. 540 compound-target interactions were obtained between the 68 compounds and 95 targets. Combining network analysis, molecular docking and concentration of compounds, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis. These interactions would maintain the balance of ECM, reduce liver damage, inhibit hepatocyte apoptosis, and alleviate liver inflammation through five signaling pathways including p53, PPAR, HIF-1, IL-17, and TNF signaling pathway. CONCLUSIONS: This study provides a new way to understand the MoA of HQD on liver fibrosis by considering the concentrations of components and metabolites, which might be a model for investigation of MoA of other Chinese herbs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13020-021-00473-8. |
format | Online Article Text |
id | pubmed-8306236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83062362021-07-28 Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches Wang, Biting Wu, Zengrui Li, Weihua Liu, Guixia Tang, Yun Chin Med Research BACKGROUND: The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. METHODS: Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein–protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, considering the concentrations of prototype compounds and metabolites of HQD, the critical compound-liver fibrosis target bipartite network was constructed. RESULTS: 68 compounds including 17 prototype components and 51 metabolic products were collected. 540 compound-target interactions were obtained between the 68 compounds and 95 targets. Combining network analysis, molecular docking and concentration of compounds, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis. These interactions would maintain the balance of ECM, reduce liver damage, inhibit hepatocyte apoptosis, and alleviate liver inflammation through five signaling pathways including p53, PPAR, HIF-1, IL-17, and TNF signaling pathway. CONCLUSIONS: This study provides a new way to understand the MoA of HQD on liver fibrosis by considering the concentrations of components and metabolites, which might be a model for investigation of MoA of other Chinese herbs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13020-021-00473-8. BioMed Central 2021-07-23 /pmc/articles/PMC8306236/ /pubmed/34301291 http://dx.doi.org/10.1186/s13020-021-00473-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Wang, Biting Wu, Zengrui Li, Weihua Liu, Guixia Tang, Yun Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
title | Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
title_full | Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
title_fullStr | Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
title_full_unstemmed | Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
title_short | Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
title_sort | insights into the molecular mechanisms of huangqi decoction on liver fibrosis via computational systems pharmacology approaches |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8306236/ https://www.ncbi.nlm.nih.gov/pubmed/34301291 http://dx.doi.org/10.1186/s13020-021-00473-8 |
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