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Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking
According to current research, the primary active ingredients of Radix Astragali (RA), such as saponins, flavonoids, and polysaccharides, play an important role in anti-inflammatory effects. However, the exact molecular mechanism underlying the action was not elucidated to date. Our research attempt...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476849/ https://www.ncbi.nlm.nih.gov/pubmed/37657026 http://dx.doi.org/10.1097/MD.0000000000034945 |
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author | Ren, Jianwei Ding, Yuetian Li, Shangze Lei, Ming |
author_facet | Ren, Jianwei Ding, Yuetian Li, Shangze Lei, Ming |
author_sort | Ren, Jianwei |
collection | PubMed |
description | According to current research, the primary active ingredients of Radix Astragali (RA), such as saponins, flavonoids, and polysaccharides, play an important role in anti-inflammatory effects. However, the exact molecular mechanism underlying the action was not elucidated to date. Our research attempted to determine the active components in RA and to investigate the interaction between the active components and targets involved in the anti-inflammation activity by network pharmacology and molecular docking. The active components and targets of RA were screened out by TCMSP. Thereafter, through the “anti-inflammation effect” and “inflammation” as the keywords, disease targets were obtained from the GeneCards database. The PPI network was constructed with Cytoscape 3.8.0 software to screen core targets. The GO function and KEGG analysis were enriched and analyzed through the Metascape platform, obtaining the 3-dimensional view of the core targets from the PDB database, and then, performing molecular docking in AutoDock Vina, a heatmap was constructed using the binding free energies in GraphPad Prism 8. The Discovery Studio software was used for docking analysis, and eventually, the docking results were visualized. We also explored the targets and signaling pathways of Astragaloside IV acting on anti-inflammatory effects via constructing compound-disease-target-pathway network. 18 active components and 45 targets of RA were screened out. The main anti-inflammatory active components of RA were quercetin, Astragaloside IV, kaempferol, 7-O-methylisomucronulatol, and formononetin, and the strongly interacting core proteins were TNF, IL6, IL1B, TLR4, CXCL8, CCL2, IL10, VEGFA, and MMP9. The signal pathways mainly involved include Lipid and atherosclerosis, IL-17 signaling pathway, Chagas disease, leishmaniasis, and TNF signaling pathway. Moreover, molecular docking showed that the 2 most active compounds, Astragaloside IV and kaempferol, could efficiently bind with the targets TNF, TLR4, and IL10. Astragaloside IV may play a part in anti-inflammatory effects through pathways such as HIF-1 signaling pathway, Inflammatory bowel disease and Hepatitis B ect. RA exhibits the characteristic of multicomponent and multitarget synergistic effects in exerting anti-inflammatory effects and the effective component of RA is Astragaloside IV, targeting TNF, TLR4, and IL10. |
format | Online Article Text |
id | pubmed-10476849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-104768492023-09-05 Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking Ren, Jianwei Ding, Yuetian Li, Shangze Lei, Ming Medicine (Baltimore) 3800 According to current research, the primary active ingredients of Radix Astragali (RA), such as saponins, flavonoids, and polysaccharides, play an important role in anti-inflammatory effects. However, the exact molecular mechanism underlying the action was not elucidated to date. Our research attempted to determine the active components in RA and to investigate the interaction between the active components and targets involved in the anti-inflammation activity by network pharmacology and molecular docking. The active components and targets of RA were screened out by TCMSP. Thereafter, through the “anti-inflammation effect” and “inflammation” as the keywords, disease targets were obtained from the GeneCards database. The PPI network was constructed with Cytoscape 3.8.0 software to screen core targets. The GO function and KEGG analysis were enriched and analyzed through the Metascape platform, obtaining the 3-dimensional view of the core targets from the PDB database, and then, performing molecular docking in AutoDock Vina, a heatmap was constructed using the binding free energies in GraphPad Prism 8. The Discovery Studio software was used for docking analysis, and eventually, the docking results were visualized. We also explored the targets and signaling pathways of Astragaloside IV acting on anti-inflammatory effects via constructing compound-disease-target-pathway network. 18 active components and 45 targets of RA were screened out. The main anti-inflammatory active components of RA were quercetin, Astragaloside IV, kaempferol, 7-O-methylisomucronulatol, and formononetin, and the strongly interacting core proteins were TNF, IL6, IL1B, TLR4, CXCL8, CCL2, IL10, VEGFA, and MMP9. The signal pathways mainly involved include Lipid and atherosclerosis, IL-17 signaling pathway, Chagas disease, leishmaniasis, and TNF signaling pathway. Moreover, molecular docking showed that the 2 most active compounds, Astragaloside IV and kaempferol, could efficiently bind with the targets TNF, TLR4, and IL10. Astragaloside IV may play a part in anti-inflammatory effects through pathways such as HIF-1 signaling pathway, Inflammatory bowel disease and Hepatitis B ect. RA exhibits the characteristic of multicomponent and multitarget synergistic effects in exerting anti-inflammatory effects and the effective component of RA is Astragaloside IV, targeting TNF, TLR4, and IL10. Lippincott Williams & Wilkins 2023-09-01 /pmc/articles/PMC10476849/ /pubmed/37657026 http://dx.doi.org/10.1097/MD.0000000000034945 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. |
spellingShingle | 3800 Ren, Jianwei Ding, Yuetian Li, Shangze Lei, Ming Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking |
title | Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking |
title_full | Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking |
title_fullStr | Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking |
title_full_unstemmed | Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking |
title_short | Predicting the anti-inflammatory mechanism of Radix Astragali using network pharmacology and molecular docking |
title_sort | predicting the anti-inflammatory mechanism of radix astragali using network pharmacology and molecular docking |
topic | 3800 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476849/ https://www.ncbi.nlm.nih.gov/pubmed/37657026 http://dx.doi.org/10.1097/MD.0000000000034945 |
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