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Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking
Background: This study aimed to investigate the molecular mechanism of Radix Paeoniae Alba (white peony, WP) in treating immune inflammatory diseases of rheumatoid arthritis (RA) and tumor necrosis factor-alpha (TNF-α) inhibitors (TNFis) by using network pharmacology and molecular docking. Methods:...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175775/ https://www.ncbi.nlm.nih.gov/pubmed/34093213 http://dx.doi.org/10.3389/fphar.2021.690118 |
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author | Bai, Liang Liang Chen, Hao Zhou, Peng Yu, Jun |
author_facet | Bai, Liang Liang Chen, Hao Zhou, Peng Yu, Jun |
author_sort | Bai, Liang Liang |
collection | PubMed |
description | Background: This study aimed to investigate the molecular mechanism of Radix Paeoniae Alba (white peony, WP) in treating immune inflammatory diseases of rheumatoid arthritis (RA) and tumor necrosis factor-alpha (TNF-α) inhibitors (TNFis) by using network pharmacology and molecular docking. Methods: In this study, the ingredient of WP and the potential inflammatory targets of RA were obtained from the Traditional Chinese Medicine Systematic Pharmacology Database, GeneCard, and OMIM databases, respectively. The establishment of the RA–WP-potential inflammatory target gene interaction network was accomplished using the STRING database. Network maps of the WP–RA-potential inflammatory target gene network were constructed using Cytoscape software. Gene ontology (GO) and the biological pathway (KEGG) enrichment analyses were used to further explore the RA mechanism and therapeutic effects of WP. Molecular docking technology was used to analyze the optimal effective components from WP for docking with TNF-α. Results: Thirteen active ingredients and 71 target genes were screened from WP, and 49 of the target genes intersected with RA target inflammatory genes and were considered potential therapeutic targets. Network pharmacological analysis showed that the WP active ingredients such as mairin, DPHCD, (+)-catechin, beta-sitosterol, paeoniflorin, sitosterol, and kaempferol showed better correlation with RA inflammatory target genes such as PGR, PTGS1, PTGS2, NR3C2, TNFSF15, and CHRM2, respectively. The immune-inflammatory signaling pathways of the active ingredients for the treatment of RA are the TNF-α signaling pathway, Toll-like receptor signaling pathway, cell apoptosis, interleukin-17 signaling pathway, C-type lectin receptor signaling pathway, mitogen-associated protein kinase, etc. Molecular docking results suggested that mairin was the most appropriate natural TNFis. Conclusion: Our findings provide an essential role and basis for further immune-inflammatory studies into the molecular mechanisms of WP and TNFis development in RA. |
format | Online Article Text |
id | pubmed-8175775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81757752021-06-05 Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking Bai, Liang Liang Chen, Hao Zhou, Peng Yu, Jun Front Pharmacol Pharmacology Background: This study aimed to investigate the molecular mechanism of Radix Paeoniae Alba (white peony, WP) in treating immune inflammatory diseases of rheumatoid arthritis (RA) and tumor necrosis factor-alpha (TNF-α) inhibitors (TNFis) by using network pharmacology and molecular docking. Methods: In this study, the ingredient of WP and the potential inflammatory targets of RA were obtained from the Traditional Chinese Medicine Systematic Pharmacology Database, GeneCard, and OMIM databases, respectively. The establishment of the RA–WP-potential inflammatory target gene interaction network was accomplished using the STRING database. Network maps of the WP–RA-potential inflammatory target gene network were constructed using Cytoscape software. Gene ontology (GO) and the biological pathway (KEGG) enrichment analyses were used to further explore the RA mechanism and therapeutic effects of WP. Molecular docking technology was used to analyze the optimal effective components from WP for docking with TNF-α. Results: Thirteen active ingredients and 71 target genes were screened from WP, and 49 of the target genes intersected with RA target inflammatory genes and were considered potential therapeutic targets. Network pharmacological analysis showed that the WP active ingredients such as mairin, DPHCD, (+)-catechin, beta-sitosterol, paeoniflorin, sitosterol, and kaempferol showed better correlation with RA inflammatory target genes such as PGR, PTGS1, PTGS2, NR3C2, TNFSF15, and CHRM2, respectively. The immune-inflammatory signaling pathways of the active ingredients for the treatment of RA are the TNF-α signaling pathway, Toll-like receptor signaling pathway, cell apoptosis, interleukin-17 signaling pathway, C-type lectin receptor signaling pathway, mitogen-associated protein kinase, etc. Molecular docking results suggested that mairin was the most appropriate natural TNFis. Conclusion: Our findings provide an essential role and basis for further immune-inflammatory studies into the molecular mechanisms of WP and TNFis development in RA. Frontiers Media S.A. 2021-05-21 /pmc/articles/PMC8175775/ /pubmed/34093213 http://dx.doi.org/10.3389/fphar.2021.690118 Text en Copyright © 2021 Bai, Chen, Zhou and Yu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Bai, Liang Liang Chen, Hao Zhou, Peng Yu, Jun Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking |
title | Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking |
title_full | Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking |
title_fullStr | Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking |
title_full_unstemmed | Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking |
title_short | Identification of Tumor Necrosis Factor-Alpha (TNF-α) Inhibitor in Rheumatoid Arthritis Using Network Pharmacology and Molecular Docking |
title_sort | identification of tumor necrosis factor-alpha (tnf-α) inhibitor in rheumatoid arthritis using network pharmacology and molecular docking |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175775/ https://www.ncbi.nlm.nih.gov/pubmed/34093213 http://dx.doi.org/10.3389/fphar.2021.690118 |
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