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Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology

BACKGROUND: This study sought to examine the mechanism of the Jian Pi Tiao Gan Yin in the treatment of obesity by network pharmacology. METHODS: The active components and corresponding targets of the Jian Pi Tiao Gan Yin were identified using the traditional Chinese medicine systems pharmacology dat...

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Autores principales: Tian, Minghui, Gao, Hua, Jiao, Hongfei, Tian, Hongbin, Han, Lulu, Lin, Xiaowan, Cheng, Gong, Sun, Fenglei, Feng, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9011268/
https://www.ncbi.nlm.nih.gov/pubmed/35433974
http://dx.doi.org/10.21037/atm-22-553
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author Tian, Minghui
Gao, Hua
Jiao, Hongfei
Tian, Hongbin
Han, Lulu
Lin, Xiaowan
Cheng, Gong
Sun, Fenglei
Feng, Bo
author_facet Tian, Minghui
Gao, Hua
Jiao, Hongfei
Tian, Hongbin
Han, Lulu
Lin, Xiaowan
Cheng, Gong
Sun, Fenglei
Feng, Bo
author_sort Tian, Minghui
collection PubMed
description BACKGROUND: This study sought to examine the mechanism of the Jian Pi Tiao Gan Yin in the treatment of obesity by network pharmacology. METHODS: The active components and corresponding targets of the Jian Pi Tiao Gan Yin were identified using the traditional Chinese medicine systems pharmacology database and analysis platform, and the obesity-related targets were acquired from the Online Mendelian Inheritance in Man database. The drug and disease targets were also identified. Cytoscape software was used to construct the “active component target” network diagram. The protein-protein interaction network was drawn using the Search Tool for the Retrieval of Interacting Genes/Proteins platform, and the Cytoscape MCODE plugin was used to find clusters for the protein cluster analysis. The gene annotation and analysis were performed with the Metascape database via functional databases, such as the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and Autodock and PyMOL were used for the molecular docking. RESULTS: The GO analysis identified 244 target genes of the Jian Pi Tiao Gan Yin, 1,378 targets of obesity, and 123 targets of drug and disease. Additionally, 208 biological process items, 38 molecular function items, and 33 cell component items were also identified. The KEGG pathway analysis identified the hypoxia-inducible factor, forkhead box O, cyclic adenosine monophosphate, and vascular endothelial growth factor signaling pathways. The results of the molecular docking showed that the main active components of the Jian Pi Tiao Gan Yin in the treatment of obesity were quercetin, kaempferol, stigmasterol, luteolin, isorhamnetin, β-sitosterol, sapogenin, tanshinone, and formononetin, all of which have been proven to bind to core obesity-related proteins, such as AKT1, interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA), tumor necrosis factor (TNF), tumor protein 53 (TP53), prostaglandin-endoperoxide synthase 2 (PTGS2), caspase-3 (CASP3), mitogen-activated protein kinase 1 (MAPK1), JUN, and epidermal growth factor (EGF). Thus, our study revealed the potential mechanism of the Jian Pi Tiao Gan Yin as a multi-component, multi-target, and multi-channel treatment for obesity. These findings lay the foundation for further studies on the mechanism of the Jian Pi Tiao Gan Yin in obesity treatment. CONCLUSIONS: The Jian Pi Tiao Gan Yin can be used as a multi-component, multi-target, and multi-channel treatment for obesity.
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spelling pubmed-90112682022-04-16 Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology Tian, Minghui Gao, Hua Jiao, Hongfei Tian, Hongbin Han, Lulu Lin, Xiaowan Cheng, Gong Sun, Fenglei Feng, Bo Ann Transl Med Original Article BACKGROUND: This study sought to examine the mechanism of the Jian Pi Tiao Gan Yin in the treatment of obesity by network pharmacology. METHODS: The active components and corresponding targets of the Jian Pi Tiao Gan Yin were identified using the traditional Chinese medicine systems pharmacology database and analysis platform, and the obesity-related targets were acquired from the Online Mendelian Inheritance in Man database. The drug and disease targets were also identified. Cytoscape software was used to construct the “active component target” network diagram. The protein-protein interaction network was drawn using the Search Tool for the Retrieval of Interacting Genes/Proteins platform, and the Cytoscape MCODE plugin was used to find clusters for the protein cluster analysis. The gene annotation and analysis were performed with the Metascape database via functional databases, such as the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and Autodock and PyMOL were used for the molecular docking. RESULTS: The GO analysis identified 244 target genes of the Jian Pi Tiao Gan Yin, 1,378 targets of obesity, and 123 targets of drug and disease. Additionally, 208 biological process items, 38 molecular function items, and 33 cell component items were also identified. The KEGG pathway analysis identified the hypoxia-inducible factor, forkhead box O, cyclic adenosine monophosphate, and vascular endothelial growth factor signaling pathways. The results of the molecular docking showed that the main active components of the Jian Pi Tiao Gan Yin in the treatment of obesity were quercetin, kaempferol, stigmasterol, luteolin, isorhamnetin, β-sitosterol, sapogenin, tanshinone, and formononetin, all of which have been proven to bind to core obesity-related proteins, such as AKT1, interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA), tumor necrosis factor (TNF), tumor protein 53 (TP53), prostaglandin-endoperoxide synthase 2 (PTGS2), caspase-3 (CASP3), mitogen-activated protein kinase 1 (MAPK1), JUN, and epidermal growth factor (EGF). Thus, our study revealed the potential mechanism of the Jian Pi Tiao Gan Yin as a multi-component, multi-target, and multi-channel treatment for obesity. These findings lay the foundation for further studies on the mechanism of the Jian Pi Tiao Gan Yin in obesity treatment. CONCLUSIONS: The Jian Pi Tiao Gan Yin can be used as a multi-component, multi-target, and multi-channel treatment for obesity. AME Publishing Company 2022-03 /pmc/articles/PMC9011268/ /pubmed/35433974 http://dx.doi.org/10.21037/atm-22-553 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Tian, Minghui
Gao, Hua
Jiao, Hongfei
Tian, Hongbin
Han, Lulu
Lin, Xiaowan
Cheng, Gong
Sun, Fenglei
Feng, Bo
Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology
title Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology
title_full Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology
title_fullStr Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology
title_full_unstemmed Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology
title_short Mechanisms of the Jian Pi Tiao Gan Yin in the treatment of simple obesity revealed by network pharmacology
title_sort mechanisms of the jian pi tiao gan yin in the treatment of simple obesity revealed by network pharmacology
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9011268/
https://www.ncbi.nlm.nih.gov/pubmed/35433974
http://dx.doi.org/10.21037/atm-22-553
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