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Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model

Traditional Chinese medicine (TCM) with the characteristics of “multi-component-multi-target-multi-pathway” has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of “treating the same disease with different treatments”. However, there are still some pr...

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Autores principales: Wang, Ke-xin, Gao, Yao, Lu, Cheng, Li, Yao, Zhou, Bo-ya, Qin, Xue-mei, Du, Guan-hua, Gao, Li, Guan, Dao-gang, Lu, Ai-ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365894/
https://www.ncbi.nlm.nih.gov/pubmed/32754034
http://dx.doi.org/10.3389/fphar.2020.01035
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author Wang, Ke-xin
Gao, Yao
Lu, Cheng
Li, Yao
Zhou, Bo-ya
Qin, Xue-mei
Du, Guan-hua
Gao, Li
Guan, Dao-gang
Lu, Ai-ping
author_facet Wang, Ke-xin
Gao, Yao
Lu, Cheng
Li, Yao
Zhou, Bo-ya
Qin, Xue-mei
Du, Guan-hua
Gao, Li
Guan, Dao-gang
Lu, Ai-ping
author_sort Wang, Ke-xin
collection PubMed
description Traditional Chinese medicine (TCM) with the characteristics of “multi-component-multi-target-multi-pathway” has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of “treating the same disease with different treatments”. However, there are still some problems such as unclear substance basis and molecular mechanism of the effectiveness of formula. Network pharmacology is a new strategy based on system biology and poly-pharmacology, which could observe the intervention of drugs on disease networks at systematical and comprehensive level, and especially suitable for study of complex TCM systems. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, causing articular and extra articular dysfunctions among patients, it could lead to irreversible joint damage or disability if left untreated. TCM formulas, Danggui-Sini-decoction (DSD), Guizhi-Fuzi-decoction (GFD), and Huangqi-Guizhi-Wuwu-Decoction (HGWD), et al., have been found successful in controlling RA in clinical applications. Here, a network pharmacology-based approach was established. With this model, key gene network motif with significant (KNMS) of three formulas were predicted, and the molecular mechanism of different formula in the treatment of rheumatoid arthritis (RA) was inferred based on these KNMSs. The results show that the KNMSs predicted by the model kept a high consistency with the corresponding C-T network in coverage of RA pathogenic genes, coverage of functional pathways and cumulative contribution of key nodes, which confirmed the reliability and accuracy of our proposed KNMS prediction strategy. All validated KNMSs of each RA therapy-related formula were employed to decode the mechanisms of different formulas treat the same disease. Finally, the key components in KNMSs of each formula were evaluated by in vitro experiments. Our proposed KNMS prediction and validation strategy provides methodological reference for interpreting the optimization of core components group and inference of molecular mechanism of formula in the treatment of complex diseases in TCM.
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spelling pubmed-73658942020-08-03 Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model Wang, Ke-xin Gao, Yao Lu, Cheng Li, Yao Zhou, Bo-ya Qin, Xue-mei Du, Guan-hua Gao, Li Guan, Dao-gang Lu, Ai-ping Front Pharmacol Pharmacology Traditional Chinese medicine (TCM) with the characteristics of “multi-component-multi-target-multi-pathway” has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of “treating the same disease with different treatments”. However, there are still some problems such as unclear substance basis and molecular mechanism of the effectiveness of formula. Network pharmacology is a new strategy based on system biology and poly-pharmacology, which could observe the intervention of drugs on disease networks at systematical and comprehensive level, and especially suitable for study of complex TCM systems. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, causing articular and extra articular dysfunctions among patients, it could lead to irreversible joint damage or disability if left untreated. TCM formulas, Danggui-Sini-decoction (DSD), Guizhi-Fuzi-decoction (GFD), and Huangqi-Guizhi-Wuwu-Decoction (HGWD), et al., have been found successful in controlling RA in clinical applications. Here, a network pharmacology-based approach was established. With this model, key gene network motif with significant (KNMS) of three formulas were predicted, and the molecular mechanism of different formula in the treatment of rheumatoid arthritis (RA) was inferred based on these KNMSs. The results show that the KNMSs predicted by the model kept a high consistency with the corresponding C-T network in coverage of RA pathogenic genes, coverage of functional pathways and cumulative contribution of key nodes, which confirmed the reliability and accuracy of our proposed KNMS prediction strategy. All validated KNMSs of each RA therapy-related formula were employed to decode the mechanisms of different formulas treat the same disease. Finally, the key components in KNMSs of each formula were evaluated by in vitro experiments. Our proposed KNMS prediction and validation strategy provides methodological reference for interpreting the optimization of core components group and inference of molecular mechanism of formula in the treatment of complex diseases in TCM. Frontiers Media S.A. 2020-07-10 /pmc/articles/PMC7365894/ /pubmed/32754034 http://dx.doi.org/10.3389/fphar.2020.01035 Text en Copyright © 2020 Wang, Gao, Lu, Li, Zhou, Qin, Du, Gao, Guan and Lu http://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
Wang, Ke-xin
Gao, Yao
Lu, Cheng
Li, Yao
Zhou, Bo-ya
Qin, Xue-mei
Du, Guan-hua
Gao, Li
Guan, Dao-gang
Lu, Ai-ping
Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model
title Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model
title_full Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model
title_fullStr Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model
title_full_unstemmed Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model
title_short Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model
title_sort uncovering the complexity mechanism of different formulas treatment for rheumatoid arthritis based on a novel network pharmacology model
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365894/
https://www.ncbi.nlm.nih.gov/pubmed/32754034
http://dx.doi.org/10.3389/fphar.2020.01035
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