Exploring therapeutic mechanisms of San-Huang-Tang in nonalcoholic fatty liver disease through network pharmacology and experimental validation.


Journal

Journal of ethnopharmacology
ISSN: 1872-7573
Titre abrégé: J Ethnopharmacol
Pays: Ireland
ID NLM: 7903310

Informations de publication

Date de publication:
05 Oct 2022
Historique:
received: 29 10 2021
revised: 10 04 2022
accepted: 14 06 2022
pubmed: 29 6 2022
medline: 20 7 2022
entrez: 28 6 2022
Statut: ppublish

Résumé

San-Huang-Tang (SHT), a traditional Chinese medicine (TCM) formula, has been clinically used to treat obesity and type 2 diabetes mellitus. Recently it has proved that SHT have a good effect on non-alcoholic fatty liver disease (NAFLD). Our study was designed to investigate the therapeutic mechanisms of the SHT against NAFLD. The data of SHT were obtained through network pharmacology platform and validated experimentally in vivo and in vitro. The candidate targets of SHT were predicted by network pharmacological analysis and crucial targets were chosen by the protein-protein interaction (PPI) network. Furthermore, Gene Ontology (GO) and Kyoto encyclopedia of genes and Genomes (KEGG) were applied to analyze the NAFLD-related signaling pathways affected by SHT, and then the analysis results were verified with molecular biological experiments in vivo and in vitro. Molecules were screened with network pharmacological analysis, and then the improvement of insulin resistance of NAFLD mice was measured by IPITTs and IPGTTs. Through series of molecular experiments, it is revealed that SHT could increase the transcription of insulin receptor (INSR) and insulin receptor substrate (IRS1), and enhance the phosphorylation of both threonine protein kinase (AKT) and forkhead box O1 (FoxO1). Screened by bioinformatics and verified by experiments in vivo and in vitro, SHT could contribute to NAFLD by affecting insulin resistance via activating INSR/IRS1/AKT/FoxO1 pathway. Our research findings provide not only an experimental basis for the therapeutic effect of SHT but also a new target against NAFLD.

Identifiants

pubmed: 35764198
pii: S0378-8741(22)00516-5
doi: 10.1016/j.jep.2022.115477
pii:
doi:

Substances chimiques

Drugs, Chinese Herbal 0
San-Huang 0
Receptor, Insulin EC 2.7.10.1
Proto-Oncogene Proteins c-akt EC 2.7.11.1

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115477

Informations de copyright

Copyright © 2022. Published by Elsevier B.V.

Auteurs

Huilian Shi (H)

Department of Infectious Diseases, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, PR China.

Fei Qiao (F)

Department of Infectious Diseases, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, PR China.

Kaiyue Huang (K)

Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, PR China.

Weiting Lu (W)

Department of Infectious Diseases, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, PR China.

Xinzhuang Zhang (X)

State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Jiangsu Kanion Pharmaceutical Co.,Ltd, Lianyungang, Jiangsu, PR China.

Zhipeng Ke (Z)

State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Jiangsu Kanion Pharmaceutical Co.,Ltd, Lianyungang, Jiangsu, PR China.

Yanchi Wu (Y)

Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, PR China.

Liang Cao (L)

State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Jiangsu Kanion Pharmaceutical Co.,Ltd, Lianyungang, Jiangsu, PR China; Department of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, PR China. Electronic address: leancao@163.com.

Yuanyuan Chen (Y)

Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, PR China. Electronic address: yuanyuanch@njmu.edu.cn.

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Classifications MeSH