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Issue 87, 2017, Issue in Progress
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Metabolomic investigation into molecular mechanisms of a clinical herb prescription against metabolic syndrome by a systematic approach

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Abstract

Wendan decoction (WDD), a classic herb prescription in China, has been extensively proved to improve metabolic syndrome (Mets) in clinics. However, till now, its pharmacological mechanisms remained vague. In this study, a systematic approach that integrated GC-TOF/MS based metabolomics, multivariate statistical techniques (PCA and PLS-DA), KEGG pathway analysis and molecular docking simulation was established to explore the pathophysiological mechanisms of Mets and elucidate the molecular mechanisms of WDD against Mets rats. Compared to the control rat group, five significantly altered and impacted pathways (P < 0.05 and IV > 1) associated with thirty-nine significantly altered metabolites related to glycolysis, the TCA cycle, the urea cycle, amino acid and lipid metabolisms, gluconeogenesis and ketogenesis were identified as biomarkers of Mets. After two weeks of treatment, seventeen and fourteen significantly altered metabolites in the Mets model group tended to be restored to normal levels by WDD and metformin, respectively. Additionally, six significantly altered pathways were involved in treatment of Mets by WDD, while no significant pathway was found for metformin (P < 0.05). Finally, the molecular docking simulation revealed that seventy compounds in WDD competed with substrates to bind with four enzymes, which led to a reduction in the serum levels of significantly altered metabolites.

Graphical abstract: Metabolomic investigation into molecular mechanisms of a clinical herb prescription against metabolic syndrome by a systematic approach

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Supplementary files

Article information


Submitted
02 Sep 2017
Accepted
22 Nov 2017
First published
06 Dec 2017

This article is Open Access

RSC Adv., 2017,7, 55389-55399
Article type
Paper

Metabolomic investigation into molecular mechanisms of a clinical herb prescription against metabolic syndrome by a systematic approach

M. Chen, F. Yang, J. Kang, H. Gan, X. Lai and Y. Gao, RSC Adv., 2017, 7, 55389
DOI: 10.1039/C7RA09779D

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