Abstract

Alismatis Rhizoma decoction (ARD), comprised of Alisma plantago-aquatica subsp. orientale (Sam.) Sam and Atractylodes macrocephala Koidz. at a ratio of 5 : 2, is a classic traditional Chinese medicine (TCM) formula with successful clinical hypolipidemic effect. This paper aimed to explore the major bioactive compounds and potential mechanism of ARD in the treatment of hyperlipidemia on the basis of spectrum-effect analysis and molecular docking. Nine ARD samples with varying ratios of the constituent herbs were prepared and analyzed by UPLC-Q-TOF/MS to obtain the chemical spectra. Then, the lipid-lowering ability of the nine samples was tested in an oleic acid-induced lipid accumulation model in human hepatoma cells (HepG2). Grey relational analysis and partial least squares regression analysis were then performed to determine the correlation between the chemical spectrums and lipid-lowering efficacies of ARD. The potential mechanisms of the effective compounds were investigated by docking with the farnesoid X receptor (FXR) protein. The results indicated that alisol B 23-acetate, alisol C 23-acetate, and alisol B appeared to be the core effective components on hyperlipidemia in ARD. Molecular docking further demonstrated that all three compounds could bind to FXR and were potential FXR agonists for the treatment of hyperlipidemia. This study elucidated the effective components and potential molecular mechanism of action of ARD for treating hyperlipidemia from a perspective of different compatibility, providing a new and feasible reference for the research of TCM formulas such as ARD.

Highlights

  • Alismatis Rhizoma decoction (ARD), comprised of the rhizomes of Alisma orientale (Sam.) Juzep. (AR) and the rhizomes of Atractylodes macrocephala Koidz. (AMR) at a ratio of 5 : 2, was first described by Zhongjing Zhang in “Jingui Yaolue” [1]

  • Under the abovementioned UPLC-MS conditions, the bask peak ion (BPI) chromatograms of the nine ARD samples were obtained as the chemical spectrum in the spectrum-effect study. en, nine chemical chromatograms were automatically matched by the professional software named Similarity Evaluation System for Chromatographic Spectrum of Traditional Chinese Medicine (2004A version, Committee of Chinese Pharmacopeia) to generate the common peaks of the different ARD samples [20]

  • Qualitative Analysis of ARD. e UPLC-MS-based qualitative analysis of ARD was performed in our previous study. e chromatographic and mass spectrometric conditions were the same as the conditions above. e results could be confirmed in the published paper in detail [21]

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Summary

Introduction

Alismatis Rhizoma decoction (ARD), comprised of the rhizomes of Alisma orientale (Sam.) Juzep. (AR) and the rhizomes of Atractylodes macrocephala Koidz. (AMR) at a ratio of 5 : 2, was first described by Zhongjing Zhang in “Jingui Yaolue” [1]. The spectrum-effect study is increasingly being used to discern the specific biological active compounds in TCM by analyzing the correlation between the spectral profiles and biological effects [8]. Reasonable chemometric methods, such as canonical correlation analysis, grey relational analysis, and partial least squares regression analysis, are frequently utilized for the spectrum-effect research [9]. E chemical spectra and lipid-lowering efficacies of ARD extracts in HepG2 cells with different compatibilities were correlated to reveal the core lipid-lowering compounds, and their potential interactions with FXR were determined by molecular docking in order to verify the accuracy of spectrum-effect analysis and probe the mechanism of action of ARD on hyperlipidemia. To prepare working solutions for chromatography, 50 mg of each ARD crude extract was diluted in 10 mL 80% methanol to yield a solution of concentration 5 mg/mL. e standard solution was prepared by dissolving accurately weighted portions of the five reference compounds in MeOH

UPLC-MS Analysis
Materials and Methods
Lipid-Lowering Effect Investigations
Spectrum-Effect Analysis
Establishment of the UPLC-MS Spectrum
Combination of Suitable Mathematical Approaches for Relevance Analysis
Findings
Discussion
Conclusion
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