Discovery of quality markers in the rhizome of Atractylodes chinensis using GC–MS fingerprint and network pharmacology

Wang, Wei; Jiang, Yuanyuan; Song, Baohong; Tang, Xuemei; Wu, Hongfei; Jin, Zhao; Chen, Lu

doi:10.1016/j.arabjc.2023.105114

Cited by 6 publications

(5 citation statements)

References 40 publications

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“…Zhang et al [44] identified atramacronoids A-C (18)(19)(20) from the rhizomes of A. macrocephala using spectroscopic data analysis, chemical calculations, and X-ray diffraction, which were found to contain an unusual 6/6/5/5/6 skeleton furnished by an unexpected C-8-C-16 linkage. Subsequently, twenty undescribed eudesmane-type sesquiterpenes named atramacronoids D-W (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40) were identified in the rhizomes of A. macrocephala using extensive spectroscopic data analysis, Snatzke's rule, ECD calculations, and X-ray crystallographic analysis [45,46]. A chemical investigation of the ethanol extract of A. lancea resulted in the isolation of nine eudesmanetype sesquiterpenoids (41)(42)(43)(44)(45)(46)(47)(48)(49), and their structures were elucidated using spectroscopic techniques and HRESIMS [47].…”

Section: Eudesmane-type Sesquiterpenesmentioning

confidence: 99%

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Phytochemistry and Pharmacology of Sesquiterpenoids from Atractylodes DC. Genus Rhizomes

Qu,

Liu,

Zhang

et al. 2024

Molecules

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The rhizomes of the genus Atractylodes DC. consist of various bioactive components, including sesquiterpenes, which have attracted a great deal of research interest in recent years. In the present study, we reviewed the previously published literatures prior to November 2023 on the chemical structures, biosynthetic pathways, and pharmacological activities of the sesquiterpenoids from this genus via online databases such as Web of Science, Google Scholar, and ScienceDirect. Phytochemical studies have led to the identification of more than 160 sesquiterpenes, notably eudesmane-type sesquiterpenes. Many pharmacological activities have been demonstrated, particularly anticancer, anti-inflammatory, and antibacterial and antiviral activities. This review presents updated, comprehensive and categorized information on the phytochemistry and pharmacology of sesquiterpenes in Atractylodes DC., with the aim of offering guidance for the future exploitation and utilization of active ingredients in this genus.

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Section: Eudesmane-type Sesquiterpenesmentioning

confidence: 99%

“…β -eudesmol, atractylon, and hinesol are usually used as chemical markers for evaluating the quality of Atractylodes DC. in different regions [ 22 , 23 , 24 , 25 ]. Many studies have been conducted on Atractylodes DC.…”

Section: Introductionmentioning

confidence: 99%

Phytochemistry and Pharmacology of Sesquiterpenoids from Atractylodes DC. Genus Rhizomes

Qu,

Liu,

Zhang

et al. 2024

Molecules

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“…They identified 78 components from Atractylodis rhizoma. Wang et al 10 developed a qualitative method to discover the quality markers in Atractylodis rhizoma using GC-MS fingerprint and network pharmacology. Finally, hinesol, atractylon, and β-eudesmol were identified as potential Q-markers for Atractylodis rhizoma.…”

Section: Introductionmentioning

confidence: 99%

Fast Discrimination and Quantification Analysis of Atractylodis rhizoma Using NIR Spectroscopy Coupled with Chemometrics Tools

Peng,

He,

Wang

et al. 2024

J. Agric. Food Chem.

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In this study, near-infrared (NIR) spectroscopy and high-performance liquid chromatography (HPLC) combined with chemometrics tools were applied for quick discrimination and quantitative analysis of different varieties and origins of Atractylodis rhizoma samples. Based on NIR data, orthogonal partial least squares discriminant analysis (OPLS-DA) and K-nearest neighbor (KNN) models achieved greater than 90% discriminant accuracy of the three species and two origins of Atractylodis rhizoma. Moreover, the contents of three active ingredients (atractyloxin, atractylone, and β-eudesmol) in Atractylodis rhizoma were simultaneously determined by HPLC. There are significant differences in the content of the three components in the samples of Atractylodis rhizoma from different varieties and origins. Then, partial least squares regression (PLSR) models for the prediction of atractyloxin, atractylone, and β-eudesmol content were successfully established. The complete Atractylodis rhizoma spectra gave rise to good predictions of atractyloxin, atractylone, and β-eudesmol content with R 2 values of 0.9642, 0.9588, and 0.9812, respectively. Based on the results of this present research, it can be concluded that NIR is a great nondestructive alternative to be applied as a rapid classification system by the drug industry.

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“…Emerged as the most promising medicinal option. Wang et al (2023) utilized a combination of “GC-MS fingerprinting - network pharmacology - chemometric pattern recognition” to demonstrate that Atractylodes lancea (Thunb.) DC.…”

Section: Introductionmentioning

confidence: 99%

Utilizing metabolomics and network analysis to explore the effects of artificial production methods on the chemical composition and activity of agarwood

Hou,

Feng,

Sun

et al. 2024

Front. Pharmacol.

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Introduction: Agarwood is a traditional aromatic southern medicine. It has a long history of being used in traditional Chinese aromatherapy to treat insomnia, anxiety and depression. Due to the scarcity of wild resources, people have planted trees successfully and begun to explore various agarwood-inducing techniques. This study comparative analysis of volatile metabolites in agarwood produced by various inducing techniques and its potential sleep-promoting, anti-anxiety and anti-depressant network pharmacological activities. Methods: A total of 23 batches of two types of agarwood were collected, one of which was produced by artificial techniques, including 6 batches of TongTi (TT) agarwood produced by “Agar-Wit” and 6 batches of HuoLao (HL) agarwood produced by “burning, chisel and drilling”, while the other was collected from the wild, including 6 batches of BanTou (BT) agarwood with trunks broken due to natural or man-made factors and 5 batches of ChongLou (CL) agarwood with trunks damaged by moth worms. The study employed metabolomics combined with network analysis to compare the differences in volatile metabolites of agarwood produced by four commonly used inducing techniques, and explored their potential roles and possible action targets in promoting sleep, reducing anxiety, and alleviating depression. Results: A total of 147 volatile metabolites were detected in agarwood samples, mainly including small aromatic hydrocarbons, sesquiterpenes and 2-(2-phenylethyl) chromone and their pyrolysis products. The results showed composition of metabolites was minimally influenced by the agarwood induction method. However, their concentrations exhibited significant variations, with 17 metabolites showing major differences. The two most distinct metabolites were 6-methoxy-2-(2-phenylethyl) chromone and 6,7-dimethoxy-2-(2-phenylethyl) chromone. Among the volatile metabolites, 142 showed promising potential in treating insomnia, anxiety, and depression, implicating various biological and signaling pathways, predominantly ALB and TNF targets. The top three active metabolites identified were 2-(2-phenylethyl) chromone, 1,5-diphenylpent-1-en-3-one, and 6-methoxy-2-[2-(4'-methoxyphenyl) ethyl] chromone, with their relative content in the four types of agarwood being TT>HL>CL>BT. Conclusion: The differences in the content of 2-(2-phenylethyl) chromones suggest that they may be responsible for the varying therapeutic activities observed in different types of agarwood aromatherapy. This study offers theoretical support for the selection of agarwood in aromatherapy practices.

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Discovery of quality markers in the rhizome of Atractylodes chinensis using GC–MS fingerprint and network pharmacology

Cited by 6 publications

References 40 publications

Phytochemistry and Pharmacology of Sesquiterpenoids from Atractylodes DC. Genus Rhizomes

Phytochemistry and Pharmacology of Sesquiterpenoids from Atractylodes DC. Genus Rhizomes

Fast Discrimination and Quantification Analysis of Atractylodis rhizoma Using NIR Spectroscopy Coupled with Chemometrics Tools

Utilizing metabolomics and network analysis to explore the effects of artificial production methods on the chemical composition and activity of agarwood

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