Zhao Y, Chang X, Gu X, Li Y, Zheng Y, Fang H. Predictive Analysis of Quality Markers of Atractylodis Rhizoma Based on Fingerprint and Network Pharmacology.
J AOAC Int 2023;
106:1402-1413. [PMID:
37208180 DOI:
10.1093/jaoacint/qsad059]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 05/03/2023] [Accepted: 05/09/2023] [Indexed: 05/21/2023]
Abstract
BACKGROUND
Atractylodes chinensis (DC.) Koidz. (A. chinensis) is a perennial herbaceous plant that is widely used as a Chinese medicine herb for gastric diseases. However, the bioactive compounds of this herbal medicine have not been defined, and quality control is imperfect.
OBJECTIVE
Although the method of quality evaluation method for A. chinensis by high-performance liquid chromatography (HPLC) fingerprinting has been reported in related papers, it remains unknown whether the chemical markers selected are representative of their clinical efficacy. To develop methods for qualitative analysis and improved quality evaluation of A. chinensis.
METHOD
In this study, HPLC was used to establish fingerprints and conduct similarity evaluation. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to reveal the differences of these fingerprints. Network pharmacology was used to analyze the corresponding targets of the active ingredients. Meantime, an active ingredient-target-pathway network was constructed to investigate the characteristics of the medical efficacy of A. chinensis and to predict potential Q-markers.
RESULTS
Combining network pharmacological effectiveness and composition specificity with the Q-marker concept, atractylodin (ATD), β-eudesmol, atractylenolide Ι (AT-I) and atractylenolide III (AT-III) were predicted to be potential Q-markers of A. chinensis that showed anti-inflammatory, antidepressant, anti-gastric, and antiviral effects by acting on 10 core targets and 20 key pathways.
CONCLUSIONS
The HPLC fingerprinting method established in this study is straightforward, and the identified four active constituents can be used as Q-markers of A. chinensis. These findings facilitate effective quality evaluation of A. chinensis and suggest this approach could be applied to evaluate the quality of other herbal medicines.
HIGHLIGHTS
The fingerprints of Atractylodis rhizoma were organically combined with network pharmacology to further clarify its criteria for quality control.
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