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

Abstract

BackgroundThe rhizome of Atractylodes chinensis (RAC), also known as “Cangzhu”, is a well-known Chinese herbal medicine (CHMs). Due to the scarcity of wild resources, cultivated RAC and counterfeit products derived from the rhizome of Atractylodes japonica (RAJ) are also prevalent on the market. Diverse origins lead to varying quality. At present, the Chinese Pharmacopoeia (2020 edition) uses atractylodin as the only quantitative index component for RAC, and there is a lack of research on quality markers (Q-markers) that are closely related to efficacy. PurposeThis work aims to discover the Q-markers of RAC based on chemical and pharmacological strategies. MethodsThe chemical composition of RAC was analyzed and identified through gas chromatography-mass spectrometry (GC–MS). The ″Chromatographic Fingerprint Similarity Evaluation System for Traditional Chinese Medicine″ was utilized to assess the similarity of the samples and identify the characteristic peaks. Network pharmacology was employed to screen targets and pathways for characteristic components of the RAC, construct “active ingredients–targets–pathways” network diagrams, and predict the Q-markers. The Q-markers for RAC were identified through an integrated analysis of the chemical components, network pharmacology, pharmacological activities and clinical applications. In addition, a preliminary evaluation of 28 batches of “Cangzhu” from different origins were conducted by GC–MS and chemical pattern recognition. ResultsA total of 16 specific components of RAC were identified by GC–MS fingerprint. The network pharmacology study found that these 16 components primarily function through 29 core targets and 23 pathways. Three compounds, hinesol, atractylon, and β-eudesmol were identified as the potential Q-markers for RAC. The evaluation of 28 batches of “Cangzhu” showed that these three Q-markers could effectively distinguish RAC from RAJ, and RAJ could not be used as a substitute for RAC. There was no significant difference between cultivated RAC and wild RAC, and the quality of cultivated RAC was more uniform than wild RAC. ConclusionThis study identified and verified three potential Q-markers for RAC by using a comprehensive strategy combing of “GC–MS fingerprinting – network pharmacology – chemical pattern recognition”. It provides a basis for the establishment of a more reasonable RAC quality evaluation system. Furthermore, it provides a reference for the discovery of Q-markers in other CHMs.