National Pharmaceutical Engineering Center for Solid Preparation in Chinese Herbal Medicine, Jiangxi University of Chinese Medicine, No. 1688 Meiling Road, Nanchang 330002, PR China; Jiangxi Institute for Drug Control, No.1566 Beijing East Road, Nanchang 330029, PR China; NMPA Key Laboratory of Quality Evaluation of Traditional Chinese Patent Medicine, No.1566 Beijing East Road, Nanchang 330029, PR China.
National Pharmaceutical Engineering Center for Solid Preparation in Chinese Herbal Medicine, Jiangxi University of Chinese Medicine, No. 1688 Meiling Road, Nanchang 330002, PR China.
J Chromatogr A. 2024 Aug 16;1730:465094. doi: 10.1016/j.chroma.2024.465094. Epub 2024 Jun 16.
In this study, the collision induced dissociation tandem mass spectrometry (CID-MS/MS) fragmentation pathway of chemical components in rhubarb was wholly explored using 34 standards by UHPLC-QTOF-MS/MS in negative ion mode. In consequently, the diagnostic product ions for speedy screening and categorization of chemical components in rhubarb were ascertained based on their MS/MS splitting decomposition patterns and intensity analysis. According to these findings, a fresh two-step data mining strategy had set up. The initial key step involves the use of characteristic product ions and neutral loss to screen for different types of substituents and basic skeletons of compounds. The subsequent key step is to screen and classify different types of compounds based on their characteristic product ions. This method can be utilized for rapid research, classification, and identification of compounds in rhubarb. A total of 356 compounds were rapidly identified or tentatively characterized in three rhubarb species extracts, including 150 acylglucoside, 125 anthraquinone, 65 flavanols and 15 other compounds. This study manifests that the analytical strategy is feasible for the analysis of complex natural products in rhubarb.
本研究采用 UHPLC-QTOF-MS/MS 在负离子模式下,利用 34 个标准品,全面探究了大黄中化学成分的碰撞诱导解离串联质谱(CID-MS/MS)碎裂途径。由此,基于其 MS/MS 裂解分解模式和强度分析,确定了用于大黄中化学成分快速筛选和分类的诊断产物离子。根据这些发现,建立了一种新的两步数据挖掘策略。初始关键步骤涉及使用特征产物离子和中性丢失来筛选不同类型的取代基和化合物的基本骨架。后续的关键步骤是根据特征产物离子筛选和分类不同类型的化合物。该方法可用于大黄中化合物的快速研究、分类和鉴定。在三种大黄属植物提取物中,快速鉴定或暂定鉴定了 356 种化合物,包括 150 种酰基葡萄糖苷、125 种蒽醌、65 种黄烷醇和 15 种其他化合物。该研究表明,该分析策略适用于大黄中复杂天然产物的分析。