State Key Laboratory of Natural Medicines, Key Lab of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Tongjiaxiang 24, Nanjing 210009, China.
J Chromatogr A. 2012 Mar 2;1227:234-44. doi: 10.1016/j.chroma.2012.01.017. Epub 2012 Jan 14.
This study was to develop and evaluate a practical approach of mass defect filtering (MDF), a post-acquisition data processing technique, for the rapid classification of complicated peaks into well-known chemical families based on the exact mass acquired by high resolution mass spectrometry. The full-scan LC-MS/MS data of the Ophiopogon japonicus extract was acquired using high performance liquid chromatography coupled with hybrid quadrupole-time of flight (LCMS-Q-TOF) system which features high resolution, mass accuracy, and sensitivity. To remove the interferences of the complex matrix, MDF approach was developed and employed to rapidly pick out the peaks of ophiopogonins and ophiopogonones from full-scan mass chromatograms. The accuracy of MDF was evaluated in reference to the result of structural identification. After the MDF based classification, both target and non-target components in Ophiopogon japonicus extract were characterized based on the detailed fragment ions analysis in the hybrid ion trap and time-of-flight mass spectrometry (LCMS-IT-TOF). By this approach, more than 50 ophiopogonins and 27 ophiopogonones were structurally characterized. The present results of rapid detection and identification of ophiopogonins and ophiopogonones suggest that the proposed MDF approach based on the high-resolution mass spectrometry data would be expected adaptable to the analysis of other herbal components.
本研究旨在开发和评估一种实用的质量亏损过滤(MDF)方法,这是一种采集后数据处理技术,可根据高分辨率质谱获得的精确质量,将复杂峰快速分类为已知的化学家族。采用高性能液相色谱-混合四极杆飞行时间(LCMS-Q-TOF)系统获得麦冬提取物的全扫描 LC-MS/MS 数据,该系统具有高分辨率、质量精度和灵敏度。为了去除复杂基质的干扰,开发并采用 MDF 方法从全扫描质量色谱中快速提取麦冬皂苷和麦冬酮的峰。MDF 的准确性通过结构鉴定的结果进行评估。在基于 MDF 的分类之后,根据混合离子阱和飞行时间质谱(LCMS-IT-TOF)中的详细碎片离子分析,对麦冬提取物中的目标和非目标成分进行了表征。通过这种方法,鉴定了 50 多种麦冬皂苷和 27 种麦冬酮。麦冬皂苷和麦冬酮的快速检测和鉴定的结果表明,基于高分辨率质谱数据的 MDF 方法有望适用于其他草药成分的分析。