Abstract：
Liquid chromatography-mass spectrometry (LC-MS) guided isolation is a favored strategy to quickly and efficiently explore the chemical diversity of herbal medicines. In this study, two methods were adopted to improve the performance of the strategy, including offline two-dimensional (2D) LC to extend the peak capacities and predicted metabolites screening (PMS) to automatically screen the targets with expanded databases. Ginsenosides in the leaves of Panax notoginseng (PNL) were taken as a case. An offline 2D LC system was constructed with an orthogonality of 0.69 and peak capacity of 8925. Quadrupole time-of-flight mass spectrometry-fast data directed analysis (QTOF-Fast DDA) was employed for detection of the ginsenosides in the fractioned samples. Four modified groups, including glucose, xylose, rhamnose and malonyl, were adopted and markedly extended the screening coverage. The combined strategy showed about 7.5 times improvement in the screening capability. PMS is conveniently and automatically implemented in UNIFI. Using this strategy, 945 ginsenosides were discovered from PNL, including 662 potentially novel ginsenosides. Furthermore, two new ginsenosides were purified, and unambiguously identified by NMR analysis, partially demonstrating the LC-MS guided isolation. The combined strategy can also be applied in characterizing and discovering new bioactive constituents from other herbal medicines.
摘要：
液相色谱-质谱（LC-MS）引导分离是快速有效探索草药化学多样性的首选策略。在这项研究中,采用了两种方法来提高策略的性能，包括离线二维（2D）LC以扩展峰容量和预测代谢物筛选（PMS），以使用扩展的数据库自动筛选目标。以三七（PNL）叶片中的人参皂甙为例。构建了一个离线2DLC系统，正交度为0.69，峰值容量为8925。四极杆飞行时间质谱快速数据导向分析（QTOF-FastDDA）用于检测分割样品中的人参皂苷。四个修改组，包括葡萄糖,木糖,鼠李糖和丙二酰,被采纳并显著扩大了筛查覆盖面。组合策略显示筛选能力提高约7.5倍。PMS在UNIFT中方便且自动地实现。使用这个策略，从PNL中发现了945种人参皂苷，包括662个潜在的新人参皂苷。此外，纯化了两种新的人参皂苷，并通过NMR分析明确确定，部分证明了LC-MS引导的分离。组合策略还可以应用于表征和发现来自其他草药的新的生物活性成分。
