Deep investigation, profiling of chemical diversity of constituent compounds and discovery of novel structures is a great challenge. A novel comprehensive and effective approach to mine trace unknown compounds combined with structure recognition in complex matrix is developed, in order to profiling potential Chlorogenic acids (CGAs) in Lonicera Flos (LFs): using multiple neutral loss/precursor ion (NL/PI) markers scans combined with high resolution mass spectrometry (HRMS). The workflow included (i) Fragmentation rules deduced by Q-orbitrap and selection of multiple NL/PI markers. (ii) Multiple NL/PI marker scans and grouping of peaks that had responses on two or more channels. (iii) Alignment of peaks in Full-MS scan and multiple NL/PI scans. (iv) The precursor ions list was introduced to mine novel CGAs according to simulated molecular formula. (v) Identification and structure recognition with the aid of HRMS. The procedure proved to be valid to screen and identify 51 CGAs from Lonicera Flos (LFs) with 16 categories, especially dihydroxyphenyl and glucoside for the first time. Its application could also be extended for global profiling of other complicated chemical systems, such as Chinese medicinal formulas.

深入研究，分析组成化合物的化学多样性以及发现新结构是一项巨大的挑战。为了分析忍冬属植物（LFs）中潜在的绿原酸（CGA），使用多种中性损失/前体离子（NL / PI），开发了一种新型的综合有效的方法来挖掘痕量未知化合物并在复杂基质中进行结构识别标记扫描结合高分辨率质谱（HRMS）。工作流程包括（i）由Q-orbitrap推导的片段化规则以及多个NL / PI标记的选择。（ii）多次NL / PI标记扫描和在两个或更多通道上有响应的峰分组。（iii）Full-MS扫描和多个NL / PI扫描中的峰对齐。（iv）根据模拟分子式，引入了前体离子列表来挖掘新型CGA。v在人力资源管理系统的帮助下进行识别和结构识别。事实证明，该程序对于从忍冬属植物（LFs）中的16种类别的51种CGA（尤其是二羟苯基和葡萄糖苷）进​​行筛选和鉴定是有效的。它的应用也可以扩展到其他复杂化学系统的全球概要分析，例如中药配方。