Improving natural products identification through molecular features-oriented precursor ion selection and targeted MS/MS analysis: a case study of Zhi-Ke-Yang-Yin capsule

RSC Adv. 2022 Nov 22;12(51):33340-33347. doi: 10.1039/d2ra06063a. eCollection 2022 Nov 15.

Abstract

Chemical substance identification is an indispensable step in research on therapeutic materials based on traditional Chinese medicine and its formulas. The successful characterization of chemical substances mainly relies on high-quality MS/MS spectra. However, to date, relatively few studies have specifically addressed the issues of improving the acquisition of MS/MS spectra of compounds for characterization. The current auto-MS/MS mode, where the precursor ions are selected depending on their signal intensity, encounters a drawback when the sample contains many overlapping signals, leading to compounds with a lower or much lower abundance missing identification. To solve this problem, a strategy in which molecular features oriented precursor ion selection was followed by targeted MS/MS analysis for structure elucidation was proposed. The precursor ions were selected according to their first and second molecular features, namely m/z and retention time, irrespective of their intensities. By performing targeted MS/MS analysis, the MS/MS spectra of many more compounds of interest can be obtained, leading to an improvement in natural product identification. As an example, the chemical substances in the Zhi-Ke-Yang-Yin extract were analyzed using this strategy, and as a result, 431 ingredients were tentatively characterized, including both known and unknown or new compounds.