Title：
A structure database and in silico mass spectral library for in-depth profiling of glucosinolates in plants by high-resolution tandem mass spectrometry
Authors：
Corresponding
Author：
Jing Li, Jie Gao, Guangqin Cai, Jun Ding*
Pubyear：
2026
Title of
Journal：
Food Chemistry
Paper
Code：
Volume：
518
Number：
Page：
518:149695.
Others：
Classification：
Source：
Abstract：
Glucosinolates (GSLs) are bioactive secondary metabolites in Brassicaceae plants that contribute to both food flavor and plant defense. Their untargeted profiling is challenging because of the large discrepancy between their high chemical diversity and the limited availability of authentic standards. To address this gap, we developed an in silico mass spectral library containing 142 previously reported and 1776 computationally generated GSL species. The corresponding high-resolution MS/MS spectra were predicted based on fragmentation rules learned from standards. Compatible with NIST MS Search and MS-DIAL, the library enables automatic GSL annotation without the need for chemical standards. Application to 13 Brassicaceae species annotated 107 endogenous GSLs, including 36 unreported candidate species, which markedly expanded known GSL diversity. Distinct GSL patterns reveal species-specific chemical signatures and functional responses to pathogen infection. The library provides a robust structural and mass spectral resource for untargeted GSL profiling, enabling systematic exploration of GSL diversity in plants.
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