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Identification of Glycosylated and Prenylated (Iso)flavonoids Using cIMS-MS
Carlo Roberto de Bruin1, Quentin Duez2,3, Marie Hennebelle1
1Laboratory of Food Chemistry, Department of Agrotechnology and Food Sciences, Wageningen University, 6708 WG Wageningen, The Netherlands.
Analytical Chemistry
|April 30, 2026
Summary
A new cyclic ion mobility-MS (cIMS-MS) method enhances (iso)flavonoid identification in plant extracts. This approach uses collisional cross section (CCS) values to differentiate isomers, improving accuracy in complex mixtures.
Area of Science:
- Analytical Chemistry
- Natural Product Chemistry
- Biochemistry
Background:
- Identification of (iso)flavonoids and their isomers is crucial due to varying bioactivities.
- Complex plant extracts pose challenges for isomer differentiation using traditional LC-MSⁿ due to similar retention times and fragmentation patterns.
Purpose of the Study:
- To develop and validate a cyclic ion mobility-MS (cIMS-MS) method for improved identification of prenylated and glycosylated (iso)flavonoids.
- To establish a library of collisional cross section (CCS) values for (iso)flavonoid isomers.
Main Methods:
- Development of a cIMS-MS method utilizing lithium adducts for high-resolution separation.
- Creation of a library of cIMS-CCS<0xE2><0x82><0x99> values for 51 (iso)flavonoids.
- Statistical analysis of CCS values to differentiate isomers.
- Exploration of modeling and molecular dynamics for CCS prediction.
Main Results:
- Lithium adducts provided the most stable ions and high-resolution separation.
- Statistically significant differences in cIMS-CCS<0xE2><0x82><0x99> values were found for 47 out of 50 isomer pairs.
- The cIMS-MS method, combined with LC-MSⁿ, successfully identified several (iso)flavonoids in a licorice root extract.
Conclusions:
- The developed cIMS-MS method, incorporating cIMS-CCS<0xE2><0x82><0x99> values, significantly enhances the identification of substituted (iso)flavonoids and their isomers in complex matrices.
- This approach offers a powerful tool for natural product research and analysis.
