A strategy of combining energy-resolved mass spectrometry and density functional theory for the recognition of forsythoside isomers

Chuhui Lin, Yangkun Sun, Jingjing Kuang, Hongyang Zhang, Haoyu Yang, Min Zhang, Ping Hu

RAPID COMMUNICATIONS IN MASS SPECTROMETRY(2024)

Cited 0|Views7
No score
Abstract
RationaleIsomerism is very common in nature, and the mass spectrometry (MS) behavior of isomers is highly similar, making their spectral analysis and identification difficult. Computational chemistry can effectively assist the study of MS spectra and molecule structures. Herein, three isomers of forsythoside (For-A, For-H, and For-I) were successfully identified using energy-resolved MS combined with density functional theory (DFT).MethodsThe MS scan spectra of the isomers were collected in electrospray ionization MS. The possible positive/negative ion adduct sites were investigated using the DFT method, and the molecular formation energy of each precursor ion was obtained. In the multireaction monitoring mode, the spectra of the common precursor ion -> product ion pair of the three isomers were acquired under different collision energy, and the optimal collision energy (OCE) and maximum relative intensity (MRI) of each product ion were obtained. The energy of the broken chemical bond was calculated.ResultsThe experimental data showed that the product ions of [M + H]+ of the three isomers have the greatest differences in OCE and MRI and were the most suitable to distinguish the three isomers. The DFT data showed that there was a good positive correlation between the bond fragmentation energy calculated by the quasi-molecular ion model and OCE. The results indicated that the energy of precursor ions and corresponding fragments could be correlated with their experimental spectra.ConclusionsA strategy of combining energy-resolved MS and DFT was implemented on the recognition of forsythoside isomers, and this strategy was expected to be applied to the identification of more isomers.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined