Radical Fragment Ions in Collision-Induced Dissociation Mass Spectrometry

16 September 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Collision-induced dissociation (CID) is a common fragmentation strategy in mass spectrometry (MS) analysis. A conventional understanding is that fragment ions generated in low-energy CID should follow the even-electron rule. As such, (de)protonated precursor ions should predominately generate (de)protonated fragment ions with very few radical fragment ions (RFIs). However, the extent to which RFIs present in MS2 spectra has not been comprehensively investigated. This work uses the latest NIST 20 tandem mass spectral library to investigate of the occurrence of RFIs in CID MS2 experiments. In particular, RFIs were recognized using their integer double bond equivalent (DBE) values calculated from their annotated molecular formulas. Our study shows unexpected results as 65.4% and 68.8% of MS2 spectra contain at least 10% RFIs by ion-count (total number of ions) in positive and negative electrospray ionization (ESI) modes, respectively. Furthermore, we classified chemicals based on their compound classes and chemical substructures, and calculated the percentages of RFIs in each class. Results show that “Organic 1,3-dipolar compounds” and “Lignans, neolignans and related compounds” are the top 2 compound superclasses which tend to produce RFIs in their CID MS2 spectra. Moreover, aromatic, arylbromide, heteroaromatic, alkylarylether, phenol, and conjugated double bond-containing chemicals are more likely to produce RFIs. We also found four possible patterns of change in RFI percentages as a function of CID collision energy. Finally, we demonstrate that the inadequate consideration of RFIs in most conventional bioinformatic tools might cause problems during in silico fragmentation and de novo annotation of MS2 spectra. This work provides a further understanding of CID MS2 mechanism, and the unexpectedly large percentage of RFIs suggests a need for consideration in the development of bioinformatic software for MS2 interpretation.

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