Calculations of relative intensities of fragment ions in the MSMS spectra of a doubly charged penta-peptide

Abstract

Doc number: S13

Abstract

Background: Currently, the tandem mass spectrometry (MSMS) of peptides is a dominant technique used to identify peptides and consequently proteins. The peptide fragmentation inside the mass analyzer typically offers a spectrum containing several different groups of ions. The mass to charge (m/z ) values of these ions can be exactly calculated following simple rules based on the possible peptide fragmentation reactions. But the (relative) intensities of the particular ions cannot be simply predicted from the amino-acid sequence of the peptide. This study presents initial work towards developing a theoretical fundamental approach to ion intensity elucidation by utilizing quantum mechanical computations.

Methods: MSMS spectra of the doubly charged GAVLK peptide were collected on electrospray ion trap mass spectrometers using low energy modes of fragmentation. Density functional theory (DFT) calculations were performed on the population of ion precursors to determine the fragment ion intensities corresponding to a Boltzmann distribution of the protonation of nitrogens in the peptide backbone amide bonds.

Results: We were able to a) predict the y and b ions intensities order in concert with the experimental observation; b) predict relative intensities of y ions with errors not exceeding the experimental variation.

Conclusions: These results suggest that the GAVLK peptide fragmentation process in the ion trap mass spectrometer is predominantly driven by the thermodynamic stability of the precursor ions formed upon ionization of the sample. The computational approach presented in this manuscript successfully calculated ion intensities in the mass spectra of this doubly charged tryptic peptide, based solely on its amino acid sequence. As such, this work indicates a potential of incorporating quantum mechanical calculations into mass spectrometry based algorithms for molecular identification.