In mass spectrometry (MS)-based proteomics, protein and peptide sequences are determined by the isolation and subsequent fragmentation of precursor ions. When an isolation window captures only part of a precursor’s isotopic distribution, the isotope distributions of the fragments depend on the subset of isolated precursor isotopes. Approximation of the expected isotope distributions of these fragments prior to sequence determination enables MS2 deisotoping, monoisotopic mass calculation, charge assignment of fragment peaks, and deconvolution of chimeric spectra. However, currently such methods do not exist, and precursor isotope distributions are often used as a proxy. Here, we present methods that approximate the isotope distribution of a biomolecule’s fragment given its monoisotopic mass, the monoisotopic mass of its precursor, the set of isolated precursor isotopes, and optionally sulfur atom content. Our methods use either the Averagine model or splines, the latter of which have similar accuracy to the Averagine approach, but are 20 times faster to compute. Theoreticaland approximated isotope distributions are consistent for fragmentsof in silico digested peptides. Furthermore, mass spectrometry experimentswith the angiotensin I peptide and HeLa cell lysate demonstrate thatthe fragment methods match isotope peaks in MS2 spectra more accuratelythan the precursor Averagine approach. The algorithms for the approximationof fragment isotope distributions have been added to the OpenMS softwarelibrary. By providing the means for analyzing fragment isotopic distributions,these methods will improve MS2 spectra interpretation.
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