Approximating Isotope Distributions of Biomolecule Fragments.

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. Theoretical and approximated isotope distributions are consistent for fragments of in silico digested peptides. Furthermore, mass spectrometry experiments with the angiotensin I peptide and HeLa cell lysate demonstrate that the fragment methods match isotope peaks in MS2 spectra more accurately than the precursor Averagine approach. The algorithms for the approximation of fragment isotope distributions have been added to the OpenMS software library. By providing the means for analyzing fragment isotopic distributions, these methods will improve MS2 spectra interpretation.