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Determination of partial amino acid composition from tandem mass spectra for use in peptide identification strategies
Author(s) -
Shadforth Ian,
Todd Kieran,
Crowther Daniel,
Bessant Conrad
Publication year - 2005
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200401058
Subject(s) - tandem mass spectrometry , chemistry , peptide , mass spectrometry , tandem , mass spectrum , amino acid , biological system , ion , chromatography , pipeline (software) , analytical chemistry (journal) , computer science , materials science , biology , biochemistry , organic chemistry , composite material , programming language
Abstract We demonstrate a new approach to the determination of amino acid composition from tandem mass spectrometrically fragmented peptides using both experimental and simulated data. The approach has been developed to be used as a search‐space filter in a protein identification pipeline with the aim of increased performance above that which could be attained by using immonium ion information. Three automated methods have been developed and tested: one based upon a simple peak traversal, in which all intense ion peaks are treated as being either a b‐ or y‐ion using a wide mass tolerance; a second which uses a much narrower tolerance and does not perform transformations of ion peaks to the complementary type; and the unique fragments method which allows for b‐ or y‐ion type to be inferred and corroborated using a scan of the other ions present in each peptide spectrum. The combination of these methods is shown to provide a high‐accuracy set of amino acid predictions using both experimental and simulated data sets. These high quality predictions, with an accuracy of over 85%, may be used to identify peptide fragments that are hard to identify using other methods. The data simulation algorithm is also shown post priori to be a good model of noiseless tandem mass spectrometric peptide data.