Search-space reduction of a non-redundant peptide database

Ian Shadforth, Daniel Crowther, Conrad Bessant

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Peptide mass fingerprinting and database searching with tandem mass spectrometry are two methods commonly employed to identify proteins in a sample. However, up to 90% of peptides can remain unidentified. In this paper, a search-space filter using amino acids identified by a novel de novo methodology is presented. This provides a high-accuracy set of amino acid predictions through exploiting the internal fragmentation of amino acid chains during tandem mass spectrometry. These predictions are used to reduce the number of peptides considered from a non-redundant peptide database. The presence of one confirmed amino acid can be used to reduce the search-database size by between 33% (Leucine) and 83% (Tryptophan). One or more accurate amino acid identifications are made in 18% of simulated and 9% of experimental peptide spectra considered. Given the large proportion of currently unidentified peptides, this method represents a useful tool for increasing peptide identification rates.

Original languageEnglish
Title of host publicationProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
Pages470-471
Number of pages2
DOIs
Publication statusPublished - 31 Aug 2004
EventProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA, United States
Duration: 16 Aug 200419 Aug 2004

Publication series

NameProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

Conference

ConferenceProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
CountryUnited States
CityStanford, CA
Period16/08/0419/08/04

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  • Cite this

    Shadforth, I., Crowther, D., & Bessant, C. (2004). Search-space reduction of a non-redundant peptide database. In Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 (pp. 470-471). (Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004). https://doi.org/10.1109/CSB.2004.1332462