Effectively addressing complex proteomic search spaces with peptide spectrum matching

Bioinformatics. 2013 May 15;29(10):1343-4. doi: 10.1093/bioinformatics/btt106. Epub 2013 Feb 27.

Abstract

Summary: Protein identification by mass spectrometry is commonly accomplished using a peptide sequence matching search algorithm, whose sensitivity varies inversely with the size of the sequence database and the number of post-translational modifications considered. We present the Spectrum Identification Machine, a peptide sequence matching tool that capitalizes on the high-intensity b1-fragment ion of tandem mass spectra of peptides coupled in solution with phenylisotiocyanate to confidently sequence the first amino acid and ultimately reduce the search space. We demonstrate that in complex search spaces, a gain of some 120% in sensitivity can be achieved.

Availability: All data generated and the software are freely available for academic use at http://proteomics.fiocruz.br/software/sim.

Contact: paulo@pcarvalho.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Amino Acid Sequence
  • Escherichia coli / chemistry*
  • Escherichia coli Proteins / analysis*
  • Escherichia coli Proteins / chemistry
  • Mass Spectrometry
  • Peptides / analysis*
  • Peptides / chemistry
  • Protein Processing, Post-Translational
  • Proteomics / methods*
  • Software

Substances

  • Escherichia coli Proteins
  • Peptides