title: Prophossi: automating expert validation of phosphopeptide-spectrum matches from tandem mass spectrometry.
abstract: BACKGROUND
  Complex patterns of protein phosphorylation mediate many cellular processes. Tandem mass spectrometry (MS/MS) is a powerful tool for identifying these post-translational modifications. In high-throughput experiments, mass spectrometry database search engines, such as MASCOT provide a ranked list of peptide identifications based on hundreds of thousands of MS/MS spectra obtained in a mass spectrometry experiment. These search results are not in themselves sufficient for confident assignment of phosphorylation sites as identification of characteristic mass differences requires time-consuming manual assessment of the spectra by an experienced analyst. The time required for manual assessment has previously rendered high-throughput confident assignment of phosphorylation sites challenging.
  
  
  RESULTS
  We have developed a knowledge base of criteria, which replicate expert assessment, allowing more than half of cases to be automatically validated and site assignments verified with a high degree of confidence. This was assessed by comparing automated spectral interpretation with careful manual examination of the assignments for 501 peptides above the 1% false discovery rate (FDR) threshold corresponding to 259 putative phosphorylation sites in 74 proteins of the Trypanosoma brucei proteome. Despite this stringent approach, we are able to validate 80 of the 91 phosphorylation sites (88%) positively identified by manual examination of the spectra used for the MASCOT searches with a FDR < 15%.
  
  
  CONCLUSIONS
  High-throughput computational analysis can provide a viable second stage validation of primary mass spectrometry database search results. Such validation gives rapid access to a systems level overview of protein phosphorylation in the experiment under investigation.
  
  
  BACKGROUND
  A GPL licensed software implementation in Perl for analysis and spectrum annotation is available in the supplementary material and a web server can be assessed online at http://www.compbio.dundee.ac.uk/prophossi.
authors.affiliation: Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk
authors.forename: David M A
authors.initials: DM
authors.lastname: Martin
authors.forename: Isabelle R E
authors.initials: IR
authors.lastname: Nett
authors.forename: Franck
authors.initials: F
authors.lastname: Vandermoere
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Barber
authors.forename: Nicholas A
authors.initials: NA
authors.lastname: Morrice
authors.forename: Michael A J
authors.initials: MA
authors.lastname: Ferguson
mesh_terms: D000465:Algorithms; D001331:Automation; D016208:Databases, Factual; D010748:Phosphopeptides / Q000032:analysis*; D010766:Phosphorylation; D011499:Protein Processing, Post-Translational; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods*; D014346:Trypanosoma brucei brucei / Q000378:metabolism
chemical_list: D010748:Phosphopeptides