title: Defining parameters for homology-tolerant database searching.
abstract: De novo interpretation of tandem mass spectrometry (MS/MS) spectra provides sequences for searching protein databases when limited sequence information is present in the database. Our objective was to define a strategy for this type of homology-tolerant database search. Homology searches, using MS-Homology software, were conducted with 20, 10, or 5 of the most abundant peptides from 9 proteins, based either on precursor trigger intensity or on total ion current, and allowing for 50%, 30%, or 10% mismatch in the search. Protein scores were corrected by subtracting a threshold score that was calculated from random peptides. The highest (p < .01) corrected protein scores (i.e., above the threshold) were obtained by submitting 20 peptides and allowing 30% mismatch. Using these criteria, protein identification based on ion mass searching using MS/MS data (i.e., Mascot) was compared with that obtained using homology search. The highest-ranking protein was the same using Mascot, homology search using the 20 most intense peptides, or homology search using all peptides, for 63.4% of 112 spots from two-dimensional polyacrylamide gel electrophoresis gels. For these proteins, the percent coverage was greatest using Mascot compared with the use of all or just the 20 most intense peptides in a homology search (25.1%, 18.3%, and 10.6%, respectively). Finally, 35% of de novo sequences completely matched the corresponding known amino acid sequence of the matching peptide. This percentage increased when the search was limited to the 20 most intense peptides (44.0%). After identifying the protein using MS-Homology, a peptide mass search may increase the percent coverage of the protein identified.
authors.affiliation: USDA, ARS, RLH US Meat Animal Research Center, Clay Center, NE 68933, USA.
authors.forename: J P
authors.initials: JP
authors.lastname: Kayser
authors.forename: J L
authors.initials: JL
authors.lastname: Vallet
authors.forename: R L
authors.initials: RL
authors.lastname: Cerny
mesh_terms: D000595:Amino Acid Sequence; D030562:Databases, Protein; D010455:Peptides / Q000737:chemistry / Q000235:genetics; D017386:Sequence Homology, Amino Acid; D012984:Software
chemical_list: D010455:Peptides