title: Empirical multidimensional space for scoring peptide spectrum matches in shotgun proteomics.
abstract: Data-dependent tandem mass spectrometry (MS/MS) is one of the main techniques for protein identification in shotgun proteomics. In a typical LC-MS/MS workflow, peptide product ion mass spectra (MS/MS spectra) are compared with those derived theoretically from a protein sequence database. Scoring of these matches results in peptide identifications. A set of peptide identifications is characterized by false discovery rate (FDR), which determines the fraction of false identifications in the set. The total number of peptides targeted for fragmentation is in the range of 10,000 to 20,000 for a several-hour LC-MS/MS run. Typically, <50% of these MS/MS spectra result in peptide-spectrum matches (PSMs). A small fraction of PSMs pass the preset FDR level (commonly 1%) giving a list of identified proteins, yet a large number of correct PSMs corresponding to the peptides originally present in the sample are left behind in the "grey area" below the identity threshold. Following the numerous efforts to recover these correct PSMs, here we investigate the utility of a scoring scheme based on the multiple PSM descriptors available from the experimental data. These descriptors include retention time, deviation between experimental and theoretical mass, number of missed cleavages upon in-solution protein digestion, precursor ion fraction (PIF), PSM count per sequence, potential modifications, median fragment mass error, (13)C isotope mass difference, charge states, and number of PSMs per protein. The proposed scheme utilizes a set of metrics obtained for the corresponding distributions of each of the descriptors. We found that the proposed PSM scoring algorithm differentiates equally or more efficiently between correct and incorrect identifications compared with existing postsearch validation approaches.
authors.affiliation: Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences , 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia.
authors.forename: Mark V
authors.initials: MV
authors.lastname: Ivanov
authors.forename: Lev I
authors.initials: LI
authors.lastname: Levitsky
authors.forename: Anna A
authors.initials: AA
authors.lastname: Lobas
authors.forename: Tanja
authors.initials: T
authors.lastname: Panic
authors.forename: Ünige A
authors.initials: ÜA
authors.lastname: Laskay
authors.forename: Goran
authors.initials: G
authors.lastname: Mitulovic
authors.forename: Rainer
authors.initials: R
authors.lastname: Schmid
authors.forename: Marina L
authors.initials: ML
authors.lastname: Pridatchenko
authors.forename: Yury O
authors.initials: YO
authors.lastname: Tsybin
authors.forename: Mikhail V
authors.initials: MV
authors.lastname: Gorshkov
mesh_terms: D010449:Peptide Mapping / Q000379:methods*; D010455:Peptides / Q000032:analysis / Q000737:chemistry / Q000145:classification*; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D053719:Tandem Mass Spectrometry / Q000379:methods
chemical_list: D010455:Peptides