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.

Genome and proteome analysis of Pseudomonas chloritidismutans AW‐1T that grows on n‐decane with chlorate or oxygen as electron acceptor

“…Overall, out of 118 362 spectra obtained 45 518 peptide spectral matches were found over the five conditions with a false discovery rate (FDR) of < 5% and a peptide-spectrum match (PSM) efficiency of 38% (Table 1), which is a reasonable value that is more often found (Ivanov et al, 2014). For each condition approximately 20 000 to 25 000 MS/MS spectra were obtained from trypsindigested protein mixtures of cell free extracts.…”

Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows

“…X!Tandem output files were converted to pepXML using pepxmltk utility [17]. MPscore [18] was applied to pepXML files for post-search validation. We also applied Percolator [19] to the Bfused^database search results to demonstrate the versatility of the proposed approach.…”

Scavager: A Versatile Postsearch Validation Algorithm for Shotgun Proteomics Based on Gradient Boosting

“…CatBoost was chosen for Scavager for its efficiency, speed, and thorough overfitting protection. While we have applied the experience obtained from our previously developed MP score postsearch validation tool, Scavager is a completely new software that uses a different scoring model and supports a wider range of search engines.…”