Abstract
The localization of phosphorylation sites in peptide sequences is a challenging problem in large-scale phosphoproteomics analysis. The intense neutral loss peaks and the coexistence of multiple serine/threonine and/or tyrosine residues are limiting factors for objectively scoring site patterns across thousands of peptides. Various computational approaches for phosphorylation site localization have been proposed, including Ascore, Mascot Delta score, and ProteinProspector, yet few address direct estimation of the false localization rate (FLR) in each experiment. Here we propose LuciPHOr, a modified target-decoy-based approach that uses mass accuracy and peak intensities for site localization scoring and FLR estimation. Accurate estimation of the FLR is a difficult task at the individual-site level because the degree of uncertainty in localization varies significantly across different peptides. LuciPHOr carries out simultaneous localization on all candidate sites in each peptide and estimates the FLR based on the target-decoy framework, where decoy phosphopeptides generated by placing artificial phosphorylation(s) on non-candidate residues compete with the non-decoy phosphopeptides. LuciPHOr also reports approximate site-level confidence scores for all candidate sites as a means to localize additional sites from multiphosphorylated peptides in which localization can be partially achieved. Unlike the existing tools, LuciPHOr is compatible with any search engine output processed through the Trans-Proteomic Pipeline. We evaluated the performance of LuciPHOr in terms of the sensitivity and accuracy of FLR estimates using two synthetic phosphopeptide libraries and a phosphoproteomic dataset generated from complex mouse brain samples.
Highlights
Phosphorylation is a common and essential form of posttranslational regulation that has been extensively studied via mass spectrometry [1,2,3,4,5]
LuciPHOr—A Phosphorylation Site Localization Algorithm with false localization rate (FLR) Estimation trast, the Mascot Delta score (MD-score)1 determines the confidence of phosphosite localization on peptides as the difference in Mascot ion scores between the highest scoring phosphopeptide and the best scoring phosphopermutation (same peptide sequence, alternative phosphorylation site [17])
We highlight the practical utility of LuciPHOr, which is capable of processing the results of any database search tool (including commonly used search engines X! Tandem [19], SEQUEST [20], and Mascot [21]) that is supported by the widely used Trans-Proteomic Pipeline (TPP) [22]
Summary
Phosphorylation is a common and essential form of posttranslational regulation that has been extensively studied via mass spectrometry [1,2,3,4,5]. A number of computational approaches that localize phosphorylation sites have been reported in the literature, enabling automated phosphoproteomic analysis (reviewed in Ref. 9) These tools either rescore the MS/MS spectra to assign confidence measures for individual sites based on site-determining ions (10 –15) or derive localization scores directly from the search engine output [16, 17]. A similar idea was implemented in the SLIP score using a modified version of the Batch-Tag search engine of the ProteinProspector suite [16] and in the variable modification localization score of the proprietary software Spectrum Mill [9] These tools, apply the logic of delta scoring for individual sites, not for the whole peptide; this is an important consideration in the case of multiply phosphorylated peptides. The performance of LuciPHOr is further investigated using a complex mouse brain dataset, and we discuss the issue of site-level scoring in the analysis of multiphosphorylated peptides
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