Literature DB >> 31290668

PTMProphet: Fast and Accurate Mass Modification Localization for the Trans-Proteomic Pipeline.

David D Shteynberg1, Eric W Deutsch1, David S Campbell1, Michael R Hoopmann1, Ulrike Kusebauch1, Dave Lee2, Luis Mendoza1, Mukul K Midha1, Zhi Sun1, Anthony D Whetton2, Robert L Moritz1.   

Abstract

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms, and demonstrate its performance on ground-truth synthetic peptide reference data sets, one previously published small data set, one new larger data set, and also on a previously published phosphoenriched data set where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.

Entities:  

Keywords:  PTM localization; PTMProphet; PTMs; TPP; mass spectrometry; protein phosphorylation; proteomics; reference data set analysis

Mesh:

Substances:

Year:  2019        PMID: 31290668      PMCID: PMC6898736          DOI: 10.1021/acs.jproteome.9b00205

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  47 in total

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