4.5 Article

ProteinProcessor: A probabilistic analysis using mass accuracy and the MS spectrum

期刊

PROTEOMICS
卷 16, 期 18, 页码 2480-2490

出版社

WILEY-BLACKWELL
DOI: 10.1002/pmic.201600137

关键词

Bayesian analysis; Bioinformatics; Protein sequencing; MALDI; Tandem mass spectrometry

资金

  1. Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services

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Current approaches to protein identification rely heavily on database matching of fragmentation spectra or precursor peptide ions. We have developed a method for MALDI TOF-TOF instrumentation that uses peptide masses and their measurement errors to confirm protein identifications from a first pass MS/MS database search. The method uses MS1-level spectral data that have heretofore been ignored by most search engines. This approach uses the distribution of mass errors of peptide matches in the MS1 spectrum to develop a probability model that is independent of the MS/MS database search identifications. Peptide mass matches can come from both precursor ions that have been fragmented as well as those that are tentatively identified by accurate mass alone. This additional corroboration enables us to confirm protein identifications to MS/MS-based scores that are otherwise considered to be only of moderate quality. Straightforward and easily applicable to current proteomic analyses, this tool termed Protein-Processor provides a robust and invaluable addition to current protein identification tools.

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