Literature DB >> 17185772

Protein identification by tandem mass spectrometry and sequence database searching.

Alexey I Nesvizhskii1.   

Abstract

The shotgun proteomics strategy, based on digesting proteins into peptides and sequencing them using tandem mass spectrometry (MS/MS), has become widely adopted. The identification of peptides from acquired MS/MS spectra is most often performed using the database search approach. We provide a detailed description of the peptide identification process and review the most commonly used database search programs. The appropriate choice of the search parameters and the sequence database are important for successful application of this method, and we provide general guidelines for carrying out efficient analysis of MS/MS data. We also discuss various reasons why database search tools fail to assign the correct sequence to many MS/MS spectra, and draw attention to the problem of false-positive identifications that can significantly diminish the value of published data. To assist in the evaluation of peptide assignments to MS/MS spectra, we review the scoring schemes implemented in most frequently used database search tools. We also describe statistical approaches and computational tools for validating peptide assignments to MS/MS spectra, including the concept of expectation values, reversed database searching, and the empirical Bayesian analysis of PeptideProphet. Finally, the process of inferring the identities of the sample proteins given the list of peptide identifications is outlined, and the limitations of shotgun proteomics with regard to discrimination between protein isoforms are discussed.

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Year:  2007        PMID: 17185772     DOI: 10.1385/1-59745-275-0:87

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  58 in total

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3.  The protein expression landscape of the Arabidopsis root.

Authors:  Jalean J Petricka; Monica A Schauer; Molly Megraw; Natalie W Breakfield; J Will Thompson; Stoyan Georgiev; Erik J Soderblom; Uwe Ohler; Martin Arthur Moseley; Ueli Grossniklaus; Philip N Benfey
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-23       Impact factor: 11.205

Review 4.  Mass spectrometry based glycoproteomics--from a proteomics perspective.

Authors:  Sheng Pan; Ru Chen; Ruedi Aebersold; Teresa A Brentnall
Journal:  Mol Cell Proteomics       Date:  2010-08-24       Impact factor: 5.911

5.  Synapse-directed delivery of immunomodulators using T-cell-conjugated nanoparticles.

Authors:  Matthias T Stephan; Sirkka B Stephan; Peter Bak; Jianzhu Chen; Darrell J Irvine
Journal:  Biomaterials       Date:  2012-05-15       Impact factor: 12.479

6.  A method to enhance a1 ions and application for peptide sequencing and protein identification.

Authors:  Ning Liu; Wan Chan; Kim-Chung Lee; Zongwei Cai
Journal:  J Am Soc Mass Spectrom       Date:  2009-02-21       Impact factor: 3.109

7.  Mapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines.

Authors:  Erin L Crowgey; Andrea Matlock; Vidya Venkatraman; Justyna Fert-Bober; Jennifer E Van Eyk
Journal:  Methods Mol Biol       Date:  2017

Review 8.  A face in the crowd: recognizing peptides through database search.

Authors:  Jimmy K Eng; Brian C Searle; Karl R Clauser; David L Tabb
Journal:  Mol Cell Proteomics       Date:  2011-08-29       Impact factor: 5.911

9.  The standard protein mix database: a diverse data set to assist in the production of improved Peptide and protein identification software tools.

Authors:  John Klimek; James S Eddes; Laura Hohmann; Jennifer Jackson; Amelia Peterson; Simon Letarte; Philip R Gafken; Jonathan E Katz; Parag Mallick; Hookeun Lee; Alexander Schmidt; Reto Ossola; Jimmy K Eng; Ruedi Aebersold; Daniel B Martin
Journal:  J Proteome Res       Date:  2007-08-21       Impact factor: 4.466

10.  Predicting direct protein interactions from affinity purification mass spectrometry data.

Authors:  Ethan Dh Kim; Ashish Sabharwal; Adrian R Vetta; Mathieu Blanchette
Journal:  Algorithms Mol Biol       Date:  2010-10-29       Impact factor: 1.405

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