Literature DB >> 16335983

VEMS 3.0: algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins.

Rune Matthiesen1, Morten Beck Trelle, Peter Højrup, Jakob Bunkenborg, Ole N Jensen.   

Abstract

Protein and peptide mass analysis and amino acid sequencing by mass spectrometry is widely used for identification and annotation of post-translational modifications (PTMs) in proteins. Modification-specific mass increments, neutral losses or diagnostic fragment ions in peptide mass spectra provide direct evidence for the presence of post-translational modifications, such as phosphorylation, acetylation, methylation or glycosylation. However, the commonly used database search engines are not always practical for exhaustive searches for multiple modifications and concomitant missed proteolytic cleavage sites in large-scale proteomic datasets, since the search space is dramatically expanded. We present a formal definition of the problem of searching databases with tandem mass spectra of peptides that are partially (sub-stoichiometrically) modified. In addition, an improved search algorithm and peptide scoring scheme that includes modification specific ion information from MS/MS spectra was implemented and tested using the Virtual Expert Mass Spectrometrist (VEMS) software. A set of 2825 peptide MS/MS spectra were searched with 16 variable modifications and 6 missed cleavages. The scoring scheme returned a large set of post-translationally modified peptides including precise information on modification type and position. The scoring scheme was able to extract and distinguish the near-isobaric modifications of trimethylation and acetylation of lysine residues based on the presence and absence of diagnostic neutral losses and immonium ions. In addition, the VEMS software contains a range of new features for analysis of mass spectrometry data obtained in large-scale proteomic experiments. Windows binaries are available at http://www.yass.sdu.dk/.

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Year:  2005        PMID: 16335983     DOI: 10.1021/pr050264q

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


  30 in total

1.  Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications.

Authors:  Bruce D Pascal; Graham M West; Catherina Scharager-Tapia; Ricardo Flefil; Tina Moroni; Pablo Martinez-Acedo; Patrick R Griffin; Anthony C Carvalloza
Journal:  J Am Soc Mass Spectrom       Date:  2015-08-12       Impact factor: 3.109

2.  Parallel processing of large datasets from NanoLC-FTICR-MS measurements.

Authors:  Y E M van der Burgt; I M Taban; M Konijnenburg; M Biskup; M C Duursma; R M A Heeren; A Römpp; R V van Nieuwpoort; H E Bal
Journal:  J Am Soc Mass Spectrom       Date:  2006-10-19       Impact factor: 3.109

3.  Elimination of systematic mass measurement errors in liquid chromatography-mass spectrometry based proteomics using regression models and a priori partial knowledge of the sample content.

Authors:  Vladislav A Petyuk; Navdeep Jaitly; Ronald J Moore; Jie Ding; Thomas O Metz; Keqi Tang; Matthew E Monroe; Aleksey V Tolmachev; Joshua N Adkins; Mikhail E Belov; Alan R Dabney; Wei-Jun Qian; David G Camp; Richard D Smith
Journal:  Anal Chem       Date:  2007-12-29       Impact factor: 6.986

4.  Spectral dictionaries: Integrating de novo peptide sequencing with database search of tandem mass spectra.

Authors:  Sangtae Kim; Nitin Gupta; Nuno Bandeira; Pavel A Pevzner
Journal:  Mol Cell Proteomics       Date:  2008-08-14       Impact factor: 5.911

5.  DtaRefinery, a software tool for elimination of systematic errors from parent ion mass measurements in tandem mass spectra data sets.

Authors:  Vladislav A Petyuk; Anoop M Mayampurath; Matthew E Monroe; Ashoka D Polpitiya; Samuel O Purvine; Gordon A Anderson; David G Camp; Richard D Smith
Journal:  Mol Cell Proteomics       Date:  2009-12-17       Impact factor: 5.911

6.  A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry.

Authors:  Richard C Baliban; Peter A DiMaggio; Mariana D Plazas-Mayorca; Nicolas L Young; Benjamin A Garcia; Christodoulos A Floudas
Journal:  Mol Cell Proteomics       Date:  2010-01-26       Impact factor: 5.911

7.  A mixed integer linear optimization framework for the identification and quantification of targeted post-translational modifications of highly modified proteins using multiplexed electron transfer dissociation tandem mass spectrometry.

Authors:  Peter A DiMaggio; Nicolas L Young; Richard C Baliban; Benjamin A Garcia; Christodoulos A Floudas
Journal:  Mol Cell Proteomics       Date:  2009-08-07       Impact factor: 5.911

8.  GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

Authors:  Kristoffer T G Rigbolt; Jens T Vanselow; Blagoy Blagoev
Journal:  Mol Cell Proteomics       Date:  2011-05-20       Impact factor: 5.911

9.  Isolation of Pseudomonas fluorescens species highly resistant to pentachlorobenzene.

Authors:  Itxaso Montánchez; Anna Chao Kaberdina; Elena Sevillano; Lucía Gallego; Susana Rodríguez-Couto; Vladimir R Kaberdin
Journal:  Folia Microbiol (Praha)       Date:  2017-02-10       Impact factor: 2.099

10.  SweetSEQer, simple de novo filtering and annotation of glycoconjugate mass spectra.

Authors:  Oliver Serang; John W Froehlich; Jan Muntel; Gary McDowell; Hanno Steen; Richard S Lee; Judith A Steen
Journal:  Mol Cell Proteomics       Date:  2013-02-26       Impact factor: 5.911

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