Literature DB >> 17891751

Using a Poisson approximation to predict the isotopic distribution of sulphur-containing peptides in a peptide-centric proteomic approach.

Dirk Valkenborg1, Pryseley Assam, Grégoire Thomas, Luc Krols, Koen Kas, Tomasz Burzykowski.   

Abstract

Breen et al. (Electrophoresis 2000; 21: 2243) proposed a method for finding monoisotopic peptide peaks in mass spectra based on an approximation of the distribution of different isotopic variants of a peptide by a Poisson distribution. They developed the method using all protein sequences from the SWISS-PROT database. We investigate the suitability of this method to predict the isotopic distribution in an environment which enriches for peptides carrying sulphur. More specifically, we focus on mass spectra obtained by a COmbined FRActional DIagonal Chromatography (COFRADIC) approach, developed by Gevaert et al. (Nature Biotechnology 2003; 21: 566), targeting a specific subset of peptides, in this case the N-terminal peptides. One can therefore ask whether the original results of Breen et al. apply to spectra generated by the particular COFRADIC method. We investigate whether the proposed approximation holds for N-terminal peptides. We also evaluate whether ignoring sulphur atoms while developing the approximation, as proposed by Breen et al., does not increase the risk of missing monoisotopic peaks corresponding to sulphur-containing peptides. Finally, we check the sensitivity of the quality of the approximation to optimization criteria used in the development process. The results are not simply restricted to a COFRADIC setting but are also applicable more generally, for any method which enriches for sulphur-containing peptides. Copyright (c) 2007 John Wiley & Sons, Ltd.

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Year:  2007        PMID: 17891751     DOI: 10.1002/rcm.3237

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  10 in total

1.  An efficient method to calculate the aggregated isotopic distribution and exact center-masses.

Authors:  Jürgen Claesen; Piotr Dittwald; Tomasz Burzykowski; Dirk Valkenborg
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2.  A model-based method for the prediction of the isotopic distribution of peptides.

Authors:  Dirk Valkenborg; Ivy Jansen; Tomasz Burzykowski
Journal:  J Am Soc Mass Spectrom       Date:  2008-01-31       Impact factor: 3.109

3.  Comparison of the Mahalanobis distance and Pearson's χ² statistic as measures of similarity of isotope patterns.

Authors:  Fatemeh Zamanzad Ghavidel; Jürgen Claesen; Tomasz Burzykowski; Dirk Valkenborg
Journal:  J Am Soc Mass Spectrom       Date:  2013-11-19       Impact factor: 3.109

4.  Suppression correction and characteristic study in liquid chromatography/Fourier transform mass spectrometry measurements.

Authors:  Xuepo Ma; Travis J Hestilow; Jian Cui; Jianqiu Zhang
Journal:  Rapid Commun Mass Spectrom       Date:  2011-02-28       Impact factor: 2.419

5.  Poisson Model To Generate Isotope Distribution for Biomolecules.

Authors:  Rovshan G Sadygov
Journal:  J Proteome Res       Date:  2017-12-19       Impact factor: 4.466

6.  Review of peak detection algorithms in liquid-chromatography-mass spectrometry.

Authors:  Jianqiu Zhang; Elias Gonzalez; Travis Hestilow; William Haskins; Yufei Huang
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7.  ICPD-a new peak detection algorithm for LC/MS.

Authors:  Jianqiu Zhang; William Haskins
Journal:  BMC Genomics       Date:  2010-12-01       Impact factor: 3.969

Review 8.  Current challenges in software solutions for mass spectrometry-based quantitative proteomics.

Authors:  Salvatore Cappadona; Peter R Baker; Pedro R Cutillas; Albert J R Heck; Bas van Breukelen
Journal:  Amino Acids       Date:  2012-07-22       Impact factor: 3.520

9.  MRCQuant- an accurate LC-MS relative isotopic quantification algorithm on TOF instruments.

Authors:  William E Haskins; Konstantinos Petritis; Jianqiu Zhang
Journal:  BMC Bioinformatics       Date:  2011-03-15       Impact factor: 3.169

10.  A software application for comparing large numbers of high resolution MALDI-FTICR MS spectra demonstrated by searching candidate biomarkers for glioma blood vessel formation.

Authors:  Mark K Titulaer; Dana A N Mustafa; Ivar Siccama; Marco Konijnenburg; Peter C Burgers; Arno C Andeweg; Peter A E Sillevis Smitt; Johan M Kros; Theo M Luider
Journal:  BMC Bioinformatics       Date:  2008-03-01       Impact factor: 3.169

  10 in total

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