Literature DB >> 21539947

Clustering of MS spectra for improved protein identification rate and screening for protein variants and modifications by MALDI-MS/MS.

Irene Granlund1, Thomas Kieselbach, Rikard Alm, Wolfgang P Schröder, Cecilia Emanuelsson.   

Abstract

It is an established fact that allelic variation and post-translational modifications create different variants of proteins, which are observed as isoelectric and size subspecies in two-dimensional gel based proteomics. Here we explore the stromal proteome of spinach and Arabidopsis chloroplast and show that clustering of mass spectra is a useful tool for investigating such variants and detecting modified peptides with amino acid substitutions or post-translational modifications. This study employs data mining by hierarchical clustering of MALDI-MS spectra, using the web version of the SPECLUST program (http://bioinfo.thep.lu.se/speclust.html). The tool can also be used to remove peaks of contaminating proteins and to improve protein identification, especially for species without a fully sequenced genome. Mutually exclusive peptide peaks within a cluster provide a good starting point for MS/MS investigation of modified peptides, here exemplified by the identification of an A to E substitution that accounts for the isoelectric heterogeneity in protein isoforms.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21539947     DOI: 10.1016/j.jprot.2011.04.008

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  2 in total

1.  Fluorescent protein tagging as a tool to define the subcellular distribution of proteins in plants.

Authors:  Sandra K Tanz; Ian Castleden; Ian D Small; A Harvey Millar
Journal:  Front Plant Sci       Date:  2013-06-24       Impact factor: 5.753

2.  Mass-Up: an all-in-one open software application for MALDI-TOF mass spectrometry knowledge discovery.

Authors:  H López-Fernández; H M Santos; J L Capelo; F Fdez-Riverola; D Glez-Peña; M Reboiro-Jato
Journal:  BMC Bioinformatics       Date:  2015-10-05       Impact factor: 3.169

  2 in total

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