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Monoisotopic mass determination algorithm for selenocysteine-containing polypeptides from mass spectrometric data based on theoretical modeling of isotopic peak intensity ratios

Title
Monoisotopic mass determination algorithm for selenocysteine-containing polypeptides from mass spectrometric data based on theoretical modeling of isotopic peak intensity ratios
Authors
Kim J.W.Lee S.Park K.Na S.Paek E.Park H.S.Park H.Lee K.-J.Jeong J.Kim H.-Y.
Ewha Authors
이공주
SCOPUS Author ID
이공주scopus
Issue Date
2012
Journal Title
Journal of Proteome Research
ISSN
1535-3893JCR Link
Citation
vol. 11, no. 9, pp. 4488 - 4498
Indexed
SCI; SCIE; SCOPUS WOS scopus
Abstract
Selenoproteins, containing selenocysteine (Sec, U) as the 21st amino acid in the genetic code, are well conserved from bacteria to human, except yeast and higher plants that miss the Sec insertion machinery. Determination of Sec association is important to find substrates and to understand redox action of selenoproteins. While mass spectrometry (MS) has become a common and powerful tool to determine an amino acid sequence of a protein, identification of a protein sequence containing Sec was not easy using MS because of the limited stability of Sec in selenoproteins. Se has six naturally occurring isotopes, 74Se, 76Se, 77Se, 78Se, 80Se, and 82Se, and 80Se is the most abundant isotope. These characteristics provide a good indicator for selenopeptides but make it difficult to detect selenopeptides using software analysis tools developed for common peptides. Thus, previous reports verified MS scans of selenopeptides by manual inspection. None of the fully automated algorithms have taken into account the isotopes of Se, leading to the wrong interpretation for selenopeptides. In this paper, we present an algorithm to determine monoisotopic masses of selenocysteine-containing polypeptides. Our algorithm is based on a theoretical model for an isotopic distribution of a selenopeptide, which regards peak intensities in an isotopic distribution as the natural abundances of C, H, N, O, S, and Se. Our algorithm uses two kinds of isotopic peak intensity ratios: one for two adjacent peaks and another for two distant peaks. It is shown that our algorithm for selenopeptides performs accurately, which was demonstrated with two LC-MS/MS data sets. Using this algorithm, we have successfully identified the Sec-Cys and Sec-Sec cross-linking of glutaredoxin 1 (GRX1) from mass spectra obtained by UPLC-ESI-q-TOF instrument. © 2012 American Chemical Society.
DOI
10.1021/pr300232y
Appears in Collections:
약학대학 > 약학과 > Journal papers
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