Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution

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Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution. / Claesen, Jürgen; Valkenborg, Dirk; Burzykowski, Tomasz.

In: Rapid Communications in Mass Spectrometry, Vol. 35, e9162, 08.07.2021, p. 1-8.

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Claesen, J, Valkenborg, D & Burzykowski, T 2021, 'Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution', Rapid Communications in Mass Spectrometry, vol. 35, e9162, pp. 1-8. https://doi.org/10.1002/rcm.9162

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Claesen, Jürgen ; Valkenborg, Dirk ; Burzykowski, Tomasz. / Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution. In: Rapid Communications in Mass Spectrometry. 2021 ; Vol. 35. pp. 1-8.

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@article{a49af2b11ada46cea9e0f70fe48ff346,
title = "Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution",
abstract = "RationaleIdentification of peptides and proteins is a challenging task in mass spectrometry–based proteomics. Knowledge of the number of sulfur atoms can improve the identification of peptides and proteins.MethodsIn this article, we propose a method for the prediction of S-atoms based on the aggregated isotope distribution. The Mahalanobis distance is used as dissimilarity measure to compare mass- and intensity-based features from the observed and theoretical isotope distributions.ResultsThe relative abundance of the second and the third aggregated isotopic variants (as compared to the monoisotopic one) and the mass difference between the second and third aggregated isotopic variants are the most important features to predict the number of S-atoms.ConclusionsThe mass and intensity accuracies of the observed aggregated isotopic variants are insufficient to accurately predict the number of atoms. However, using a limited set of predictions for a peptide, rather than predicting a single number of S-atoms, has a reasonably high prediction accuracy.",
keywords = "Resonance mass-spectrometry, Fine-structure, Resolution, Identification, Stategy",
author = "J{\"u}rgen Claesen and Dirk Valkenborg and Tomasz Burzykowski",
note = "Score=10",
year = "2021",
month = jul,
day = "8",
doi = "10.1002/rcm.9162",
language = "English",
volume = "35",
pages = "1--8",
journal = "Rapid Communications in Mass Spectrometry",
issn = "0951-4198",
publisher = "Wiley",

}

RIS - Download

TY - JOUR

T1 - Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution

AU - Claesen, Jürgen

AU - Valkenborg, Dirk

AU - Burzykowski, Tomasz

N1 - Score=10

PY - 2021/7/8

Y1 - 2021/7/8

N2 - RationaleIdentification of peptides and proteins is a challenging task in mass spectrometry–based proteomics. Knowledge of the number of sulfur atoms can improve the identification of peptides and proteins.MethodsIn this article, we propose a method for the prediction of S-atoms based on the aggregated isotope distribution. The Mahalanobis distance is used as dissimilarity measure to compare mass- and intensity-based features from the observed and theoretical isotope distributions.ResultsThe relative abundance of the second and the third aggregated isotopic variants (as compared to the monoisotopic one) and the mass difference between the second and third aggregated isotopic variants are the most important features to predict the number of S-atoms.ConclusionsThe mass and intensity accuracies of the observed aggregated isotopic variants are insufficient to accurately predict the number of atoms. However, using a limited set of predictions for a peptide, rather than predicting a single number of S-atoms, has a reasonably high prediction accuracy.

AB - RationaleIdentification of peptides and proteins is a challenging task in mass spectrometry–based proteomics. Knowledge of the number of sulfur atoms can improve the identification of peptides and proteins.MethodsIn this article, we propose a method for the prediction of S-atoms based on the aggregated isotope distribution. The Mahalanobis distance is used as dissimilarity measure to compare mass- and intensity-based features from the observed and theoretical isotope distributions.ResultsThe relative abundance of the second and the third aggregated isotopic variants (as compared to the monoisotopic one) and the mass difference between the second and third aggregated isotopic variants are the most important features to predict the number of S-atoms.ConclusionsThe mass and intensity accuracies of the observed aggregated isotopic variants are insufficient to accurately predict the number of atoms. However, using a limited set of predictions for a peptide, rather than predicting a single number of S-atoms, has a reasonably high prediction accuracy.

KW - Resonance mass-spectrometry

KW - Fine-structure

KW - Resolution

KW - Identification

KW - Stategy

UR - https://ecm.sckcen.be/OTCS/llisapi.dll/overview/48433387

U2 - 10.1002/rcm.9162

DO - 10.1002/rcm.9162

M3 - Article

VL - 35

SP - 1

EP - 8

JO - Rapid Communications in Mass Spectrometry

JF - Rapid Communications in Mass Spectrometry

SN - 0951-4198

M1 - e9162

ER -

ID: 7487984