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Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution
RATIONALE: Identification 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. METHODS: In this article, we propose a method for the prediction of S‐atoms based on the ag...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459233/ https://www.ncbi.nlm.nih.gov/pubmed/34240492 http://dx.doi.org/10.1002/rcm.9162 |
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author | Claesen, Jürgen Valkenborg, Dirk Burzykowski, Tomasz |
author_facet | Claesen, Jürgen Valkenborg, Dirk Burzykowski, Tomasz |
author_sort | Claesen, Jürgen |
collection | PubMed |
description | RATIONALE: Identification 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. METHODS: In 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. RESULTS: The 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. CONCLUSIONS: The 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. |
format | Online Article Text |
id | pubmed-8459233 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84592332021-09-28 Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution Claesen, Jürgen Valkenborg, Dirk Burzykowski, Tomasz Rapid Commun Mass Spectrom Research Articles RATIONALE: Identification 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. METHODS: In 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. RESULTS: The 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. CONCLUSIONS: The 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. John Wiley and Sons Inc. 2021-08-05 2021-10-15 /pmc/articles/PMC8459233/ /pubmed/34240492 http://dx.doi.org/10.1002/rcm.9162 Text en © 2021 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Claesen, Jürgen Valkenborg, Dirk Burzykowski, Tomasz Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
title | Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
title_full | Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
title_fullStr | Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
title_full_unstemmed | Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
title_short | Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
title_sort | predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459233/ https://www.ncbi.nlm.nih.gov/pubmed/34240492 http://dx.doi.org/10.1002/rcm.9162 |
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