A graph-based approach for modification site assignment in proteomics

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Main Authors: Skiadopoulou, Dafni, Käll, Lukas, Barsnes, Harald, Schwämmle, Veit, Vaudel, Marc
Format: Preprint
Published: 2025
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author Skiadopoulou, Dafni
Käll, Lukas
Barsnes, Harald
Schwämmle, Veit
Vaudel, Marc
author_facet Skiadopoulou, Dafni
Käll, Lukas
Barsnes, Harald
Schwämmle, Veit
Vaudel, Marc
contents Background In proteomics, the most probable localizations of post-translational modifications are assessed by localization scores evaluating the likelihood of a given modification to occupy a site on a peptide sequence. When identifying highly modified peptides, localization scores for different modifications can return conflicting results, stacking modifications on the same amino acid. Here, we propose a graph-based approach that assigns modifications to sites in a way that maximizes localization scores while avoiding conflicting assignments. Results The algorithm is implemented as both a standalone Python program and in the compomics-utilities Java library. Our graph-based approach showed the ability to match complex combinations of modifications and acceptor sites, allowing the processing of thousands of peptides in a few seconds. Conclusions Our graph-based approach to modification site assignment allows distributing multiple modifications in a way that maximizes individual localization scores. Having an optimal modification site assignment is important for spectrum annotation and biological interpretation.
format Preprint
id arxiv_https___arxiv_org_abs_2505_17755
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A graph-based approach for modification site assignment in proteomics
Skiadopoulou, Dafni
Käll, Lukas
Barsnes, Harald
Schwämmle, Veit
Vaudel, Marc
Quantitative Methods
Background In proteomics, the most probable localizations of post-translational modifications are assessed by localization scores evaluating the likelihood of a given modification to occupy a site on a peptide sequence. When identifying highly modified peptides, localization scores for different modifications can return conflicting results, stacking modifications on the same amino acid. Here, we propose a graph-based approach that assigns modifications to sites in a way that maximizes localization scores while avoiding conflicting assignments. Results The algorithm is implemented as both a standalone Python program and in the compomics-utilities Java library. Our graph-based approach showed the ability to match complex combinations of modifications and acceptor sites, allowing the processing of thousands of peptides in a few seconds. Conclusions Our graph-based approach to modification site assignment allows distributing multiple modifications in a way that maximizes individual localization scores. Having an optimal modification site assignment is important for spectrum annotation and biological interpretation.
title A graph-based approach for modification site assignment in proteomics
topic Quantitative Methods
url https://arxiv.org/abs/2505.17755