Assessment and prediction of human proteotypic peptide stability for proteomics quantification

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• dc.contributor.author Chiva, Cristina
• dc.contributor.author Elhamraoui, Zahra
• dc.contributor.author Solé, Amanda
• dc.contributor.author Serret, Marc
• dc.contributor.author Wilhelm, Mathias
• dc.contributor.author Sabidó Aguadé, Eduard, 1981-
• dc.date.accessioned 2025-05-05T06:12:35Z
• dc.date.available 2025-05-05T06:12:35Z
• dc.date.issued 2023
• dc.description.abstract Mass spectrometry coupled to liquid chromatography is one of the most powerful technologies for proteome quantification in biomedical samples. In peptide-centric workflows, protein mixtures are enzymatically digested to peptides prior their analysis. However, proteome-wide quantification studies rarely identify all potential peptides for any given protein, and targeted proteomics experiments focus on a set of peptides for the proteins of interest. Consequently, proteomics relies on the use of a limited subset of all possible peptides as proxies for protein quantitation. In this work, we evaluated the stability of the human proteotypic peptides during 21 days and trained a deep learning model to predict peptide stability directly from tryptic sequences, which together constitute a resource of broad interest to prioritize and select peptides in proteome quantification experiments.en
• dc.description.sponsorship We acknowledge support from the Spanish Ministry of Science, Innovation and Universities (PID2020-115092GB-I00), the German Federal Ministry of Education and Research (BMBF; Grant No. 031L0008A), “Centro de Excelencia Severo Ochoa 2013-2017”, SEV-2012-0208, and “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2021SGR01225). This project has also received support from Marie Skłodowska-Curie Actions – European Training Networks PROTrEIN: Computational Proteomics Training European Innovative Network (GA 956148). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech).en
• dc.format.mimetype application/pdf
• dc.identifier.citation Chiva C, Elhamraoui Z, Solé A, Serret M, Wilhelm M, Sabidó E. Assessment and prediction of human proteotypic peptide stability for proteomics quantification. Anal Chem. 2023 Sep 19;95(37):13746-9. DOI: 10.1021/acs.analchem.3c02269
• dc.identifier.doi http://dx.doi.org/10.1021/acs.analchem.3c02269
• dc.identifier.issn 0003-2700
• dc.identifier.uri http://hdl.handle.net/10230/70262
• dc.language.iso eng
• dc.publisher American Chemical Society (ACS)
• dc.relation.ispartof Analytical Chemistry. 2023 Sep 19;95(37):13746-9
• dc.relation.isreferencedby https://github.com/proteomicsunitcrg/peptide-stability
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/956148
• dc.rights This publication is licensed under CC-BY 4.0.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.other Proteòmicaca
• dc.subject.other Cromatografia de líquidsca
• dc.subject.other Aprenentatge profundca
• dc.title Assessment and prediction of human proteotypic peptide stability for proteomics quantificationen
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion