Assessment and Prediction of Human Proteotypic Peptide Stability for Proteomics Quantification

Cristina Chiva, Zahra Elhamraoui, Amanda Solé, Marc Serret, Mathias Wilhelm, Eduard Sabidó

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish
Pages (from-to)13746-13749
Number of pages4
JournalAnalytical Chemistry
Volume95
Issue number37
DOIs
StatePublished - 19 Sep 2023

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