Assessment and prediction of human proteotypic peptide stability for proteomics quantification
Assessment and prediction of human proteotypic peptide stability for proteomics quantification
Citació
- 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
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Resum
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.