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Protein turnover models for LC-MS data of heavy water metabolic labeling.
- Source :
-
Briefings in bioinformatics [Brief Bioinform] 2022 Mar 10; Vol. 23 (2). - Publication Year :
- 2022
-
Abstract
- Protein turnover is vital for cellular functioning and is often associated with the pathophysiology of a variety of diseases. Metabolic labeling with heavy water followed by liquid chromatography coupled to mass spectrometry is a powerful tool to study in vivo protein turnover in high throughput and large scale. Heavy water is a cost-effective and easy to use labeling agent. It labels all nonessential amino acids. Due to its toxicity in high concentrations (20% or higher), small enrichments (8% or smaller) of heavy water are used with most organisms. The low concentration results in incomplete labeling of peptides/proteins. Therefore, the data processing is more challenging and requires accurate quantification of labeled and unlabeled forms of a peptide from overlapping mass isotopomer distributions. The work describes the bioinformatics aspects of the analysis of heavy water labeled mass spectral data, available software tools and current challenges and opportunities.<br /> (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
Details
- Language :
- English
- ISSN :
- 1477-4054
- Volume :
- 23
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Briefings in bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 35062023
- Full Text :
- https://doi.org/10.1093/bib/bbab598