Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081715%3A_____%2F25%3A00583729" target="_blank" >RIV/68081715:_____/25:00583729 - isvavai.cz</a>
Result on the web
<a href="https://febs.onlinelibrary.wiley.com/doi/10.1111/febs.17108" target="_blank" >https://febs.onlinelibrary.wiley.com/doi/10.1111/febs.17108</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1111/febs.17108" target="_blank" >10.1111/febs.17108</a>
Alternative languages
Result language
angličtina
Original language name
Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches
Original language description
Over 400 different types of post-translational modifications (PTMs) have been reported and over 200 various types of PTMs have been discovered using mass spectrometry (MS)-based proteomics. MS-based proteomics has proven to be a powerful method capable of global PTM mapping with the identification of modified proteins/peptides, the localization of PTM sites and PTM quantitation. PTMs play regulatory roles in protein functions, activities and interactions in various heart related diseases, such as ischemia/reperfusion injury, cardiomyopathy and heart failure. The recognition of PTMs that are specific to cardiovascular pathology and the clarification of the mechanisms underlying these PTMs at molecular levels are crucial for discovery of novel biomarkers and application in a clinical setting. With sensitive MS instrumentationnand novel biostatistical methods for precise processing of the data, lowabundance PTMs can be successfully detected and the beneficial or unfavorable effects of specific PTMs on cardiac function can be determined. Moreover, computational proteomic strategies that can predict PTM sites based on MS data have gained an increasing interest and can contribute to characterization of PTM profiles in cardiovascular disorders. More recently, machine learning- and deep learning-based methods have been employed to predict the locations of PTMs and explore PTMcrosstalk. In this review article, the types of PTMs are briefly overviewed, approaches for PTM identification/quantitation in MS-based proteomics are discussed and recently published proteomic studies on PTMs associated with cardiovascular diseases are included.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10406 - Analytical chemistry
Result continuities
Project
<a href="/en/project/GA23-04703S" target="_blank" >GA23-04703S: Alternative route to capillary monolithic silica columns from discrete particles treated with supercritical water</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
FEBS Journal
ISSN
1742-464X
e-ISSN
1742-4658
Volume of the periodical
292
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
19
Pages from-to
28-46
UT code for WoS article
001178112600001
EID of the result in the Scopus database
2-s2.0-85186874554