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Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches
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SYSNO ASEP 0583729 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches Author(s) Šťastná, Miroslava (UIACH-O) RID, ORCID Number of authors 1 Source Title FEBS Journal - ISSN 1742-464X
Roč. 291, č. 5 (2024), s. 1-19Number of pages 19 s. Publication form Online - E Language eng - English Country GB - United Kingdom Keywords cardiovascular disease ; MS-based proteomics ; post-translational modifications ; proteins Subject RIV CB - Analytical Chemistry, Separation OECD category Analytical chemistry R&D Projects GA23-04703S GA ČR - Czech Science Foundation (CSF) Method of publishing Open access Institutional support UIACH-O - RVO:68081715 UT WOS 001178112600001 EID SCOPUS 85186874554 DOI 10.1111/febs.17108 Annotation 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 instrumentation
and 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.Workplace Institute of Analytical Chemistry Contact Iveta Drobníková, drobnikova@iach.cz, Tel.: 532 290 234 Year of Publishing 2025 Electronic address https://febs.onlinelibrary.wiley.com/doi/10.1111/febs.17108
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