Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches.

The FEBS journal Pub Date : 2025-01-01 Epub Date: 2024-03-05 DOI:10.1111/febs.17108
Miroslava Stastna
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Abstract

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, low-abundance 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 PTM crosstalk. 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.

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通过蛋白质组学方法研究心血管疾病中蛋白质的翻译后修饰。
已有 400 多种不同类型的翻译后修饰(PTM)被报道,利用基于质谱(MS)的蛋白质组学发现了 200 多种不同类型的 PTM。基于质谱的蛋白质组学已被证明是一种功能强大的方法,能够绘制全球 PTM 图谱,鉴定修饰的蛋白质/肽,定位 PTM 位点和定量 PTM。在缺血/再灌注损伤、心肌病和心力衰竭等各种心脏相关疾病中,PTM 在蛋白质功能、活性和相互作用中发挥着调控作用。识别心血管病变中的特异性 PTM,并阐明这些 PTM 在分子水平上的作用机制,对于发现新型生物标记物和应用于临床至关重要。利用灵敏的 MS 仪器和新型生物统计方法对数据进行精确处理,可以成功检测到低丰度 PTM,并确定特定 PTM 对心脏功能的有利或不利影响。此外,能根据 MS 数据预测 PTM 位点的计算蛋白质组学策略也受到越来越多的关注,并有助于描述心血管疾病的 PTM 特征。最近,基于机器学习和深度学习的方法已被用于预测 PTM 的位置和探索 PTM 的串扰。在这篇综述文章中,简要概述了 PTM 的类型,讨论了基于 MS 的蛋白质组学中 PTM 鉴定/定量的方法,并纳入了最近发表的与心血管疾病相关的 PTM 蛋白质组学研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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