Maximizing Depth of PTM Coverage: Generating Robust MS Datasets for Computational Prediction Modeling

Exploring the landscape of post-translational modification in drug discovery

Post-translational modifications (PTMs) play a crucial role in regulating protein function, and their dysregulation is frequently associated with various diseases. The emergence of epigenetic drugs targeting factors such as histone deacetylases (HDACs) and histone methyltransferase enhancers of zeste homolog 2 (EZH2) has led to a significant shift towards precision medicine, offering new possibilities to overcome the limitations of traditional therapeutics. In this review, we aim to systematically explore how small molecules modulate PTMs. We discuss the direct targeting of enzymes involved in PTM pathways, the modulation of substrate proteins, and the disruption of protein-enzyme interactions that govern PTM processes. Additionally, we delve into the emerging strategy of employing multifunctional molecules to precisely regulate the modification levels of proteins of interest (POIs). Furthermore, we examine the specific characteristics of these molecules, evaluating their therapeutic benefits and potential drawbacks. The goal of this review is to provide a comprehensive understanding of PTM-targeting strategies and their potential for personalized medicine, offering a forward-looking perspective on the evolution of precision therapeutics.

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

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.