Ridgeway Nashira H, Biggar Kyle K
Institute of Biochemistry, Carleton University, Ottawa, ON K1S5B6, Canada.
Proteomes. 2025 Aug 11;13(3):37. doi: 10.3390/proteomes13030037.
Post-translational modifications (PTMs) govern a multitude of protein functions within the cell, surpassing the basic function(s) encoded directly within the amino acid sequence. Despite the historical discovery of PTMs dating back over a century, recent technological advancements have facilitated the rapid expansion of the known PTM landscape. However, the elucidation of enzyme-substrate relationships responsible for PTMs, particularly for those less studied, remains a challenging endeavor. This review provides an extensive overview of methods employed in the discovery of enzyme-specific substrates for PTM catalysis. Beginning with traditional experimental approaches rooted in chemistry, biochemistry and cell biology, this review progresses to recently developed computational strategies tailored for identifying enzyme-substrate interactions. The analysis reflects on the remarkable progress achieved in PTM research to date, underscoring the increasing role of computational and high-throughput techniques in expediting enzyme-substrate discovery. Furthermore, it highlights the potential of artificial intelligence to revolutionize PTM research and emphasizes the importance of unbiased high-throughput analysis in advancing our understanding of PTM networks. Ultimately, the review advocates for the integration of sophisticated computational strategies with experimental techniques to unravel the complex enzyme-substrate networks governing PTM-mediated cellular processes.
翻译后修饰(PTMs)在细胞内调控着众多蛋白质功能,其作用超越了由氨基酸序列直接编码的基本功能。尽管PTMs的发现可追溯到一个多世纪以前,但近期的技术进步推动了已知PTM格局的迅速扩展。然而,阐明负责PTMs的酶-底物关系,尤其是对于那些研究较少的关系,仍然是一项具有挑战性的工作。本综述广泛概述了用于发现PTM催化的酶特异性底物的方法。从源于化学、生物化学和细胞生物学的传统实验方法开始,本综述进而介绍了为识别酶-底物相互作用而开发的最新计算策略。分析反映了迄今为止PTM研究取得的显著进展,强调了计算和高通量技术在加速酶-底物发现方面日益重要的作用。此外,它突出了人工智能在变革PTM研究方面的潜力,并强调了无偏高通量分析在推进我们对PTM网络理解方面的重要性。最终,本综述主张将复杂的计算策略与实验技术相结合,以揭示控制PTM介导的细胞过程的复杂酶-底物网络。