Borkakoti Neera, Ribeiro António J M, Thornton Janet M
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1SD, UK.
LAQV-REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências da, Universidade do Porto, 4169-007, Porto, Portugal.
Curr Opin Struct Biol. 2025 Jun;92:103040. doi: 10.1016/j.sbi.2025.103040. Epub 2025 Mar 29.
In this perspective, we analyse the progress made in our knowledge of enzyme sequences, structures and functions in the last 2 years. We review how much new enzyme data have been garnered and annotated, derived from the study of proteins using structural and computational approaches. Recent advances towards capturing 'Catalysis in silico' are described, including knowledge and predictions of enzyme structures, their interactions and mechanisms. We highlight the flood of enzyme data, driven by metagenomic sequencing, the improved enzyme data resources, the high coverage in Protein Data Bank of E.C. classes and the AI-driven structure prediction techniques that facilitate the accurate prediction of protein structures. We note the focus on disordered regions in the context of enzyme regulation and specificity and comment on emerging bioinformatic approaches that capture reaction mechanisms computationally for comparing and predicting enzyme mechanisms. We also consider the drivers of progress in this field in the next five years.
从这一角度出发,我们分析了过去两年中我们在酶序列、结构和功能知识方面取得的进展。我们回顾了通过使用结构和计算方法研究蛋白质所获得和注释的新酶数据的数量。描述了在实现“计算机模拟催化”方面的最新进展,包括酶结构、它们的相互作用和机制的知识及预测。我们强调了宏基因组测序推动的酶数据洪流、改进的酶数据资源、蛋白质数据库中酶委员会(EC)分类的高覆盖率以及有助于准确预测蛋白质结构的人工智能驱动的结构预测技术。我们注意到在酶调节和特异性背景下对无序区域的关注,并对通过计算捕获反应机制以比较和预测酶机制的新兴生物信息学方法进行了评论。我们还考虑了该领域未来五年的发展驱动力。