Xie Mingjie, Du Jiaxiang, Jia Miaohang, Nie Xiaoyu, Zhang Xuanling, Hu Yi, Nian Binbin
State Key Laboratory of Materials-Oriented Chemical Engineering, School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 210009, Jiangsu Province, People's Republic of China.
J Agric Food Chem. 2025 Aug 20;73(33):20600-20615. doi: 10.1021/acs.jafc.5c05979. Epub 2025 Aug 11.
Enzymes, recognized for their remarkable catalytic efficiency, play a crucial role in a myriad of biochemical reactions. However, the catalytic performance of natural enzymes frequently does not meet the demands of specific applications. To address this limitation, the integration of computer-aided technologies has emerged as a pivotal strategy in enzyme engineering, allowing for significant enhancements in enzyme properties. The binding pocket is one of the key factors for these enhancements, whose structural and conformational dynamics profoundly influence the enzyme's activity, selectivity, and stability. This review underscores the importance of employing advanced computer-aided techniques in the analysis and engineering of binding pockets, highlighting successful cases that demonstrate the modification of these pockets to achieve desired catalytic properties. By leveraging machine learning and artificial intelligence, it is now possible to design enzymes with customized binding pockets from the ground up. Furthermore, various software tools that facilitate the analysis of binding pocket, focusing on geometric dimensions, functional attributes, and dynamic conformations, which are essential for engineering of binding pockets are systematically reviewed. Finally, the challenges and future directions for the application of these technologies in the design of binding pockets are also discussed in-depth, emphasizing their transformative potential in biocatalysis.
酶因其卓越的催化效率而闻名,在众多生化反应中发挥着关键作用。然而,天然酶的催化性能常常无法满足特定应用的需求。为解决这一局限性,计算机辅助技术的整合已成为酶工程中的关键策略,可显著提升酶的性质。结合口袋是实现这些提升的关键因素之一,其结构和构象动力学深刻影响着酶的活性、选择性和稳定性。本综述强调了在结合口袋的分析和工程中运用先进计算机辅助技术的重要性,突出了通过修饰这些口袋以实现所需催化性质的成功案例。借助机器学习和人工智能,现在有可能从头设计具有定制结合口袋的酶。此外,还系统地综述了各种有助于结合口袋分析的软件工具,重点关注对结合口袋工程至关重要的几何尺寸、功能属性和动态构象。最后,还深入讨论了这些技术在结合口袋设计应用中的挑战和未来方向,强调了它们在生物催化中的变革潜力。