The chemical and physical properties of proteins are limited by the 20 canonical amino acids. Genetic code manipulation allows for the incorporation of noncanonical amino acids (ncAAs) that enhance or alter protein functionality. This review explores advances in the three main strategies for introducing ncAAs into biosynthesized proteins, focusing on the role of high throughput screening in these advancements. The first section discusses engineering aminoacyl-tRNA synthetases (aaRSs) and tRNAs, emphasizing how novel selection methods improve characteristics including ncAA incorporation efficiency and selectivity. The second section examines high-throughput techniques for improving protein translation machinery, enabling accommodation of alternative genetic codes. This includes opportunities to enhance ncAA incorporation through engineering cellular components unrelated to translation. The final section highlights various discovery platforms for high-throughput screening of ncAA-containing proteins, showcasing innovative binding ligands and enzymes that are challenging to create with only canonical amino acids. These advances have led to promising drug leads and biocatalysts. Overall, the ability to discover unexpected functionalities through high-throughput methods significantly influences ncAA incorporation and its applications. Future innovations in experimental techniques, along with advancements in computational protein design and machine learning, are poised to further elevate this field.

中文翻译：

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通过高通量筛选实现遗传密码操作的新高度


蛋白质的化学和物理性质受 20 个经典氨基酸的限制。遗传密码操作允许掺入增强或改变蛋白质功能的非经典氨基酸 （ncAA）。本文探讨了将 ncAAs 引入生物合成蛋白的三种主要策略的进展，重点介绍了高通量筛选在这些进展中的作用。第一部分讨论了工程氨酰基-tRNA 合成酶 （aaRS） 和 tRNA，强调了新的选择方法如何改善特性，包括 ncAA 掺入效率和选择性。第二部分研究了用于改进蛋白质翻译机制的高通量技术，从而能够容纳替代遗传密码。这包括通过工程化与翻译无关的细胞成分来增强 ncAA 掺入的机会。最后一部分重点介绍了用于高通量筛选含 ncAA 蛋白质的各种发现平台，展示了仅用经典氨基酸难以创建的创新结合配体和酶。这些进步导致了有前途的药物先导物和生物催化剂。总体而言，通过高通量方法发现意外功能的能力会显著影响 ncAA 掺入及其应用。实验技术的未来创新，以及计算蛋白质设计和机器学习的进步，有望进一步提升这一领域。