利用高通量筛选技术实现遗传密码操作的新高度

IF 51.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Chemical Reviews Pub Date : 2024-10-17 DOI:10.1021/acs.chemrev.4c00329
Briana R. Lino, Sean J. Williams, Michelle E. Castor, James A. Van Deventer
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引用次数: 0

摘要

蛋白质的化学和物理特性受到 20 个标准氨基酸的限制。通过操纵遗传密码,可以加入非典型氨基酸(ncAAs),从而增强或改变蛋白质的功能。本综述探讨了将 ncAAs 引入生物合成蛋白质的三种主要策略的进展,重点关注高通量筛选在这些进展中的作用。第一部分讨论了氨基酰-tRNA 合成酶(amaRSs)和 tRNAs 的工程化,强调了新型选择方法如何提高 ncAA 结合效率和选择性等特性。第二部分探讨了改进蛋白质翻译机制的高通量技术,以适应替代遗传密码。这包括通过设计与翻译无关的细胞元件来提高 ncAA 结合率的机会。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,展示了创新的结合配体和酶,这些配体和酶只用典型的氨基酸就很难创造出来。这些进展带来了前景广阔的药物线索和生物催化剂。总之,通过高通量方法发现意想不到的功能的能力极大地影响了 ncAA 的加入及其应用。未来实验技术的创新以及计算蛋白质设计和机器学习的进步将进一步提升这一领域的水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Reaching New Heights in Genetic Code Manipulation with High Throughput Screening
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.
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来源期刊
Chemical Reviews
Chemical Reviews 化学-化学综合
CiteScore
106.00
自引率
1.10%
发文量
278
审稿时长
4.3 months
期刊介绍: Chemical Reviews is a highly regarded and highest-ranked journal covering the general topic of chemistry. Its mission is to provide comprehensive, authoritative, critical, and readable reviews of important recent research in organic, inorganic, physical, analytical, theoretical, and biological chemistry. Since 1985, Chemical Reviews has also published periodic thematic issues that focus on a single theme or direction of emerging research.
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