Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design
Efficient Exploration of Sequence Space by Sequence-Guided Protein Engineering and Design
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DOI：
10.1021/acs.biochem.1c00757
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发表时间：
2022-03-04
期刊：
影响因子：
2.9
通讯作者：
Laurino，Paola
中科院分区：
文献类型：
--
作者：
Clifton，Ben E.;Kozome，Dan;Laurino，Paola
在过去的二十年里，序列数据库的快速增长意味着蛋白质工程师面临着为任何给定的任务优化蛋白质的问题，他们往往可以立即获得大量相关的蛋白质序列。这些序列编码有关蛋白质进化历史的信息和产生折叠的、稳定的和功能蛋白质变体的潜在序列要求。能够利用这些信息的方法是蛋白质工程工具包中越来越重要的部分。在这个视角下，我们讨论了序列数据在蛋白质工程和设计中的应用，重点讨论了三个主要领域的最新进展：使用祖先序列重建作为工程工具来产生耐热和多功能的蛋白质，使用序列数据通过基于结构的计算蛋白质设计来指导多点突变的工程，以及使用未标记的序列数据进行无监督和半监督的机器学习，从而在序列空间的未探索区域中产生多样化和功能性的蛋白质序列。总之，这些方法能够快速探索富含功能蛋白质的区域内的序列空间，因此在加快工业和生物医学应用的稳定、功能和多样化的蛋白质工程方面具有巨大的潜力。
The rapid growth of sequence databases over the past two decades means that protein engineers faced with optimizing a protein for any given task will often have immediate access to a vast number of related protein sequences. These sequences encode information about the evolutionary history of the protein and the underlying sequence requirements to produce folded, stable, and functional protein variants. Methods that can take advantage of this information are an increasingly important part of the protein engineering tool kit. In this Perspective, we discuss the utility of sequence data in protein engineering and design, focusing on recent advances in three main areas: the use of ancestral sequence reconstruction as an engineering tool to generate thermostable and multifunctional proteins, the use of sequence data to guide engineering of multipoint mutants by structure-based computational protein design, and the use of unlabeled sequence data for unsupervised and semisupervised machine learning, allowing the generation of diverse and functional protein sequences in unexplored regions of sequence space. Altogether, these methods enable the rapid exploration of sequence space within regions enriched with functional proteins and therefore have great potential for accelerating the engineering of stable, functional, and diverse proteins for industrial and biomedical applications.