Deep sequencing methods for protein engineering and design.
Deep sequencing methods for protein engineering and design.
复制标题
用于蛋白质工程和设计的深度测序方法。
DOI：
10.1016/j.sbi.2016.11.001
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发表时间：
2017
影响因子：
6.8
通讯作者：
Whitehead,TimothyA
中科院分区：
文献类型：
--
作者：
Wrenbeck,EmilyE;Faber,MatthewS;Whitehead,TimothyA
重点深度测序允许检查局部蛋白质适应性景观。NGS有助于蛋白质分子识别的工程亲和力和特异性。酶的应用受到缺乏功能选择的限制。NGS使酶行为和进化的基础研究成为可能。基因拼接和分子条形码将NGS扩展到全长蛋白质。下一代测序（NGS）的出现彻底改变了蛋白质科学，以及能够实现NGS驱动的蛋白质工程的互补方法的开发也随之而来。一般而言，这些实验以大规模平行的方式使用基因型-表型关联的高通量功能筛选，然后通过深度测序进行DNA计数来解决数千种蛋白质变体的功能后果。我们强调使用信息丰富的数据集工程蛋白质分子识别。实例包括靶向结构上不同的表位的多个双亲和力Fab的产生和宽种系靶向抗HIV-1免疫原的工程化。此外，我们强调酶的健身景观进行蛋白质行为和进化的基础研究的生成。最后，我们将讨论技术进步。
HighlightsDeep sequencing permits examination of local protein fitness landscapes.NGS aids in engineering affinity and specificity for protein molecular recognition.Application to enzymes is limited by paucity of functional selections.NGS enables fundamental studies of enzyme behavior and evolution.Gene tiling and molecular barcoding extend NGS to full-length proteins.The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances.