定向进化
蛋白质工程
合理设计
蛋白质设计
计算机科学
功能(生物学)
定向分子进化
组分(热力学)
领域(数学)
选择(遗传算法)
蛋白质功能
合成生物学
计算生物学
数据科学
生化工程
蛋白质结构
纳米技术
生物
工程类
人工智能
生物化学
遗传学
材料科学
物理
数学
基因
突变体
纯数学
酶
热力学
标识
DOI:10.1016/j.copbio.2010.08.011
摘要
Over the past two decades, directed evolution has transformed the field of protein engineering. The advances in understanding protein structure and function, in no insignificant part a result of directed evolution studies, are increasingly empowering scientists and engineers to device more effective methods for manipulating and tailoring biocatalysts. Abandoning large combinatorial libraries, the focus has shifted to small, functionally rich libraries and rational design. A critical component to the success of these emerging engineering strategies are computational tools for the evaluation of protein sequence datasets and the analysis of conformational variations of amino acids in proteins. Highlighting the opportunities and limitations of such approaches, this review focuses on recent engineering and design examples that require screening or selection of small libraries.
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