Better library design: data-driven protein engineering
Better library design: data-driven protein engineering
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DOI：
10.1002/biot.200600170
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发表时间：
2007-02-01
影响因子：
4.7
通讯作者：
Bommarius, Andreas S.
中科院分区：
文献类型：
--
作者：
Chaparro-Riggers, Javier F.;Polizzi, Karen M.;Bommarius, Andreas S.
数据驱动的蛋白质工程越来越多地被用作理性设计和组合工程的替代方案，因为它使用可用的知识来限制文库的大小，同时仍然允许识别导致巨大影响的不可预测的替代。计算建模和生物信息学的最新进展，以及功能变异实验数据库的不断增加，导致了选择特定氨基酸残基变化的新策略，以增加获得具有所需特性的变异蛋白的机会。在每个位置限制多样性的策略、小子库的设计和侦察实验的性能也被开发甚至自动化，进一步减少了库的规模。
Data-driven protein engineering is increasingly used as an alternative to rational design and combinatorial engineering because it uses available knowledge to limit library size, while still allowing for the identification of unpredictable substitutions that lead to large effects. Recent advances in computational modeling and bioinformatics, as well as an increasing databank of experiments on functional variants, have led to new strategies to choose particular amino acid residues to vary in order to increase the chances of obtaining a variant protein with the desired property. Strategies for limiting diversity at each position, design of small sub-libraries, and the performance of scouting experiments, have also been developed or even automated, further reducing the library size.