Laboratory of Organic Chemistry, ETH Zurich, CH-8093 Zurich, Switzerland.
Curr Opin Biotechnol. 2010 Dec;21(6):753-9. doi: 10.1016/j.copbio.2010.08.008. Epub 2010 Sep 17.
Proteins evolve by iterative cycles of mutation, selection and amplification. Analogous evolutionary strategies are being profitably exploited in the laboratory to generate and optimize biocatalysts for diverse biotechnological applications. In this review, we summarize recent efforts to improve this process by creating more effective protein libraries and more efficient screening/selection schemes. Targeted mutagenesis using simplified amino acid alphabets, statistical analyses of sequence-function-stability relationships, and neutral mutational drift have emerged as powerful tools for generating useful molecular diversity, while new techniques for controlling selection stringency and microfluidic methods for screening large populations of molecules promise to facilitate exploration of sequence space. Enzyme engineers interested in creating novel biocatalysts for abiological reactions are sure to profit from these advances.
蛋白质通过突变、选择和扩增的迭代循环进化。类似的进化策略正在实验室中被有利地利用,以生成和优化用于各种生物技术应用的生物催化剂。在这篇综述中,我们总结了通过创建更有效的蛋白质文库和更有效的筛选/选择方案来改进这一过程的最新进展。使用简化的氨基酸字母表进行靶向诱变、序列-功能-稳定性关系的统计分析以及中性突变漂移已成为产生有用分子多样性的强大工具,而控制选择严格性的新技术和筛选大量分子的微流控方法有望促进序列空间的探索。对为非生物反应创造新型生物催化剂感兴趣的酶工程师肯定会从这些进展中受益。