Improving catalytic function by ProSAR-driven enzyme evolution
Improving catalytic function by ProSAR-driven enzyme evolution
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DOI：
10.1038/nbt1286
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发表时间：
2007-03-01
影响因子：
46.9
通讯作者：
Huisman, Gjalt W.
中科院分区：
文献类型：
--
作者：
Fox, Richard J.;Davis, S. Christopher;Huisman, Gjalt W.
我们描述了一种定向进化方法，该方法应该在产生符合预定义过程设计标准的酶方面找到广泛的应用。它通过结合蛋白质序列活性关系（ProSAR）的统计分析策略，增强了基于重组的定向进化。通过允许捕获序列活性数据中包含的附加信息，这种组合促进了面向突变的酶优化。因此，该方法甚至可以在功能降低的变体中识别有益的突变。我们使用这种杂交方法来进化一种细菌卤代醇脱卤酶，该酶将氰化过程的体积生产率提高了4000倍。这种改进需要满足与商业相关的生物催化工艺合成降胆固醇药物阿托伐他汀（立普妥）的实际设计标准，并且通过至少有35个突变的变体获得。
We describe a directed evolution approach that should find broad application in generating enzymes that meet predefined process-design criteria. It augments recombination-based directed evolution by incorporating a strategy for statistical analysis of protein sequence activity relationships (ProSAR). This combination facilitates mutation-oriented enzyme optimization by permitting the capture of additional information contained in the sequence-activity data. The method thus enables identification of beneficial mutations even in variants with reduced function. We use this hybrid approach to evolve a bacterial halohydrin dehalogenase that improves the volumetric productivity of a cyanation process B4,000-fold. This improvement was required to meet the practical design criteria for a commercially relevant biocatalytic process involved in the synthesis of a cholesterol-lowering drug, atorvastatin (Lipitor), and was obtained by variants that had at least 35 mutations.