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过氧化氢酶I特性突变效应的非加和性及其在高效定向进化中的应用

Nonadditivity of mutational effects on the properties of catalase I and its application to efficient directed evolution.

作者信息

Matsuura T, Yomo T, Trakulnaleamsai S, Ohashi Y, Yamamoto K, Urabe I

机构信息

Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Japan.

出版信息

Protein Eng. 1998 Sep;11(9):789-95. doi: 10.1093/protein/11.9.789.

DOI:10.1093/protein/11.9.789
PMID:9796828
Abstract

Catalase I of Bacillus stearothermophilus has high catalatic and low peroxidatic activities. The mutant from the first random mutant population, D130N, which has higher peroxidatic and lower catalatic activities than those exhibited by the wild-type enzyme, was subjected to second random mutagenesis in observance of the change in reaction specificity. From the second mutant population, the mutant I108T/D130N/I222T was selected and examined. The reaction specificity of the purified enzymes revealed that catalase I being originally 98% catalase and 2% peroxidase was brought to 58% specificity to peroxidase after two-step adaptive walks. From the statistical analysis of the two random mutant populations, the average degree of nonadditivity of the mutational effects was estimated to be 0.13 irrespective of the properties of the enzyme. It was demonstrated that the distribution pattern of a property of the second mutant population can be predicted well from the data of the first mutant population by taking into consideration the degree of nonadditivity. The strategy for an efficient adaptive walk in directed evolution of enzymes through the prediction of appropriate mutation rate and effective sample size for further mutation and selection was presented and discussed.

摘要

嗜热脂肪芽孢杆菌的过氧化氢酶I具有高催化活性和低过氧化物酶活性。来自第一个随机突变群体的突变体D130N,其过氧化物酶活性高于野生型酶,而催化活性低于野生型酶,为了观察反应特异性的变化,对其进行了第二轮随机诱变。从第二个突变群体中,选择并检测了突变体I108T/D130N/I222T。纯化酶的反应特异性表明,最初98%为过氧化氢酶活性、2%为过氧化物酶活性的过氧化氢酶I,经过两步适应性进化后,过氧化物酶的特异性达到了58%。通过对两个随机突变群体的统计分析,无论酶的性质如何,突变效应的平均非加和程度估计为0.13。结果表明,考虑到非加和程度,通过第一个突变群体的数据可以很好地预测第二个突变群体性质的分布模式。本文提出并讨论了一种在酶的定向进化中通过预测适当的突变率和有效样本量进行进一步突变和选择的高效适应性进化策略。

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