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首页> 外文期刊>Chembiochem: A European journal of chemical biology >Constructing and Analyzing the Fitness Landscape of an Experimental Evolutionary Process
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Constructing and Analyzing the Fitness Landscape of an Experimental Evolutionary Process

机译:实验进化过程的适应度景观构建与分析

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Iterative saturation mutagenesis (ISM) is a promising approach to more efficient directed evolution, especially for enhancing the enantioselectivity and/or thermostability of enzymes. This was demonstrated previously for on epoxide hydrolase (EH), after five sets of mutations led to a stepwise increase in enantioselectivity. This study utilizes these results to illuminate the nature of ISM, and identify the reasons for its operational efficacy. By applying a deconvolution strategy to the five sets of mutations and measuring the enantioselectivity factors (E) of the EH variants, Delta Delta G(double dagger) values become accessible. With these values, the construction of the complete fitness-pathway landscape is possible. The free energy profiles of the 5!= 120 evolutionary pathways leading from the wild-type to. the best mutant show that 55 trajectories are energetically favored, one of which is the originally observed route. This particular pathway was analyzed in terms of epistatic effects operating between the sets of mutations at all evolutionary stages. The degree of synergism increases as the stepwise evolutionary process proceeds. When encountering a local minimum in a disfavored pathway, that is, in the case of a dead end, choosing another set of mutations at a previous stage puts the evolutionary process back on an energetically favored trajectory. The type of analysis presented here might be useful when evaluating other mutagenesis methods and strategies in directed evolution.
机译:迭代饱和诱变(ISM)是一种有前途的方法,可用于更有效的定向进化,尤其是用于增强酶的对映选择性和/或热稳定性。在五组突变导致对映选择性逐步提高后,以前在环氧水解酶(EH)上已证明了这一点。这项研究利用这些结果阐明了ISM的性质,并确定了其运行功效的原因。通过将反卷积策略应用于五组突变并测量EH变体的对映选择性因子(E),可以访问Delta Delta G(双匕首)值。利用这些值,可以构建完整的健身路径景观。从野生型到的5!= 120个进化途径的自由能谱。最好的突变体显示,在能量上倾向于55条轨迹,其中之一是最初观察到的路线。根据在所有进化阶段的突变集之间起作用的上位性效应,分析了该特定途径。协同作用的程度随着逐步进化过程的进行而增加。当在不利的途径中遇到局部最小值时,即在死胡同的情况下,在前一阶段选择另一组突变会使进化过程回到能量有利的轨道上。在评估定向进化中的其他诱变方法和策略时,此处介绍的分析类型可能会很有用。

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