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Computationally Mapping Sequence Space To Understand Evolutionary Protein Engineering

机译：计算映射序列空间以了解进化蛋白质工程

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Evolutionary protein engineering has been dramatically successful,producing a wide variety of new proteins with altered stability,binding affinity,and enzymatic activity.However,the success of such procedures is often unreliable,and the impact of the choice of protein,engineering goal,and evolutionary procedure is not well understood.We have created a framework for understanding aspects of the protein engineering process by computationally mapping regions of feasible sequence space for three small proteins using structure-based design protocols.We then tested the ability of different evolutionary search strategies to explore these sequence spaces.The results point to a non-intuitive relationship between the error-prone PCR mutation rate and the number of rounds of replication.The evolutionary relationships among feasible sequences reveal hub-like sequences that serve as particularly fruitful starting sequences for evolutionary search.Moreover,genetic recombination procedures were examined,and tradeoffs relating sequence diversity and search efficiency were identified.This framework allows us to consider the impact of protein structure on the allowed sequence space and therefore on the challenges that each protein presents to error-prone PCR and genetic recombination procedures.
机译：进化蛋白工程取得了巨大的成功，产生了各种具有改变的稳定性，结合亲和力和酶活性的新蛋白。但是，这种方法的成功通常不可靠，并且影响蛋白选择，工程目标和目的。进化过程尚未得到很好的理解。我们已经建立了一个框架，通过使用基于结构的设计方案通过计算三个小蛋白质的可行序列空间区域来了解蛋白质工程过程的各个方面。然后，我们测试了不同进化搜索策略对探索这些序列空间。结果表明，容易出错的PCR突变率与复制轮数之间存在非直觉的关系。可行序列之间的进化关系揭示了类似轮毂的序列，这些序列对于进化特别有用。搜索。此外，对基因重组程序进行了审查。在此基础上，我们可以考虑蛋白质结构对允许的序列空间的影响，因此可以考虑每种蛋白质对易错PCR和遗传重组程序的挑战。

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