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In silico evolution of nucleic acid-binding proteins from a nonfunctional scaffold

机译:核酸结合蛋白从无功能支架的计算机进化

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摘要

Directed evolution emulates the process of natural selection to produce proteins with improved or altered functions. These approaches have proven to be very powerful but are technically challenging and particularly time and resource intensive. To bypass these limitations, we constructed a system to perform the entire process of directed evolution in silico. We employed iterative computational cycles of mutation and evaluation to predict mutations that confer high-affinity binding activities for DNA and RNA to an initial de novo designed protein with no inherent function. Beneficial mutations revealed modes of nucleic acid recognition not previously observed in natural proteins, highlighting the ability of computational directed evolution to access new molecular functions. Furthermore, the process by which new functions were obtained closely resembles natural evolution and can provide insights into the contributions of mutation rate, population size and selective pressure on functionalization of macromolecules in nature.
机译:定向进化模拟自然选择的过程,以产生具有改进或改变功能的蛋白质。这些方法已被证明非常强大,但在技术上具有挑战性,尤其是时间和资源密集型。为了绕过这些限制,我们构建了一个系统来执行计算机定向进化的整个过程。我们采用突变和评估的迭代计算周期来预测将 DNA 和 RNA 的高亲和力结合活性赋予初始从头设计的蛋白质的突变,该蛋白质没有固有功能。有益的突变揭示了以前在天然蛋白质中没有观察到的核酸识别模式,突出了计算定向进化获得新分子功能的能力。此外,获得新功能的过程与自然进化非常相似,可以深入了解突变率、种群规模和选择压力对自然界中大分子功能化的贡献。

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