Raven Samuel A, Payne Blake, Bruce Mitchell, Filipovska Aleksandra, Rackham Oliver
Harry Perkins Institute of Medical Research, Nedlands, Western Australia, Australia.
University of Western Australia Centre for Medical Research, Nedlands, Western Australia, Australia.
Nat Chem Biol. 2022 Apr;18(4):403-411. doi: 10.1038/s41589-022-00967-y. Epub 2022 Feb 24.
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.
定向进化模拟自然选择过程，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，而且特别耗费时间和资源。为了绕过这些限制，我们构建了一个系统，在计算机上执行定向进化的整个过程。我们采用突变和评估的迭代计算循环，来预测那些能赋予无固有功能的初始从头设计蛋白质对DNA和RNA具有高亲和力结合活性的突变。有益突变揭示了天然蛋白质中以前未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，并且可以为突变率、种群大小和选择压力对自然界大分子功能化的贡献提供见解。
