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Protein engineering for natural product biosynthesis and synthetic biology applications

机译:用于天然产品生物合成和合成生物应用的蛋白质工程

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摘要

As protein engineering grows more salient, many strategies have emerged to alter protein structure and function, with the goal of redesigning and optimizing natural product biosynthesis. Computational tools, including machine learning and molecular dynamics simulations, have enabled the rational mutagenesis of key catalytic residues for enhanced or altered biocatalysis. Semirational, directed evolution and microenvironment engineering strategies have optimized catalysis for native substrates and increased enzyme promiscuity beyond the scope of traditional rational approaches. These advances are made possible using novel high-throughput screens, including designer protein-based biosensors with engineered ligand specificity. Herein, we detail the most recent of these advances, focusing on polyketides, non-ribosomal peptides and isoprenoids, including their native biosynthetic logic to provide clarity for future applications of these technologies for natural product synthetic biology.
机译:随着蛋白质工程越来越突出,许多改变蛋白质结构和功能的策略应运而生,其目标是重新设计和优化天然产物生物合成。计算机工具,包括机器学习和分子动力学模拟,已经能够对关键催化残基进行合理诱变,以增强或改变生物催化作用。半理性、定向进化和微环境工程策略优化了天然底物的催化作用,增加了酶的混杂性,超出了传统理性方法的范围。利用新型高通量筛选技术,包括具有工程配体特异性的基于蛋白质的生物传感器,这些进展成为可能。在此,我们详细介绍了这些进展中的最新进展,重点介绍了聚酮、非核糖体肽和类异戊二烯,包括它们的天然生物合成逻辑,以明确这些技术在天然产物合成生物学中的未来应用。

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