Directed Evolution for the Discovery of Engineered Proteins and Small Peptides Using Molecular Mutagenesis.

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Yi Torng Chai, Chee Mun Fang, Yin Sze Lim, Hwei-San Loh, Cheng Foh Le
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引用次数: 0

Abstract

Random mutagenesis is an essential technique in the directed evolution of proteins and peptides, driving advancements in protein engineering and biotechnology. This review provides a critical analysis of various error-prone polymerase chain reaction (epPCR) techniques employed for random mutagenesis, highlighting their mechanisms, advantages, and limitations. We compare conventional methods with emerging approaches, including combinative techniques and specialized protocols for small amplicons. We also discuss a few alternative approaches for cloning a mutant gene library, which could be simpler and more efficient than the traditional restriction digestion-ligation method, significantly improving the directed evolution workflows. Ultimately, the selection of a suitable method should align with the specific goals of the research, accepting inherent trade-offs. By combining different mutagenesis techniques with complementary mutational spectra, researchers can optimize their strategies for the discovery of novel proteins and peptides with specific biological activities and physicochemical properties of interest.

利用分子诱变发现工程蛋白和小肽的定向进化。
随机诱变是蛋白质和多肽定向进化的一项重要技术,推动了蛋白质工程和生物技术的进步。这篇综述提供了用于随机诱变的各种容易出错的聚合酶链反应(epPCR)技术的关键分析,强调了它们的机制,优点和局限性。我们比较了传统方法与新兴方法,包括组合技术和小扩增子的专门协议。我们还讨论了几种克隆突变基因文库的替代方法,这些方法比传统的限制性酶切-连接方法更简单、更有效,显著改善了定向进化的工作流程。最终,选择一种合适的方法应该与研究的具体目标保持一致,接受固有的权衡。通过将不同的诱变技术与互补的突变谱相结合,研究人员可以优化他们的策略,以发现具有特定生物活性和感兴趣的物理化学性质的新蛋白质和肽。
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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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