蛋白质新功能定向进化研究策略

利用定向进化策略改造蛋白质功能已经在农业、工业和医药等领域得到了广泛的应用.蛋白质工程的最新进展是利用定向进化策略对自然界蛋白质引入新功能,但由于其决定因素比较复杂,是研究者面临的一个重大挑战.详细介绍了国外近年发展的蛋白质新功能定向进化研究策略:对传统突变体库构建策略进行改进以及非同源重组改造技术的开发,是早期引入蛋白质新功能的常用手段,利用计算/理性设计与定向进化相结合引入蛋白质新功能是近年定向进化研究的一个重大突破,而噬菌体展示技术是蛋白质新功能筛选的主要策略.蛋白质新功能的分子进化模型已逐渐成为蛋白质工程改造的新思路.     

高通量筛选工具的设计与应用

定向进化方法作为新兴的高效蛋白质工程手段,其内容包括蛋白质突变体文库的构建和有效突变体的快速筛选。高通量筛选方法是定向进化方法的重要组成部分,是成功获得有效突变体的关键。筛选的突变体数量越多,获得有效突变体的几率越大。以下介绍了目前已经成功应用于或有潜力应用于定向进化改造蛋白质的几种高通量筛选工具。高通量筛选工具的不断设计与开发将推动蛋白质工程领域的技术革新。     

蛋白质定向进化的研究进展

在工业生物催化过程和生物细胞工厂构建方面,蛋白质定向进化被广泛地应用于酶的分子改造.蛋白质定向进化不仅可以针对某一目的蛋白进行改造,还可以改善代谢途径、优化代谢网络、获得期望表型细胞.为了获得更高效的突变效率,快捷、高通量的筛选方法,提高蛋白质定向进化的效果,研究者不断开发蛋白质体内、体外进化方法,取得了新的进展和应用.本文介绍了最近发展的蛋白质定向进化技术的原理、方法及特点,总结了突变文库的筛选方法和蛋白质定向进化的最新应用,最后讨论了蛋白质定向进化存在的挑战和未来发展方向.     

微生物脂肪酶稳定性研究进展

脂肪酶广泛应用于食品、药物、生物燃料、诊断、生物修复、化学品、化妆品、清洁剂、饲料、皮革和生物传感器等工业领域,微生物脂肪酶是商品化脂肪酶的重要来源。高温、酸性、碱性和有机溶剂等恶劣的工业生产环境使得脂肪酶的进一步工业应用受到限制,获取稳定性好的脂肪酶成为打破这一限制的关键环节。本文重点对提高微生物脂肪酶稳定性的策略进行了综述:挖掘极端微生物脂肪酶资源;利用定向进化、理性设计和半理性设计等蛋白质工程策略改造脂肪酶;利用物理吸附、封装、共价结合和交联等酶的固定化技术提高脂肪酶的稳定性;利用物理/化学修饰、表面展示以及多种改良策略相结合提高脂肪酶的稳定性。结合作者前期对酶工程的研究发现,新型酶催化剂的获得应该基于明确的设计思路,结合多种改造方法,基于定向进化-理性设计、定向进化-半理性设计、蛋白质工程-酶的固定化、蛋白质工程-物理/化学修饰、酶的固定化-物理/化学修饰等组合改造,比单一的改造方法具有更高的效率。     

蛋白质定向进化及其在微生物代谢调控中的应用

蛋白质定向进化是非理性改造蛋白质的一种有效方法。利用蛋白质定向进化技术可以改变代谢流,扩展或构建新的代谢途径,弱化或消除不必要或有害的代谢途径,从而达到提高某种代谢产物产率或降解有害物质的目的。蛋白质定向进化技术在代谢调控中的应用有效拓宽了代谢工程的应用范围。本文介绍了主要的蛋白质定向进化技术如易错PCR技术、DNA改组技术、交错延伸技术和临时模板随机嵌合技术等,评述了蛋白质定向进化技术对微生物细胞代谢中的关键蛋白进行定向改造,从而改善其代谢能力,调控微生物代谢等的应用。     

几种定向进化技术的比较及文库构建策略

蛋白质定向进化在蛋白质工程中取得了令人瞩目的成就,其核心技术---随机突变库构建技术已成为近年来体外定向进化研究的热点。在概述定向进化基本原理基础上,对几种随机突变技术进行了介绍、分类和比较,并对突变库的特征及构建策略予以分析和描述 。     

蛋白质定向进化技术的研究进展

蛋白质定向进化技术是蛋白质分子改造的一个重要策略.重点介绍了易错PCR、DNA改组等对编码蛋白质的基因进行随机突变和重组的技术,以及构建突变体库和高通量筛选的方法,并探讨了定向进化技术在蛋白质工程中的应用及前景.     

ProSAR驱动的蛋白质定向进化技术

改进蛋白质序列空间检索策略是未来蛋白质工程研究的一个关键。本文介绍了一种被称为蛋白质序列-活性相关性(ProSAR)驱动的蛋白质定向进化策略的原理、机器学习算法及应用,为提高蛋白质定向进化效率和解决酶学性质的多维优化问题提供了办法和思路。     

蛋白质定向进化的研究技术及应用

蛋白质定向进化是在人类改造蛋白质的过程中产生的。蛋白质定向进化通常分三步进行,即随机诱变、体外重组和筛选。每一步都有多种研究技术。蛋白质定向进化大大加速了人类改造蛋白质的步伐,在实际应用研究和基础理论研究中都具有重要意义。     

蛋白质定向进化的研究进展及其应用前景

定向进化是改造蛋白质分子的有效新策略.它不需要了解蛋白质的空间结构,主要通过在实验室里模拟自然进化过程,采用错误倾向PCR等方法对编码蛋白质的基因进行随机突变,经DNA改组、交错延伸等技术进行体外重组,设计高通量筛选方法来选出需要的突变体.本综述了定向进化技术的发展及应用.     

Directed evolution of novel protein functions

Directed evolution has been successfully used to engineer proteins for basic and applied biological research. However, engineering of novel protein functions by directed evolution remains an overwhelming challenge. This challenge may come from the fact that multiple simultaneously or synergistic mutations are required for the creation of a novel protein function. Here we review the key developments in engineering of novel protein functions by using either directed evolution or a combined directed evolution and rational or computational design approach. Specific attention will be paid to a molecular evolution model for generation of novel proteins. The engineered novel proteins should not only broaden the range of applications of proteins but also provide new insights into protein structure-function relationship and protein evolution.     

Rapid creation of a novel protein function by in vitro coevolution

We have developed a simple and efficient method for creation of novel protein functions in an existing protein scaffold. The in vitro coevolution method involves design of a hypothetical pathway for the target function followed by stepwise directed evolution of the corresponding protein along the pathway. As a test case, this strategy was used to engineer variants of human estrogen receptor alpha ligand-binding domain (hERalphaLBD) with novel corticosterone activity. Two steroids, testosterone and progesterone, that provide a progressive structural bridge between 17beta-estradiol and corticosterone, were chosen to assist the directed evolution of hERalphaLBD. A total of approximately 10(6) variants were screened in four rounds of random mutagenesis, resulting in two hERalphaLBD variants that respond to corticosterone. Creation of this new ligand activity required the presence of four simultaneous mutations. In addition, several required mutations were located outside the ligand binding pocket and yet exerted important action on ligand binding. Our results demonstrate the ability of in vitro coevolution to create novel protein function that is difficult or impossible to achieve by existing protein engineering approaches and also shed light on the natural evolution of nuclear hormone receptors. This in vitro coevolution approach should provide a powerful, broadly applicable tool for engineering biological molecules and systems with novel functions.     

Biocatalysts: application and engineering for industrial purposes

Enzymes are widely applied in various industrial applications and processes, including the food and beverage, animal feed, textile, detergent and medical industries. Enzymes screened from natural origins are often engineered before entering the market place because their native forms do not meet the requirements for industrial application. Protein engineering is concerned with the design and construction of novel enzymes with tailored functional properties, including stability, catalytic activity, reaction product inhibition and substrate specificity. Two broad approaches have been used for enzyme engineering, namely, rational design and directed evolution. The powerful and revolutionary techniques so far developed for protein engineering provide excellent opportunities for the design of industrial enzymes with specific properties and production of high-value products at lower production costs. The present review seeks to highlight the major fields of enzyme application and to provide an updated overview on previous protein engineering studies wherein natural enzymes were modified to meet the operational conditions required for industrial application.     

High-throughput screening of enzyme libraries

Directed evolution is becoming a widely used technique for modifying or enhancing protein performance. Ultimately, the success of directed protein evolution experiments hinges on the efficiency of the methods used to screen libraries for mutants with properties of interest. Although there is still a paucity of general methods for enzyme library screening, in recent years a number of promising strategies have emerged and are increasingly being used to explore challenging issues in protein engineering.     

Directed evolution strategies for improved enzymatic performance

The engineering of enzymes with altered activity, specificity and stability, using directed evolution techniques that mimic evolution on a laboratory timescale, is now well established. However, the general acceptance of these methods as a route to new biocatalysts for organic synthesis requires further improvement of the methods for both ease-of-use and also for obtaining more significant changes in enzyme properties than is currently possible. Recent advances in library design, and methods of random mutagenesis, combined with new screening and selection tools, continue to push forward the potential of directed evolution. For example, protein engineers are now beginning to apply the vast body of knowledge and understanding of protein structure and function, to the design of focussed directed evolution libraries, with striking results compared to the previously favoured random mutagenesis and recombination of entire genes. Significant progress in computational design techniques which mimic the experimental process of library screening is also now enabling searches of much greater regions of sequence-space for those catalytic reactions that are broadly understood and, therefore, possible to model.     

De novo design of biocatalysts

The challenging field of de novo enzyme design is beginning to produce exciting results. The application of powerful computational methods to functional protein design has recently succeeded at engineering target activities. In addition, efforts in directed evolution continue to expand the transformations that can be accomplished by existing enzymes. The engineering of completely novel catalytic activity requires traversing inactive sequence space in a fitness landscape, a feat that is better suited to computational design. Optimizing activity, which can include subtle alterations in backbone conformation and protein motion, is better suited to directed evolution, which is highly effective at scaling fitness landscapes towards maxima. Improved rational design efforts coupled with directed evolution should dramatically improve the scope of de novo enzyme design.     

蛋白质工程：从定向进化到计算设计

定向进化通过建立突变体文库与高通量筛选方法,快速提升蛋白的特定性质,是目前蛋白质工程最为常用的蛋白质设计改造策略。近十年随着计算机运算能力大幅提升以及先进算法不断涌现,计算机辅助蛋白质设计改造得到了极大的重视和发展,成为蛋白质工程新开辟的重要方向。以结构模拟与能量计算为基础的蛋白质计算设计不但能改造酶的底物特异性与热稳定性,还可从头设计具有特定功能的人工酶。近年来机器学习等人工智能技术也被应用于计算机辅助蛋白质设计改造,并取得瞩目的成绩。文中介绍了蛋白质工程的发展历程,重点评述当前计算机辅助蛋白质设计改造方面的进展与应用,并展望其未来发展方向。     

Engineering proteins for thermostability: the use of sequence alignments versus rational design and directed evolution

With the advent of directed evolution techniques, protein engineering has received a fresh impetus. Engineering proteins for thermostability is a particularly exciting and challenging field, as it is crucial for broadening the industrial use of recombinant proteins. In addition to directed evolution, a variety of partially successful rational concepts for engineering thermostability have been developed in the past. Recent results suggest that amino acid sequence comparisons of mesophilic proteins alone can be used efficiently to engineer thermostable proteins. The potential benefits of the underlying, semirational 'consensus concept' are compared with those of rational design and directed evolution approaches.     

Milestones in directed enzyme evolution

Directed evolution has now been used for over two decades as an alternative to rational design for protein engineering. Protein function, however, is complex, and modifying enzyme activity is a tall order. We can now improve existing enzyme activity, change enzyme selectivity and evolve function de novo using directed evolution. Although directed evolution is now used routinely to improve existing enzyme activity, there are still only a handful of examples where substrate selectivity has been modified sufficiently for practical application, and the de novo evolution of function largely eludes us.