A hybrid strategy for massive acceleration of directed evolution: meeting the need for high-turnover enzymes in industrial biotechnology.

大规模加速定向进化的混合策略:满足工业生物技术中对高周转酶的需求。

基本信息

  • 批准号:
    BB/R014426/1
  • 负责人:
  • 金额:
    $ 95.46万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2018
  • 资助国家:
    英国
  • 起止时间:
    2018 至 无数据
  • 项目状态:
    已结题

项目摘要

Enzymes are tiny machines that speed up chemical processes in living organisms; life would not exist without enzymes, because essential chemical reactions would not happen fast enough. Enzymes perform this miraculous function by first attaching to chemicals, changing their shapes temporarily and using this to elicit a chemical reaction, and then releasing the products. Some enzymes break down large chemicals into simpler parts, while some build smaller chemicals into more complex ones. All this happens at atmospheric pressure, room temperature, neutral acidity and all components are biodegradable! In contrast, current industrial chemistry needs high temperatures and pressures, and creates organic waste and pollutants. Consequently, industrial reactions are typically not very efficient and often lead to the formation of unwanted side products. With enzymes there is relatively little energy demand and side products can be eradicated. Enzymes, therefore, represent a huge opportunity in the 21st Century to revolutionise industrial chemical reactions and make them more cost-effective and environmentally friendly.Unfortunately, there is a catch: naturally occurring enzymes, perhaps unsurprisingly, are not suited to industrial processes. For example, an enzyme may not be naturally available for the chemical reaction at hand, they may be unstable in an industrial setting, or they may be too slow to be cost-effective (metabolic reactions don't demand such speed). Biology does, however, provide a potential solution to these shortcomings. Each enzyme is constructed as a string of 100s of smaller building blocks called amino acids. Furthermore, one enzyme can be converted to another by altering (or mutating) its amino acids. There are 20 possible amino acids and within a string of 100 there are vastly more combinations than stars in the universe and it is very clear that the natural world only uses the tiniest fraction of the possible gamut. The real opportunity is to mutate natural enzymes to make them more stable, faster and tailor their specificity so that they can be used in industry and make chemical processes much more cost-effective and environmentally friendly, which is at the heart of this research proposal.The active site of an enzyme is a space that only the right chemicals can slot into easily and perfectly, like a key in its lock, and it is the shape of this space and motions within that determine an enzyme's speed and specificity; mutations alter speed and specificity by affecting the active site. Scientists thought, naively, that randomly mutating a few amino acids around the active site would be sufficient to achieve their goals. In such a case there would be, say, only a million combinations to produce and test to identify a suitable one. However, it has now been found that mutations anywhere in an enzyme's string of amino acids may affect the active site and based on random mutations the number of combinations are truly astronomical. Some progress has been made in a process called directed evolution, where random mutations are made in an iterative cycle, but not nearly enough to satisfy industry since for some enzymes the process is predicted to take millennia.Our vision is to fundamentally change the way that directed evolution is performed, and reduce the timescales, not incrementally, but by potentially millions of times to facilitate rapid production of enzymes with industrially-relevant properties. We plan to use an enzyme, monoamine oxidase, which could be used in the manufacture of almost half of current developmental drugs, to show the validity of our new approach. The idea is to use very fast, but accurate, computer simulations of enzymes, leveraging hardware developed for rendering computer games, to understand how mutations throughout an enzyme affect the active site and use this to predict the optimal mutations for directed evolution, allowing the process to occur in weeks rather than millennia.
酶是加速生物体内化学过程的微小机器;没有酶,生命就不会存在,因为基本的化学反应不会发生得足够快。酶发挥这种神奇的功能,首先是附着在化学物质上,暂时改变它们的形状,利用它来引发化学反应,然后释放产物。有些酶能将大的化学物质分解成更简单的部分,而有些酶则能将小的化学物质分解成更复杂的部分。所有这些都发生在常压、室温、中性酸度下,所有成分都是可生物降解的!相比之下,目前的工业化学需要高温和高压,并产生有机废物和污染物。因此,工业反应通常不是很有效,并且经常导致不需要的副产物的形成。有了酶,能量需求相对较少,副作用也可以消除。因此,在21世纪,酶代表了一个巨大的机会,可以彻底改变工业化学反应,使其更具成本效益和环保。不幸的是,这里有一个陷阱:自然产生的酶不适合工业过程,这也许不足为奇。例如,一种酶可能不能自然地用于手头的化学反应,它们可能在工业环境中不稳定,或者它们可能太慢而不具有成本效益(代谢反应不需要这样的速度)。然而,生物学确实为这些缺点提供了一个潜在的解决方案。每一种酶都是由100个更小的氨基酸组成的。此外,一种酶可以通过改变(或突变)其氨基酸转化为另一种酶。有20种可能的氨基酸,在100种氨基酸中,有比宇宙中恒星多得多的组合,很明显,自然界只使用了可能色域中最小的一部分。真正的机会是改变天然酶,使它们更稳定、更快,并定制它们的特异性,以便它们可以在工业中使用,使化学过程更具成本效益和环保,这是本研究计划的核心。酶的活性位点是一个空间,只有合适的化学物质才能轻松而完美地进入,就像锁上的钥匙一样,正是这个空间的形状和运动决定了酶的速度和特异性;突变通过影响活性部位来改变速度和特异性。科学家们天真地认为,随机改变活性位点周围的一些氨基酸就足以实现他们的目标。在这种情况下,只有一百万个组合需要生产和测试以确定一个合适的组合。然而,现在已经发现,酶的氨基酸链中的任何地方的突变都可能影响活性位点,基于随机突变的组合数量确实是天文数字。在一个被称为定向进化的过程中已经取得了一些进展,在这个过程中,随机突变在一个迭代的循环中产生,但还远远不足以满足工业,因为对一些酶来说,这个过程预计需要几千年的时间。我们的愿景是从根本上改变定向进化的执行方式,并减少时间尺度,不是增量,而是潜在的数百万倍,以促进具有工业相关特性的酶的快速生产。我们计划使用一种酶,单胺氧化酶,它可以用于制造几乎一半的目前正在开发的药物,以证明我们的新方法的有效性。这个想法是使用非常快速而准确的酶的计算机模拟,利用为渲染电脑游戏而开发的硬件,来了解酶的突变是如何影响活性位点的,并用它来预测定向进化的最佳突变,使这个过程在几周内发生,而不是几千年。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Deconvolution of conformational exchange from Raman spectra of aqueous RNA nucleosides.
  • DOI:
    10.1038/s42004-020-0298-x
  • 发表时间:
    2020-05-06
  • 期刊:
  • 影响因子:
    5.9
  • 作者:
    Wilson, Alex L.;Outeiral, Carlos;Dowd, Sarah E.;Doig, Andrew J.;Popelier, Paul L. A.;Waltho, Jonathan P.;Almond, Andrew
  • 通讯作者:
    Almond, Andrew
Harnessing the yeast Saccharomyces cerevisiae for the production of fungal secondary metabolites.
  • DOI:
    10.1042/ebc20200137
  • 发表时间:
    2021-07-26
  • 期刊:
  • 影响因子:
    6.4
  • 作者:
    Wang G;Kell DB;Borodina I
  • 通讯作者:
    Borodina I
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Andrew Almond其他文献

Point-of-Care Laboratory Data Collection During Critical Care Transport
  • DOI:
    10.1016/j.amj.2020.09.003
  • 发表时间:
    2021-01-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jamie Eastman;Deborah Allen;Kevin Mumma;Andrew Almond;Jason Theiling
  • 通讯作者:
    Jason Theiling
Structural characterisation of two forms of procyclic acidic repetitive protein expressed by procyclic forms of Trypanosoma brucei.
由布氏锥虫的原环形式表达的两种形式的原环酸性重复蛋白的结构特征。
  • DOI:
    10.1006/jmbi.1997.1066
  • 发表时间:
    1997
  • 期刊:
  • 影响因子:
    5.6
  • 作者:
    Achim Treumann;Nicole Zitzmann;Andreas Hülsmeier;Alan R. Prescott;Andrew Almond;John K. Sheehan;Michael A. J. Ferguson
  • 通讯作者:
    Michael A. J. Ferguson
Expression and Purification of Functionally Active Hyaluronan-binding Domains from Human Cartilage Link Protein, Aggrecan and Versican: FORMATION OF TERNARY COMPLEXES WITH DEFINED HYALURONAN OLIGOSACCHARIDES
  • DOI:
    10.1074/jbc.m411297200
  • 发表时间:
    2005-02-18
  • 期刊:
  • 影响因子:
  • 作者:
    Nicholas T. Seyfried;Gillian F. McVey;Andrew Almond;David J. Mahoney;Jayesh Dudhia;Anthony J. Day
  • 通讯作者:
    Anthony J. Day

Andrew Almond的其他文献

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{{ truncateString('Andrew Almond', 18)}}的其他基金

Rationalising glycomics with GPU-accelerated equilibrium simulations: a novel route to 3D-structure biological function and molecular design
通过 GPU 加速平衡模拟合理化糖组学:3D 结构生物功能和分子设计的新途径
  • 批准号:
    BB/J00040X/1
  • 财政年份:
    2012
  • 资助金额:
    $ 95.46万
  • 项目类别:
    Research Grant
Unravelling the biological function of heparan sulphate domain structure by three-dimensional analysis
通过三维分析揭示硫酸乙酰肝素结构域的生物学功能
  • 批准号:
    BB/G006768/1
  • 财政年份:
    2009
  • 资助金额:
    $ 95.46万
  • 项目类别:
    Research Grant
Customisation of our 3D drug-discovery software to the pharmaceutical sector: product analysis and development
为制药行业定制我们的 3D 药物发现软件:产品分析和开发
  • 批准号:
    BB/F528081/1
  • 财政年份:
    2008
  • 资助金额:
    $ 95.46万
  • 项目类别:
    Research Grant
A graphical user interface for novel software that expedites drug discovery by providing experimentally-determined 3D structures of free ligands.
新颖软件的图形用户界面,通过提供实验确定的游离配体的 3D 结构来加速药物发现。
  • 批准号:
    BB/F528006/1
  • 财政年份:
    2007
  • 资助金额:
    $ 95.46万
  • 项目类别:
    Research Grant

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