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Multi-scale enzyme modelling for SynBio: optimizing biocatalysts for selective synthesis of bioactive compounds

Multi-scale enzyme modelling for SynBio: optimizing biocatalysts for selective synthesis of bioactive compounds
SynBio 多尺度酶建模:优化生物催化剂以选择性合成生物活性化合物
批准号:
BB/M026280/1
负责人:
Marc Van Der Kamp
金额:
$90.39万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2015
资助国家:
英国
项目状态:
已结题
起止时间:
2015 至 --

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中文摘要
翻译
利用自然界中存在的强大原理来为我们的利益服务正变得越来越流行。一个关键的例子是,生物体具有非凡的能力,能够制造出具有高特异性(获得纯的、可能复杂的分子)和高效率(使用很少的能量)的分子。大自然利用酶和蛋白质作为催化剂来促进化学反应,从而实现这一目标。这些酶通常在温和的条件下起作用。酶已经在工业中被用于帮助制造我们在成本效益高、相对绿色和可持续的过程中所需的分子。然而,大自然并没有为我们提供一种酶来适应每一种所需分子的生产;通常,酶只催化特定起始物质的特定化学反应。但是进化的过程告诉我们,酶是可塑的,可以设计出不同的特性。例如,对酶的特定氨基酸(蛋白质的组成部分)进行微小的改变(突变)可以使这些酶接受不同的底物,从而催化形成新的、所需的分子。尽管有可能非常详细地确定酶中原子的位置(例如使用x射线晶体学),但改变氨基酸的全部影响并不明显。这限制了研究人员评估这些突变的影响(有益或有害)。例如,改变一个氨基酸可以影响酶的工作效率,通过改变起始物质的结合程度,起始物质转化的效率,以及酶的稳定性。我一直处于开发和使用结合量子力学和标准(牛顿)力学的方法来模拟酶中的化学反应的前沿。有了这些方法,计算机模拟可以用来评估氨基酸变化的不同可能影响。这项研究将开发出有效的方案来做到这一点,并改进方法,使它们能够应用于更复杂的酶系统和反应。正在研究的酶系统是可以制造许多不同的和潜在有价值的分子的酶的例子。抗流感药物、抗癌化合物、抗生素以及流行的天然风味化合物都是可以在这些酶的帮助下产生的分子的例子。通过获得这些酶如何工作的知识和开发修改它们的方案,我们可以以经济有效和可持续的方式获得生产新的有益化合物(如药物)的方法。
英文摘要
It is becoming increasingly popular to use the powerful principles present in nature to our advantage. A key example is the extraordinary ability of organisms to make molecules with high specificity (pure, potentially complex molecules are obtained) and efficiency (little energy is used). Nature uses enzymes, proteins that act as catalysts to promote chemical reactions, to achieve this. These enzymes typically work under mild conditions. Enzymes are already used in industry to help make molecules that we require in cost-efficient, comparatively green and sustainable processes. Nature has not, however, provided us with an enzyme to suit the production of every desired molecule; typically, enzymes only catalyze specific chemical reactions with specific starting materials. But the process of evolution teaches us that enzymes are malleable for engineering different properties. For example, making small changes (mutations) in specific amino acids (the building blocks of proteins) of enzymes can allow these enzymes to accept different substrates and thereby catalyze the formation of new, desired molecules. Even though it is possible to determine the positions of atoms in an enzyme with great detail (e.g. using X-ray crystallography), the full effects of making changes to amino acids are not evident. This limits researchers in assessing what the (beneficial or non-beneficial) effects of such mutations are. For example, changing a single amino acid can affect how efficient an enzyme works, by changing how well the starting material binds, how efficient the starting material is converted, and how stable the enzyme is. I have been at the forefront of developing and employing methods that combine quantum mechanics and standard (Newtonian) mechanics to simulate chemical reactions in enzymes. With these methods, computer simulations can be used to assess the different possible effects of amino acid changes. The proposed research will develop efficient protocols to do this, and enhance the methods so that they can be applied to more complex enzyme systems and reactions. The enzyme systems under investigation are examples of enzymes that can make many different and potentially valuable molecules. Anti-influenza drugs, anti-cancer compounds, antibiotics as well as popular natural flavour compounds are examples of molecules that could be produced with the help of these enzymes. By gaining knowledge on how these enzymes work and developing protocols to modify them, we can obtain ways to produce new beneficial compounds (such as drugs) in a cost-efficient and sustainable way.
期刊论文(10)
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DOI: 10.1084/jem.20221939
发表时间: 2023-09-04
期刊: The Journal of experimental medicine
影响因子: --
作者: []
通讯作者:
QM/MM Simulations Reveal the Determinants of Carbapenemase Activity in Class A ß-lactamases
QM/MM 模拟揭示了 A 类 - 内酰胺酶中碳青霉烯酶活性的决定因素
DOI: 10.26434/chemrxiv-2022-4jdc5
发表时间: 2022
期刊:
影响因子: --
作者: [Chudyk E]
通讯作者: Chudyk E
Simulating catalysis: Multiscale embedding of machine learning potentials
  • 批准号:
    EP/V011421/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $49.9万
  • 财政年份:
    2021
  • 负责人:
    Marc Van Der Kamp
  • 依托单位:
Engineering Water Capture in Terpene Synthases
  • 批准号:
    BB/R001332/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $37.51万
  • 财政年份:
    2018
  • 负责人:
    Marc Van Der Kamp
  • 依托单位:
国内基金
海外基金
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  • 批准号:
    22108101
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    靳光远
  • 依托单位:
基于Multi-Scale模型的轴流血泵瞬变流及空化机理研究
  • 批准号:
    31600794
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    22.0万元
  • 批准年份:
    2016
  • 负责人:
    荆腾
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基于异构医学影像数据的深度挖掘技术及中枢神经系统重大疾病的精准预测
  • 批准号:
    61672236
  • 项目类别:
    面上项目
  • 资助金额:
    64.0万元
  • 批准年份:
    2016
  • 负责人:
    王骏
  • 依托单位:
城镇居民亚健康状态的评价方法学及健康管理模式研究
  • 批准号:
    81172775
  • 项目类别:
    面上项目
  • 资助金额:
    14.0万元
  • 批准年份:
    2011
  • 负责人:
    许军
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