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Next-generation computational enzyme design for the creation of efficient artificial biocatalysts

Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
用于创建高效人工生物催化剂的下一代计算酶设计
批准号:
RGPIN-2021-03484
负责人:
Chica, Roberto
金额:
$5.76万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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英文摘要
Enzymes are the most efficient catalysts known. They can accelerate chemical reactions by more than a billion times, display unmatched selectivity, and are completely biodegradable. If we could create, from scratch, artificial enzymes that can catalyze any chemical reaction with high efficiency, it would open the door to highly valuable biotechnologies that are currently inaccessible using natural enzymes. These include biocatalytic syntheses of fine chemicals and pharmaceuticals, treatment of metabolic disorders, and bioremediation of contaminated water and soil. In this proposed research program, we will develop next-generation enzyme design methods and use them to create efficient artificial biocatalysts for the synthesis of valuable chemicals. These methods will be based on the multistate protein design algorithms that we developed in the previous funding cycle, which allow proteins to be modeled, not as a single structure as is traditionally done, but as structural ensembles that more realistically represent the range of conformations that these molecules can sample in solution. This is important because enzymes must "move" in order to catalyze chemical reactions with extreme precision and efficiency. To date, all published examples of computational enzyme design have focussed on the design of a single structural state, not taking into account the ability of enzymes to exchange between multiple states, and thereby yielded artificial enzymes with catalytic efficiencies several orders of magnitude worse than those of their natural counterparts. The development and experimental validation of our proposed multistate enzyme design algorithms will be undertaken in the following research themes. 1) We will develop methods to design complete enzymatic catalytic cycles, instead of considering only a single state as was done previously, and use them to create efficient biocatalysts for multistep reactions of industrial interest. 2) We will develop methods to predict mutations far from the active site that will have a favorable effect on catalysis, an essential requirement for the creation of highly active enzymes that nevertheless remains elusive. 3) We will develop multistate design methods to control enzyme conformational equilibria and eventually create large conformational changes required for more complex reactions. In the long term, we will combine these methods to create biocatalysts `on-demand' for valuable biotechnological applications. The proposed research program will provide world-class research training, in both computational and experimental techniques, to a diverse group of trainees, helping them acquire skills highly sought after by the pharmaceutical, biotech, and bioproducts industries. As enzymes can be applied to a wide range of commercially and societally relevant problems, our proposed research will yield new technologies required to tackle important challenges of 21st century Canada in industry, the environment and medicine.
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Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
  • 批准号:
    RGPAS-2021-00017
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
  • 资助金额:
    $2.91万
  • 财政年份:
    2022
  • 负责人:
    Chica, Roberto
  • 依托单位:
Advanced Protein Engineering Training, Internships, Courses, and Exhibition (APPRENTICE)
  • 批准号:
    511956-2018
  • 项目类别:
    Collaborative Research and Training Experience
  • 资助金额:
    $22.0万
  • 财政年份:
    2021
  • 负责人:
    Chica, Roberto
  • 依托单位:
Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
  • 批准号:
    RGPIN-2021-03484
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $5.76万
  • 财政年份:
    2021
  • 负责人:
    Chica, Roberto
  • 依托单位:
Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
  • 批准号:
    RGPAS-2021-00017
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
  • 资助金额:
    $2.91万
  • 财政年份:
    2021
  • 负责人:
    Chica, Roberto
  • 依托单位:
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  • 批准号:
    82371660
  • 项目类别:
    面上项目
  • 资助金额:
    49.00万元
  • 批准年份:
    2023
  • 负责人:
    魏喆
  • 依托单位:
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  • 批准号:
    30470495
  • 项目类别:
    面上项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2004
  • 负责人:
    邓小元
  • 依托单位: