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Pushing Heterogeneous Catalysis into Biological Chemistry via Cofactor Regeneration

Pushing Heterogeneous Catalysis into Biological Chemistry via Cofactor Regeneration
通过辅因子再生将多相催化推向生物化学
批准号:
EP/V048635/1
负责人:
Xiaodong Wang
金额:
$25.78万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

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中文摘要
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英文摘要
Heterogeneous catalysts are well regarded as the workhorses of chemical transformations, being involved in over 90% of all industrial processes. Although heterogeneous catalysis offers many advantages over traditional synthetic routes, there are still some major areas where it is still lacking. For instance, with albeit a history of around 200 years, the majority of industrial processes and research using heterogeneous catalysed systems have thus far focused on either relatively small molecules (e.g. ammonia synthesis, Fischer-Tropsch process, natural gas reforming and water gas shift reactions), or traditional petrochemical/biomass feedstock (e.g. hydrocracking, polymerisation and biomass gasification, pyrolysis) and has neglected large biological molecules (such as the enzymatic cofactors) as reactants or products (in this context, "heterogeneous" refers to conventional solid bulk phase or supported metal catalysts, not immobilised enzymes or mimics). To expand the boundaries of heterogeneous catalysis to biochemistry in areas traditionally seen as belonging to biological enzymes will be fundamentally interesting, novel and attractive, facilitating potentially new routes for clean pharmaceutical and chemical production.Cofactor NAD(P)H is a critical reducing agent participating in enzymatic reductions for the synthesis of pharmaceutical/chemical products. A notable example of these products is "atorvastatin" (the active ingredient) for Lipitor ($11.9 billion global sale in 2010) which can lower the risk for heart attack and stroke, etc. or risk factors for heart disease (age, smoking, high blood pressure, etc.). The high cost of NAD(P)H and stoichiometric use make its regeneration essential for practical applications. There have been five existing methods (enzymatic, chemical, homogeneous catalytic, photo- and electro- catalytic) for this regeneration. Astonishingly, at least in part because there has been little knowledge in introducing supported metal catalysts to biological chemistry, nobody has embarked on serious studies of the potential of heterogeneous catalysts in cofactor regeneration and associated applications. This is what we plan to do. A fundamental understanding of the mechanism in the heterogeneous catalytic regeneration pathway and optimal solid catalysts will be obtained. The ultimate goal is to develop an efficient and clean process for cofactor regeneration that can work with biotransformations, taking enzymatic synthesis of pharmaceutical intermediates and CO2 conversion as representative applications.
期刊论文(3)
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DOI: 10.1021/acsami.2c01743
发表时间: 2022-04
期刊: ACS applied materials & interfaces
影响因子: 9.5
作者: [Joseph W. H. Burnett;Hui Chen;Jianwei Li;Ying Li;Shouying Huang;Jiafu Shi;A. Mccue;R. Howe;S. Minteer;Xiaodong Wang]
通讯作者: Joseph W. H. Burnett;Hui Chen;Jianwei Li;Ying Li;Shouying Huang;Jiafu Shi;A. Mccue;R. Howe;S. Minteer;Xiaodong Wang
DOI: 10.1016/j.cclet.2023.108737
发表时间: 2023-06
期刊: Chinese Chemical Letters
影响因子: 9.1
作者: [Jianwei Li;Joseph W. H. Burnett;C. M. Macias;R. Howe;Xiaodong Wang]
通讯作者: Jianwei Li;Joseph W. H. Burnett;C. M. Macias;R. Howe;Xiaodong Wang
A RadBackCom Approach to Integrated Sensing and Communication: Waveform Design and Receiver Signal Processing
  • 批准号:
    2335765
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2024
  • 负责人:
    Xiaodong Wang
  • 依托单位:
New Route to Zero Carbon Hydrogen
  • 批准号:
    EP/X018172/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $25.77万
  • 财政年份:
    2023
  • 负责人:
    Xiaodong Wang
  • 依托单位:
Collaborative Research: Real-Time Data-Driven Anomaly Detection for Complex Networks
  • 批准号:
    2040500
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2021
  • 负责人:
    Xiaodong Wang
  • 依托单位:
Collaborative Research: SHF: Medium: TensorNN: An Algorithm and Hardware Co-design Framework for On-device Deep Neural Network Learning using Low-rank Tensors
  • 批准号:
    1954549
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2020
  • 负责人:
    Xiaodong Wang
  • 依托单位:
海外基金