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New Strategies and Catalysts for an Economic Access to Highly Functional Asymmetric Macrocycles

New Strategies and Catalysts for an Economic Access to Highly Functional Asymmetric Macrocycles
经济获取高功能不对称大环化合物的新策略和催化剂
批准号:
5407883
负责人:
Professor Dr. Ludger A. Wessjohann
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2003
资助国家:
德国
项目状态:
已结题
起止时间:
2002-12-31 至 2007-12-31

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中文摘要
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英文摘要
The aim of the project is the design and elaboration of rapid, efficient and waste-minimized strategies and tools for the synthesis of asymmetric, highly functionalized macrocycles of a molecular weight range of ca. 500 to 2000. Up to eight building blocks will be combined and cyclized in a one pot fashion. The overall process including the synthesis of the building blocks will not include the loss of a single carbon, ideally only water or in the case of enzyme applications the respective activation groups (e.g. diphosphate) are released. Even the designed chemical catalysts should either be recoverable due to immobilization, and/or be metal free. This will be achieved by natural product derived di- or polyfunctional building blocks, multiple or multiple-interlocked multi-component reactions -initially mostly of UGI-type-, new cyclization processes (by multi-component and enzyme-catalyzed cyclization reactions), the study of new catalytic systems for multi-component-reactions and combinations of all of the above.
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Chalkogenbasierte Organokatalyse: Mechanistische Untersuchungen und Design von Katalysatoren, deren Aktivität wesentlich durch Sauerstoff oder ein höheres Chalkogen bestimmt ist
  • 批准号:
    5451722
  • 项目类别:
    Priority Programmes
  • 资助金额:
    $0.0万
  • 财政年份:
    2005
  • 负责人:
    Professor Dr. Ludger A. Wessjohann
  • 依托单位:
Reactivity and modelling studies of Selenium in Se-proteins and reference compounds: Examination and design of Selenium-selective tags and ligands
  • 批准号:
    5366747
  • 项目类别:
    Priority Programmes
  • 资助金额:
    $0.0万
  • 财政年份:
    2002
  • 负责人:
    Professor Dr. Ludger A. Wessjohann
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis