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中文摘要
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描述(由申请人提供):这项工作旨在开发方法来识别蛋白质结构中的功能部位,并在基因组规模上表征蛋白质的功能。该方法基于进化踪迹方法(ET)来定位结构中的功能位点。初步研究使我们能够自动化实现完整、自动化功能注释管道的基本步骤,即利用ET进行功能位点分析;从ET中提取描述结合或催化功能所涉及的关键残基的组成和构象的SD模板;在其他结构中搜索与这些3D模板的几何匹配;以及分析哪些匹配的模板具有最高的生物相关性。我们现在寻求通过优化3-D模板的定义,通过添加新的模板特征来更好地判断分子模仿是否构成功能相似性的基础,以及通过开发使用多个模板来识别功能的新策略来提高注释管道的敏感性和特异性。这一结果将揭示蛋白质的哪些区域最具生物相关性,从而成为蛋白质工程和药物设计的合理目标,并将传统上基于蛋白质序列一维模式匹配的功能注释策略扩展到三维。在这样做的过程中,这项工作解决了NIH在“后基因组生物学”中的一个基本路线图问题:将大量且呈指数级增长的原始序列和结构数据与生物功能的分子基础联系起来。
英文摘要
DESCRIPTION (provided by applicant): This work aims to develop methods to identify functional sites in protein structures and to characterize protein function on a genomic scale. The approach is predicated on the Evolutionary Trace method (ET) to locate functional sites in structures. Preliminary studies enabled us to automate the basic steps towards a complete, automated functional annotation pipeline, namely, functional site analysis with ET; extraction from ET analysis of SD-templates that describe composition and conformation of key residues involved in binding or catalytic function; the search in other structures for geometric matches to these 3D-templates; and the analysis of which of those matched are most biologically relevant. We now seek to increase the sensitivity and specificity of the annotation pipeline by optimizing the definition of 3-D templates, by adding new template features to better judge whether molecular mimicry underlies functional similarity; and by developing novel strategies that use multiple templates to identify function. The result will reveal which regions of proteins are most biologically relevant, and hence logical targets for protein engineering and drug design, and it will extend to three dimensions a functional annotation strategy traditionally based on one- dimensional pattern matching in protein sequences. In so doing, this work addresses a fundamental NIH roadmap problem in "post-genomic biology": linking massive and exponentially growing amounts of raw sequence and structure data to the molecular basis of biological function.
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2022 Human Genetic Variation and Disease GRC and GRS
  • 批准号:
    10468402
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2022
  • 负责人:
    OLIVIER LICHTARGE
  • 依托单位:
Cognitive Computing of Alzheimer's Disease Genes and Risk
  • 批准号:
    10436879
  • 项目类别:
  • 资助金额:
    $80.0万
  • 财政年份:
    2021
  • 负责人:
    OLIVIER LICHTARGE
  • 依托单位:
Cognitive Computing of Alzheimer's Disease Genes and Risk
  • 批准号:
    10622973
  • 项目类别:
  • 资助金额:
    $27.11万
  • 财政年份:
    2021
  • 负责人:
    OLIVIER LICHTARGE
  • 依托单位:
Cognitive Computing of Alzheimer's Disease Genes and Risk
  • 批准号:
    10669697
  • 项目类别:
  • 资助金额:
    $80.0万
  • 财政年份:
    2021
  • 负责人:
    OLIVIER LICHTARGE
  • 依托单位:
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