Comparative genomics of protein structure and function

蛋白质结构和功能的比较基因组学

• 批准号: 7786185
• 负责人: OLIVIER LICHTARGE
• 金额: $ 27.85万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-01 至 2011-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7786185
• 关键词: 3-Dimensional; Address; Algorithms; Amino Acid Sequence; Amino Acids; Benchmarking; Binding; Binding Sites; Biological; Biological Process; Biology; Catalysis; Collaborations; Data; Databases; Dimensions; Drug Design; Electrostatics; Enzymes; Failure; Genomics; Goals; Gold; Ligand Binding; Link; Machine Learning; Manuals; Maps; Measures; Methods; Molecular; Molecular Conformation; Molecular Mimicry; Mutation; Outcome; PAWR protein; Pattern; Peptide Sequence Determination; Performance; Pharmaceutical Preparations; Protein Binding; Protein Engineering; Protein Region; Protein Structure Initiative; Proteins; Research Personnel; Resources; Sampling; Sensitivity and Specificity; Site; Solutions; Solvents; Source; Source Code; Specificity; Structure; Surface; Testing; United States National Institutes of Health; Variant; Work; base; comparative genomics; computer studies; conformer; database structure; design; falls; flexibility; heuristics; inhibitor/antagonist; interest; mimetics; novel strategies; programs; protein function; protein structure; protein structure function; structural genomics; success; tool

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.

描述（由申请人提供）：这项工作旨在开发识别蛋白质结构中的功能位点并在基因组规模上表征蛋白质功能的方法。该方法基于进化追踪方法（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的、自动化的功能注释管道的基本步骤，即使用 ET 进行功能位点分析；从 SD 模板的 ET 分析中提取，描述了参与结合或催化功能的关键残基的组成和构象；在其他结构中搜索与这些 3D 模板的几何匹配；并分析哪些匹配的最具生物学相关性。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拟态是否是功能相似性的基础，从而提高注释管道的敏感性和特异性；并通过开发使用多个模板来识别功能的新颖策略。结果将揭示蛋白质的哪些区域在生物学上最相关，从而成为蛋白质工程和药物设计的逻辑目标，并将传统上基于蛋白质序列中一维模式匹配的功能注释策略扩展到三个维度。通过这样做，这项工作解决了“后基因组生物学”中的一个基本的 NIH 路线图问题：将大量且呈指数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。