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Tools and Databases for Enzyme Function Prediction and Active Site Identification: Evolutionary Matching of Protein Surfaces

用于酶功能预测和活性位点识别的工具和数据库：蛋白质表面的进化匹配

基本信息

批准号：
0646035
负责人：
Jie Liang
金额：
$ 28.58万
依托单位：
University of Illinois at Chicago
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2007
资助国家：
美国
起止时间：
2007-08-01 至 2009-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0646035&HistoricalAwards=false
关键词：
Tools Databases Enzyme Function Prediction

项目摘要

The University of Illinois at Chicago is awarded a grant to develop novel computational methods for identifying surfaces on protein structures that are likely to be functionally important, for identification of key residues, and for predicting multi-functional enzymes. The PI''s will develop models and methods for constructing substitution rate matrices of local binding surfaces and will build a resource database of annotated protein functional surfaces of enzymes. The key technical products will be: novel methods for identifying functionally important binding surfaces on enzymes, for identifying candidate key residues, and for recognizing multifunctional enzymes with dual or more functional surface; a method for estimating evolutionary pattern of enzyme local surfaces; analysis of enzyme activities from structures; and a database of functional surfaces of enzyme structures. The computational tools proposed in this project will enable fast computational characterization of protein enzymes. The database as an outcome of proposed research will provide resources for biological researchers to identify functional surface, to locate key residues, and to assess possible multiple functional roles. They will also fill an important gap in current knowledge of enzymes by helping researchers to recognize potential alternative binding.

伊利诺伊大学芝加哥分校获得了一项资助，用于开发新的计算方法，用于识别蛋白质结构上可能具有重要功能的表面，用于识别关键残基，以及用于预测多功能酶。PI将开发构建局部结合表面取代率矩阵的模型和方法，并将建立酶的注释蛋白质功能表面的资源数据库。关键技术成果将是：识别酶的重要功能结合表面的新方法，识别候选关键残基的新方法，识别具有双重或多种功能表面的多功能酶的新方法；一种估计酶局部表面进化模式的方法从结构分析酶的活性；以及酶结构功能表面的数据库。本项目提出的计算工具将使蛋白质酶的快速计算表征成为可能。该数据库将为生物学研究人员识别功能表面、定位关键残基和评估可能的多种功能作用提供资源。它们还将通过帮助研究人员识别潜在的替代结合来填补当前酶知识的重要空白。