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

位于芝加哥的伊利诺伊大学获得了一笔赠款，用于开发新的计算方法，用于识别可能具有重要功能的蛋白质结构表面，用于识别关键残基，以及用于预测多功能酶。PI将开发用于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资源数据库。关键技术产品将是：用于鉴定酶上功能重要的结合表面的新方法，用于鉴定候选关键残基，以及用于识别具有双重或多个功能表面的多功能酶;用于估计酶局部表面的进化模式的方法;从结构分析酶活性;以及酶结构的功能表面数据库。在这个项目中提出的计算工具将使蛋白质酶的快速计算表征。该数据库作为拟议研究的成果将为生物研究人员提供资源，以确定功能表面，定位关键残基，并评估可能的多种功能作用。它们还将通过帮助研究人员识别潜在的替代结合来填补目前酶知识的重要空白。

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.