Automated Annotation of Function in Protein Structures from Evolutionary-based 3D-Templates

这个项目的目标是开发自动化算法来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。过去的NSF支持使ET能够自动进行功能位点分析；残基的3D模板的提取；在其他结构中搜索与这些模板的几何匹配；以及匹配的结构执行与模板相关的功能的统计可能性。这些步骤结合在一起，创建了一个完整的自动化功能注释管道，以促进新的目标：优化3D模板的提取，以捕获必要和充分的功能决定因素(目标1)；将新的模板信息添加到我们的匹配算法中，以更好地评估分子模仿是否构成功能相似性的基础(目标2)；以及开发使用多个模板来识别功能的新策略(目标3)。这一提议的广泛影响是多方面的。它将通过揭示蛋白质的哪些区域与生物最相关，从而为蛋白质工程和药物设计提供合乎逻辑的目标，从而加强生物学研究基础设施。其次，它将开发一种新的基因产品功能表征方法，将传统的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。该提案还将带来健壮、标准化和易于使用的软件。高中、本科生和研究生将参与该系统的开发。该项目将通过吸引女性和少数族裔申请者的校园项目扩大参与范围，这两所大学都在提供这一项目。

PI Olivier Lichtarge, Baylor College of MedicineCo-PI Lydia Kavraki, Rice UniveristyThe goals of this project are to develop automated algorithms to identify functional sites in protein structures and to characterize protein function on a genome scale. The approach is predicated on the Evolutionary Trace method (ET) to locate functional sites in structures. Past NSF support enabled to automate functional site analysis with ET; the extraction of 3D-templates of residues; the search in other structures for geometric matches to these templates; and the statistical likelihood that matched structures perform the function associated with the template. Taken together these steps create a complete, automated functional annotation pipeline that motivates the new goals: to optimize the extraction of 3-D templates that capture the necessary and sufficient determinants of function (Aim 1); to add new template information into our matching algorithms to better evaluate whether molecular mimicry underlies functional similarity (Aim 2); and the development of novel strategies that use multiple templates to identify function (Aim 3). The broader impact of this proposal is manifold. It will strengthen biological research infrastructure by revealing which regions of proteins are most biologically relevant and hence logical targets for protein engineering and drug design. Second, it will develop a novel method for functional characterization of gene products by extending to three dimensions a functional annotation strategy traditionally based on one-dimensional pattern matching in protein sequences. The proposal will also lead to software that is robust, standardized, and easy to use. High-school, undergraduates and graduate students will participate in the development of the system. The project will broaden participation using campus programs that attract female and minority applications and are being offered at both institutions.