Center for Critical Assessment of Structure Prediction

描述(由申请人提供)： 该项目的主要目标是为蛋白质结构预测(CASP)预测实验的关键评估提供基础设施。随着测序计划的成功，基因组编码蛋白质的结构特征变得越来越重要。对蛋白质结构的广泛了解将大大有助于蛋白质功能、蛋白质相互作用和生化途径的研究。它还将对我们对生物学和人类疾病的理解产生重大影响，并最终影响药物设计。结构的实验确定本质上是耗时和昂贵的。目前，通过测序和结构确定工作表征的蛋白质在数量上存在两个数量级的差距。结构建模和预测的计算技术为缩小这一差距带来了巨大的希望。建立CASP过程是为了回答两个主要问题：第一，这些技术的预测质量可以预期到什么水平？第二，哪些方法为持续发展提供了最大希望？CASP是一个社区范围的计划，全球约有200个研究小组在上一轮提交了超过40,000个预测。我们的团队是CASP的主要基础设施资源，负责处理预测、开发和实施评估软件、执行预测评估、开发分析和显示工具，并为访问预测及其评估数据提供便利。我们提议支持次级方案继续运作并扩大其基础设施，包括增加评估预测的能力、进一步开发和完善评估软件以及改进预测分析方法。此外，我们将进行一系列专门的非CASP实验，致力于克服结构预测方面取得进展的最重要障碍。我们还将为一个社区范围的计划提供基础设施，以建立具有生物重要性的蛋白质的有用结构模型。最后，我们将特别重视与整个学术界的讲师和研究人员的互动，目的是传播通过CASP获得的经验和丰富的数据。

DESCRIPTION (provided by applicant): The primary goal of this project is to provide the infrastructure for the Critical Assessment of Protein Structure Prediction (CASP) prediction experiments. With the success of the sequencing projects, the structural characterization of the genome-encoded proteins becomes increasingly important. Extensive knowledge of protein structure will significantly aid the investigation of protein function, protein interactions, and biochemical pathways. It will also have a major impact on our understanding of biology and human disease, and eventually on drug design. Experimental determination of structure is inherently time-consuming and costly. Currently there is a two order-of-magnitude gap in numbers between proteins characterized by sequencing and by structure determination efforts. Computational techniques of structure modeling and prediction hold great promise for narrowing this gap. The CASP process was established to answer two main questions: First, what level of prediction quality can be expected of these techniques? And second, which methods offer the most promise for continued development? CASP is a community-wide program, with approximately 200 research groups world-wide submitting over 40,000 predictions in the last round. Our group is the primary infrastructure resource for CASP, and handles processing of predictions, develops and implements evaluation software, performs prediction assessment, develops analysis and display tools, and facilitates access to predictions and their evaluation data. We propose to support the continuing operation of CASP and to expand its infrastructure, including an increased capacity for assessing predictions, further development and refinement of the evaluation software, and improved prediction analysis methods. In addition, we will conduct a series of specialized off-CASP experiments dedicated to overcoming the most significant obstacles to progress in structure prediction. We will also provide the infrastructure for a community-wide program to build useful structural models of biologically important proteins. Finally, we will place special emphasis on interactions with lecturers and researchers throughout academia with the goal of disseminating the experience and the wealth of data gained through CASP.