Prediction of Protein Crystallization and Diffraction Quality

蛋白质结晶和衍射质量的预测

• 批准号: 7707893
• 负责人: ETHAN A MERRITT
• 金额: $ 19.5万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7707893
• 关键词: Affect; Base Sequence; Biological; Biological Process; Categories; Cellular Structures; Communities; Crystallization; Crystallography; Data; Data Display; Data Set; Data Storage and Retrieval; Databases; Disease; Evaluation; Failure; Gel; Genome; Goals; Housing; Image; Individual; Internet; Laboratories; Machine Learning; Medical; Meta-Analysis; Methods; Molecular Sieve Chromatography; Nucleic Acids; Numerical value; Online Systems; Outcome; Pharmaceutical Preparations; Play; Population; Process; Property; Proteins; Protocols documentation; Protozoa; Research; Role; Sampling; Secure; Set protein; Source; Structure; Targeted Research; Techniques; Training; Work; X-Ray Crystallography; base; data mining; database design; design; fundamental research; gel electrophoresis; improved; light scattering; melting; physical property; predictive modeling; programs; protein complex; prototype; public health relevance; structural biology; structural genomics; success; three dimensional structure; tool; two-dimensional; web interface; web site

DESCRIPTION (provided by applicant): Given the key role that crystallography plays in structural biology, protein crystallization remains a significant bottleneck affecting a broad range of research programs. We developing a data-mining framework, PROSPERO, that can predict crystallization success and crystal diffraction quality based on characterization of specific protein properties available prior to large-scale crystallization trials. This will increase the efficiency and overall success rates of diffraction studies by individual research programs as well as by genome-scale projects. PROSPERO will perform a meta-analysis of many individual predictors based on statistical and machine-learning methods. A key feature of this framework is that it can dynamically re-estimate success/failure rates based on the current contents of the underlying database, and on the set of physical characterization data provided by individual users. The design will be modular, in that we will define a standard set of application interfaces (APIs) for supplying new categories of data to the core data storage, meta-analysis and prediction components. This will allow use of PROSPERO to be tailored to individual research programs, to target-specific physical properties, and to incorporate new physical characterization techniques. Our long-term goal is to grow a user community that will benefit from the continually improving predictions made by a central PROSPERO web server, that will contribute new input modules based on data produced by standard laboratory protocols and apparatus, and will also contribute to the population of the underlying database of results used for prediction. PUBLIC HEALTH RELEVANCE: X-ray crystallography is a core technique in fundamental research programs that seek to understand disease mechanisms based on the three-dimensional structure of individual proteins, of large multi-protein complexes, and of larger assemblies of proteins and nucleic acids into key components of the cell. It is also a core technique in highly targeted research programs such as the design of new drugs. This work will increase the efficiency and overall success rate of these research programs by ameliorating a key bottleneck, the difficulty of obtaining high-quality crystals of the biological entity being studied.

描述（由申请人提供）：鉴于晶体学在结构生物学中的关键作用，蛋白质结晶仍然是影响广泛研究计划的重要瓶颈。我们开发了一个数据挖掘框架Prospero，该框架可以根据大规模结晶试验之前可用的特定蛋白质特性来预测结晶成功和晶体衍射质量。这将提高单个研究计划以及基因组规模项目的衍射研究效率和总体成功率。 Prospero将根据统计和机器学习方法对许多单个预测指标进行荟萃分析。该框架的一个关键功能是，它可以根据基础数据库的当前内容以及单个用户提供的一组物理表征数据来动态重新估计成功/失败率。该设计将是模块化的，因为我们将定义一组标准的应用程序接口（API），用于为核心数据存储，荟萃分析和预测组件提供新的数据类别。这将允许使用Prospero量身定制为单个研究计划，针对特定的物理特性并结合新的物理表征技术。我们的长期目标是建立一个将受益于中央Prospero Web服务器的不断改进的预测的用户社区，该服务器将根据标准实验室协议和设备的数据贡献新的输入模块，并将为预测结果的基础数据库的人群做出贡献。 公共卫生相关性：X射线晶体学是基础研究计划中的一种核心技术，试图根据单个蛋白质的三维结构，大型多蛋白质复合物以及较大的蛋白质和核酸组装的疾病机制理解疾病机制。它也是高度针对性的研究计划（例如新药设计）中的核心技术。这项工作将通过改善关键瓶颈来提高这些研究计划的效率和总体成功率，这是获得所研究的生物实体的高质量晶体的困难。