TARGET SELECTION FOR THE STRUCTURAL GENOMICS OF CANCER

描述：（申请人的描述）本提案的广泛目的是 促进癌症的结构和功能基因组学。具体目标是 开发和应用计算工具来（i）识别和注释 癌症相关蛋白质序列;（ii）优先考虑癌症相关蛋白质序列的靶蛋白质; 癌症的结构基因组学;以及（iii）最大化结构信息 关于癌症相关蛋白质。第一个目标将通过收集 癌症相关蛋白质序列，来自NCI癌症基因组解剖计划 并通过在代谢和生物学数据库中鉴定另外的这样的序列， 信号通路和一级序列数据库。蛋白质发生在 与癌蛋白、蛋白质相同的途径或具有相似的调控模式 与癌症蛋白质相互作用，或与癌症蛋白质的表达共享的蛋白质， 与癌症蛋白质的特征相同的特征也将被认为是癌症- 相关蛋白质可查询和最新的癌症相关注释 蛋白质将通过与所有已知蛋白质的灵敏比较而获得 序列和结构。注释将包括比较蛋白质 所有癌症相关蛋白质的结构模型与指定的折叠。的 第二个目的是鉴定和优先化用于所述蛋白质的靶蛋白结构域。 AECOM/Brookhaven/Rockefeller Structural Genomics Research Consortium（SGRC） 将专注于开发高通量技术， 用X射线晶体学和核磁共振测定癌症相关蛋白 谱靶结构域将主要对应于酵母 结构未知的癌症相关蛋白的同源物。目标 列表将动态更新，以最大化结构中的信息 决心。第三个目的是分析和使用所确定的结构 通过SGRC进行结构建模和对比分析， 癌症相关蛋白质。注释、建模和分析 工具将建立在MAGPIE系统的自动基因组注释， 用于大规模比较建模的MODELLER管道。注释 将通过逻辑规则在计算机语言Prolog中定义， 关系事实，包括捕获计算的对齐数据的规则、域 定义，以及用户对目标域属性的偏好。的 能够同时提及序列、结构和功能， 与癌症相关的蛋白质，在序列和结构家族中组织， 让癌症研究人员能够解决目前还不容易解决的问题， 回答这个项目将大大增加蛋白质的量 癌症生物学家可用的结构信息。一系列的癌症- 相关蛋白质，它们的注释，家族成员和结构模型 将通过网络有效地访问。

DESCRIPTION: (Applicant's Description) The broad aim of this proposal is to facilitate structural and functional genomics of cancer. The specific aims are to develop and apply computational tools for (i) identifying and annotating cancer-related protein sequences; (ii) prioritizing target proteins for the structural genomics of cancer; and (iii) maximizing structural information about cancer-related proteins. The first aim will be achieved by collecting cancer-related protein sequences from The Cancer Genome Anatomy Project at NCI and by identifying additional such sequences in the databases of metabolic and signaling pathways, and primary sequence databases. Proteins that occur in the same pathway or have similar regulatory patterns as cancer proteins, proteins that interact with cancer proteins, or proteins whose expression shares features with that of the cancer proteins will also be considered as cancer- related proteins. Queryable and up-to-date annotations of cancer-related proteins will be obtained by sensitive comparisons to all known protein sequences and structures. The annotations will include comparative protein structure models for all cancer-related proteins with assigned folds. The second aim is to identify and prioritize target protein domains for the AECOM/Brookhaven/Rockefeller Structural Genomics Research Consortium (SGRC) that will focus on developing high-throughput technology for structure determination of the cancer-related proteins by X-ray crystallography and NMR spectroscopy. The target domains will correspond primarily to the yeast homologs of the cancer-related proteins without known structure. The target list will be dynamically updated to maximize information from structure determinations. The third aim is to analyze and use the structures determined by SGRC for comparative structure modeling and comparative analysis of as many cancer-related proteins as possible. The annotation, modeling and analysis tools will build on the MAGPIE system for automated genome annotation, and on the MODELLER pipeline for large-scale comparative modeling. The annotations will be defined in the computer language Prolog through logical rules and relational facts, including rules to capture computed alignment data, domain definitions, and user preferences about properties of target domains. The ability to refer at the same time to the sequence, structure, and function of cancer-related proteins, organized in sequence and structure families, will allow cancer researchers to address questions that are currently not easily answered. This project will increase significantly the amount of protein structure information available to cancer biologists. The set of cancer- related proteins, their annotations, family membership, and structural models will be accessible efficiently over the web.