TARGET SELECTION FOR THE STRUCTURAL GENOMICS OF CANCER

癌症结构基因组学的靶标选择

• 批准号: 6350429
• 负责人: THERESA GAASTERLAND
• 金额: $ 33.75万
• 依托单位: ROCKEFELLER UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-02-01 至 2003-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6350429
• 关键词: animal genetic material tag; chemical models; computer assisted sequence analysis; computer system design /evaluation; functional /structural genomics; human genetic material tag; model design /development; neoplasm /cancer genetics; nucleic acid sequence; oncoproteins; open reading frames; protein sequence; protein structure function

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.

描述：(申请人的描述)这项建议的主要目的是 促进癌症的结构和功能基因组学。具体目标是 开发和应用用于(I)识别和注释的计算工具 癌症相关蛋白质序列；(Ii)确定目标蛋白质的优先顺序 癌症的结构基因组学；和(Iii)最大限度地利用结构信息 与癌症相关的蛋白质。第一个目标将通过收集 美国国立卫生研究院癌症基因组解剖计划中的癌症相关蛋白质序列 并通过在代谢和代谢数据库中识别额外的此类序列 信号通路和初级序列数据库。出现在细胞内的蛋白质 与癌症蛋白、蛋白质具有相同的途径或具有相似的调控模式 与癌症蛋白或其表达共有的蛋白质相互作用 癌症蛋白质的特征也将被认为是癌症- 相关蛋白质。癌症相关的可查询和最新注释 蛋白质将通过与所有已知蛋白质进行敏感性比较而获得。 序列和结构。注释将包括比较蛋白质 具有指定折叠的所有癌症相关蛋白质的结构模型。这个 第二个目标是确定目标蛋白结构域并确定其优先顺序 AECOM/Brookaven/Rockefeller结构基因组研究联盟(SGRC) 将专注于开发结构的高通量技术 X射线结晶学和核磁共振技术测定肿瘤相关蛋白 光谱学。目标结构域将主要与酵母相对应 未知结构的癌症相关蛋白的同源物。目标是 列表将动态更新，以最大化结构中的信息 决定。第三个目标是分析和使用确定的结构 由SGRC进行比较结构建模和比较分析 与癌症相关的蛋白质越多越好。注解、建模和分析 工具将建立在鹊类系统上，用于自动进行基因组注释，以及 用于大规模比较建模的建模器管道。注解 将用计算机语言PROLOG通过逻辑规则和 关系事实，包括捕获计算的对齐数据的规则、域 定义，以及有关目标域属性的用户首选项。这个 能够同时提及…的顺序、结构和功能 癌症相关蛋白，按序列和结构家族组织，将 允许癌症研究人员解决目前不容易解决的问题 回答。这个项目将显著增加蛋白质的含量。 癌症生物学家可以利用的结构信息。一组癌症- 相关蛋白质、它们的注释、家族成员和结构模型 将可以通过网络高效地访问。