TARGET SELECTION FOR THE STRUCTURAL GENOMICS OF CANCER

癌症结构基因组学的靶标选择

• 批准号: 6497963
• 负责人: THERESA GAASTERLAND
• 金额: $ 34.76万
• 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 2004-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6497963
• 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）该提议的广泛目的是 促进癌症的结构和功能基因组学。具体目的是 开发和应用计算工具以识别和注释 与癌症相关的蛋白质序列； （ii）优先考虑目标蛋白 癌症的结构基因组学； （iii）最大化结构信息 关于与癌症相关的蛋白质。第一个目标将通过收集来实现 NCI的癌症基因组解剖项目中与癌症相关的蛋白质序列 并通过在代谢和代谢数据库中识别其他序列 信号通路和主要序列数据库。发生在 相同的途径或具有与癌症，蛋白质相似的调节模式 与癌症蛋白相互作用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视为癌症 - 相关蛋白质。与癌症相关的可查询和最新注释 将通过对所有已知蛋白的敏感比较来获得蛋白质 序列和结构。注释将包括比较蛋白 所有与癌症相关的蛋白质的结构模型。这 第二个目的是确定和确定目标蛋白域的优先级 AECOM/Brookhaven/Rockefeller结构基因组学研究联盟（SGRC） 这将着重于为结构开发高通量技术 通过X射线晶体学和NMR测定与癌症相关蛋白的测定 光谱法。目标域将主要对应于酵母 癌症相关蛋白质的同源物，没有已知结构。目标 列表将动态更新以最大化结构的信息 确定。第三个目的是分析和使用确定的结构 通过SGRC进行比较结构建模和比较分析 尽可能与癌症相关的蛋白质。注释，建模和分析 工具将建立在自动基因组注释的喜p系统上，并在 用于大规模比较建模的建模管道。注释 将通过逻辑规则在计算机语言中定义 关系事实，包括捕获计算对准数据的规则，域 定义以及对目标域属性的用户偏好。这 能够同时引用的序列，结构和功能 癌症相关的蛋白质是按顺序和结构家族组织的，将 允许癌症研究人员解决目前不容易的问题 回答。该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。一组癌症 相关蛋白质，其注释，家庭成员和结构模型 可以通过网络有效访问。

项目成果

MODBASE: a database of annotated comparative protein structure models and associated resources.

• DOI: 10.1093/nar/gkj059
• 发表时间: 2006-01-01
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Pieper U;Eswar N;Davis FP;Braberg H;Madhusudhan MS;Rossi A;Marti-Renom M;Karchin R;Webb BM;Eramian D;Shen MY;Kelly L;Melo F;Sali A
• 通讯作者: Sali A

Characterizing the relationship between protein-fusion and gene co-expression.

表征蛋白质融合与基因共表达之间的关系。

• 发表时间: 2001
• 期刊: Genome informatics. International Conference on Genome Informatics.
• 作者: Gunther,CS;Gaasterland,T
• 通讯作者: Gaasterland,T