DNA-binding specificities of Cys2His2 zinc fingers
DNA-binding specificities of Cys2His2 zinc fingers
批准号:
7772289
负责人:
J. KEITH JOUNG
金额:
$37.08万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-03-01 至 2011-02-28
关键词:
AddressAffinityAlgorithmsAmino Acid SequenceAmino AcidsArchivesBase CompositionBase PairingBindingBinding SitesCellsCodeComputing MethodologiesDNA BindingDataData SetDevelopmentEngineeringEukaryotaEukaryotic CellFundingGene ExpressionGene TargetingGeneral HospitalsGenesGenomeGenomicsGoalsGuanineHumanHuman GenomeLaboratoriesLibrariesMassachusettsMethodologyMethodsNIH Program AnnouncementsOrganismPatternProteinsRandomizedReagentRegulatory PathwayResearchResearch PersonnelSeriesSiteSpecificityStructureTestingTrainingUniversitiesWashingtonWorkZinc Fingersbasedesigngenome sequencingimprovedinterestmammalian genomemedical schoolsmembernucleasepredictive modelingpreferenceprogramsresponsetranscription factoryeast two hybrid system
中文摘要
描述(由申请人提供):该申请是响应项目公告PA-03-127(综合和协作研究方法),其长期目标是开发预测Cys2His2锌指蛋白结合特异性的算法,Cys2His2锌指蛋白是人类基因组中编码的最常见的dma结合结构域。为此,我们建议设计和表征大量人工Cys2His2锌指蛋白的dma结合特异性,并使用该综合数据集开发和验证Cys2His2锌指的概率dma识别代码,大大提高了预测能力。大量具有明确特异性的工程Cys2His2锌指结构域档案的开发,也应该对大量对工程定制“设计师”锌指核酸酶感兴趣的研究人员普遍有用(最近显示是在人类细胞中诱导位点特异性基因靶向的强大试剂)。我们将与联盟成员Gary Stormo博士(华盛顿大学医学院)和scott Wolfe博士(马萨诸塞大学医学院)合作,开发方法、试剂、数据和算法,以了解Cys2His2锌指的dma结合特异性。这些活动将加强r01资助的三个实验室研究项目的长期目标。具体而言,该项目将提供重要的锌指试剂和结合特异性数据,以促进R01GM069906 (NRSF/REST锌指- dma相互作用研究;PI: Joung)的长期目标,以了解自然发生的扩展锌指- dma界面,并设计高度特异性的工程锌指结构域,能够识别哺乳动物基因组中的独特地址。同样,这些试剂和特异性数据也将促进二聚体工程锌指蛋白的开发,这些蛋白可以结合并调节真核细胞中的单个内源性基因(R01GM068110: dimeric Cys2His2 zinc finger proteins for gene Targeting; PI: Wolfe)。最后,预测真核锌指转录因子DMA结合特异性的算法的发展扩展了R01 HG000249 (DMA模式识别和分析;PI: Stormo)的基本目标,即开发计算方法来确定DMA结合转录因子的特异性并确定其在基因组序列中的调控位点。
英文摘要
DESCRIPTION (provided by applicant): This application is in response to Program Announcement PA-03-127 (Integrative and Collaborative Approaches to Research) and has the long-term goal of developing algorithms for predicting the binding specificities of Cys2His2 zinc finger proteins, the most common DMA-binding domain encoded in the human genome. To do this, we propose to engineer and characterize the DMA-binding specificities of a large series of artificial Cys2His2 zinc finger proteins and to use this comprehensive dataset to develop and validate probabilistic DMA-recognition codes for Cys2His2 zinc fingers with greatly improved predictive power. The development of a large archive of engineered Cys2His2 zinc finger domains with well-defined specificities should also be generally useful to a large number of researchers interested in engineering customized "designer" zinc finger nucleases (recently shown to be powerful reagents for inducing site- specific gene targeting in human cells). Working together with Consortium Members Dr. Gary Stormo (of the Washington University School of Medicine) and Dr. Scot Wolfe (of the University of Massachusetts Medical School), we will develop methodologies, reagents, data, and algorithms relevant to understanding the DMA-binding specificities of Cys2His2 zinc fingers. These activities will enhance the long-term goals of R01-funded research programs in all three laboratories. Specifically, the proposed project will provide important zinc finger reagents and binding specificity data that will facilitate the long-term goals of R01GM069906 (Studies of NRSF/REST Zinc Finger-DMA Interactions; PI: Joung) to understand naturally occurring extended zinc finger-DMA interfaces and to design highly specific engineered zinc finger domains capable of recognizing unique addresses within mammalian genomes. Similarly, these reagents and specificity data will also facilitate the development of dimeric engineered zinc finger proteins that can bind to and regulate a single endogenous gene in eukaryotic cells (R01GM068110: Dimeric Cys2His2 Zinc Finger Proteins for Gene Targeting; PI: Wolfe). Finally, the development of algorithms to predict DMA-binding specificities of eukaryotic zinc finger transcription factors extends a fundamental goal of R01 HG000249 (DMA pattern identification and analysis; PI: Stormo) to develop computational methods to determine the specificity of DMA-binding transcription factors and identify their regulatory sites within genome sequences.
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