Fluorous Quantitative Proteomics
荧光定量蛋白质组学
基本信息
- 批准号:7217109
- 负责人:
- 金额:$ 18.01万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2006
- 资助国家:美国
- 起止时间:2006-09-30 至 2008-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
DESCRIPTION (provided by applicant): Project Summary/Abstract: The long-term goal of the project is to develop and then commercialize stable isotope reagents for quantitative proteomics using fluorous enrichment techniques. Successful demonstration in proteomics will be followed by extension into metabolomics and glycomics using a similar tagging strategy. Fluorous Technologies, Inc. (FTI) as the small business concern, and The Genomics Institute of the Novartis Research Foundation (GNF), as a collaborator, will synthesize fluorous isotope reagent tags (FLIRTs), develop protocols, benchmark vs. existing techniques, and demonstrate the FLIRT approach in the quantification of protein function. The specific aims of the grant are: 1) Synthesis of aniline based FLIRTs. Synthetic routes to 5 fluorous probes for chemical labeling of peptides and proteins will be synthesized based on a fluorous aniline core. A goal of 500 mg of each unlabeled compound and 150 mg of each labeled compound is targeted. 2) Synthesis of stable isotope labeled versions of the existing fluorous reagents. FLIRTs with the stable isotopes directly in the fluorous chain will be synthesized. The goal will be to obtain 100 mg of each compound. These compounds will be the direct stable isotope labeled analogs of fluorous peptide labeling reagents which FTI has previously produced. 3) Development of quantitative tagging protocols using the fluorous isotope labeled reagents and benchmarking vs. cICAT. Protocols for tagging and enrichment using FLIRTs will be developed using LC/MS with ESI detection. Quantification by FLIRT will then be benchmarked against cICAT. Performance measures will include enrichment efficiency, selectivity biases, selectivity enrichment, recovery of enriched species, and accuracy of quantitation. 4) Fluorous isotope reagent tagging (FLIRT) for relative quantification of a targeted subproteome. FLIRT technology will be applied to the quantification of specific classes of proteins within a complex sample, including the characterization of the redox state of the various cysteine residues within a protein. Successful enrichment and quantitation through a single label will demonstrate the flexibility of FLIRTs in analyzing targeted classes of proteins. FLIRTs will provide a novel method for quantitative proteomics which can be applied to numerous research areas including target discovery, biomarker discovery, and diagnostics development for various diseases affecting the human condition. Project Narrative: The goal of the project is to develop and commercialize reagents for quantitative proteomics. The successful commercialization of these products will enable researchers to elucidate biological pathways leading to new biomarkers and targets by which to develop novel diagnostics and therapeutics for various diseases that affect the human condition.
描述(由申请人提供):项目摘要/摘要:该项目的长期目标是使用荧光富集技术开发稳定的同位素试剂,以进行定量蛋白质组学。蛋白质组学中成功的演示将使用类似的标记策略扩展到代谢组学和糖基因。 Cluorof Technologies,Inc。(FTI)作为小型企业关注,而诺华研究基金会(GNF)的基因组学研究所(GNF)将作为合作者,合成易流量的同位素试剂标签(调情),制定协议,基准,基准,现有技术,现有技术,现有技术,现有技术,现有技术,并演示了定量蛋白质功能的调情方法。赠款的具体目的是:1)基于苯胺的调情的合成。将肽和蛋白质化学标记的5个荧光探针的合成途径将基于荧光苯胺核心合成。每种未标记的化合物和150 mg的每个标记化合物的目标是500毫克的目标。 2)合成稳定的同位素标记为现有氟试剂的版本。直接在荧光链中直接与稳定的同位素调味。目标是获得每种化合物的100毫克。这些化合物将是FTI先前已经生产的荧光肽标记试剂的直接稳定同位素标记的类似物。 3)使用标记为试剂和基准测试与CICAT的荧光同位素的定量标记方案开发。使用LC/MS进行ESI检测,将开发用于使用调情的标记和富集的协议。然后,通过调情定量将针对CICAT进行基准测试。绩效指标将包括富集效率,选择性偏见,选择性富集,富集物种的回收以及定量的准确性。 4)用于靶向亚蛋白质组的相对定量的荧光同位素试剂标签(调情)。调情技术将应用于复杂样品中特定类别的蛋白质类别的定量,包括蛋白质中各种半胱氨酸残基的氧化还原状态的表征。通过单个标签成功的富集和定量将证明调情在分析靶向蛋白质类别时的灵活性。调情将为定量蛋白质组学提供一种新颖的方法,该方法可应用于众多研究领域,包括目标发现,生物标志物发现以及影响人类状况的各种疾病的诊断开发。项目叙述:该项目的目的是开发和商业化定量蛋白质组学的试剂。这些产品的成功商业化将使研究人员能够阐明生物学途径,从而导致新的生物标志物和靶标,以开发针对影响人类状况的各种疾病的新型诊断和治疗剂。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Marvin S Yu其他文献
Marvin S Yu的其他文献
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7684117 - 财政年份:2007
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$ 18.01万 - 项目类别:
Diversity-Oriented Synthesis of Novel Heterocyclic & Natural Product-Like Library
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