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Proteomic Analysis Using FTICR/MS

Proteomic Analysis Using FTICR/MS
使用 FTICR/MS 进行蛋白质组分析
批准号:
6719692
负责人:
I JONATHAN AMSTER
金额:
$33.26万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-22 至 2007-07-31

项目摘要

项目成果

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中文摘要
翻译
描述(由申请人提供):拟议的研究旨在开发用于定量分析生物系统中蛋白质表达变化的新方法。提出的发展将提供比目前可能更快地分析复杂蛋白质混合物的手段。目前的方法依赖于将蛋白质混合物分离成单独的成分,然后对分离的蛋白质进行分析鉴定。提出的发展将允许同时鉴定混合物中的所有蛋白质,从而大大减少分析时间和精力。蛋白质混合物将被酶消化,得到的蛋白水解肽混合物将被液相色谱分离,并通过高分辨率质谱分析。原始混合物中的蛋白质将通过使用产生的精确质量数据从其蛋白水解片段中识别出来。目前,只有一小部分肽可以通过精确的质量测量来分配给蛋白质。大多数提议的努力将直接用于开发方法,以增加肽的比例,可以分配到他们的亲本蛋白。提出了一种称为“质量缺陷标记”的方法,以增加分配的特异性。提出了几种用于质量缺陷标记的新试剂,并将作为项目的一部分进行合成。这些试剂不仅有助于蛋白质鉴定,而且可用于定量蛋白质组学。其他实验将探索使用稳定同位素的内源性标记与使用质量缺陷标记来实现蛋白质鉴定的高特异性。综合使用这些方法,计算表明,对于原核生物蛋白质组的分析,高达95%的被测量的肽可以分配给它们产生的蛋白质。这些发展的成功将对生物研究、药物发现和医学产生重大影响。建议的努力将由研究生和本科生共同进行,并将有利于他们的科学发展。参与这项研究的学生将接触到最先进的高分辨率质谱分析。这将为社会提供在这一关键技术领域训练有素的科学家。
英文摘要
DESCRIPTION (provided by applicant): The proposed research is directed toward the development of new methods for quantitatively analyzing changes in protein expression in biological systems. The proposed developments will provide the means to analyze complex mixtures of proteins much more rapidly than is currently possible. Present day methodologies rely on the separation of protein mixtures into their individual components, followed by analysis for the identification of the separated proteins. The proposed developments will allow all proteins in a mixture to be identified simultaneously, thus providing a substantial reduction in analysis time and effort. Mixtures of proteins will be enzymatically digested, and the resulting mixture of proteolytic peptides will be separated by liquid chromatography and analyzed by high-resolution mass spectrometry. Proteins in the original mixture will be identified from their proteolytic fragments by using the accurate mass data that is produced. Presently, only a small proportion of peptides can be assigned to proteins by using accurate mass measurement. Most of the proposed effort will be directed into developing methods to increase the proportion of peptides that can be assigned to their parent proteins. A method called "mass defect labeling" is proposed as a way to increase the specificity of the assignment. Several novel reagents are proposed for mass defect labeling, and will be synthesized as part of the project. These reagents are not only useful for aiding protein identification, but also can be used to perform quantitative proteomics. Additional experiments will explore the use of endogenous labeling with a stable isotope in concert with the use of mass defect labels to achieve high specificity in protein identification. Using these methods together, calculations show that for the analysis of a prokaryotic proteome, up to 95% of the peptides that are measured can be assigned to the protein from which they derive. The success of the proposed developments will have great impact in biological research, drug discovery, and medicine. The proposed efforts will be carried out by both graduate and undergraduate students, and will be beneficial for their scientific development. The students involved in this research will be exposed to state-of-the-art, high-resolution mass spectrometry. This will provide society with well-trained scientists in this key technological area.
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T32 Predoctoral training grant in Glycosciences
  • 批准号:
    10410757
  • 项目类别:
  • 资助金额:
    $20.81万
  • 财政年份:
    2022
  • 负责人:
    I JONATHAN AMSTER
  • 依托单位:
T32 Predoctoral training grant in Glycosciences
  • 批准号:
    10650310
  • 项目类别:
  • 资助金额:
    $21.22万
  • 财政年份:
    2022
  • 负责人:
    I JONATHAN AMSTER
  • 依托单位:
An Automated Platform for the CE-MS Analysis of Glycosaminoglycans
  • 批准号:
    9753175
  • 项目类别:
  • 资助金额:
    $29.47万
  • 财政年份:
    2018
  • 负责人:
    I JONATHAN AMSTER
  • 依托单位:
An Automated Platform for the CE-MS Analysis of Glycosaminoglycans
  • 批准号:
    10005264
  • 项目类别:
  • 资助金额:
    $29.47万
  • 财政年份:
    2018
  • 负责人:
    I JONATHAN AMSTER
  • 依托单位:
海外基金