Proteomic Analysis Using FTICR/MS

使用 FTICR/MS 进行蛋白质组分析

基本信息

  • 批准号:
    6801038
  • 负责人:
  • 金额:
    $ 25.76万
  • 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
  • 起止时间:
    2003-09-22 至 2007-07-31
  • 项目状态:
    已结题

项目摘要

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.
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。拟议的发展将提供比目前可能更快地分析蛋白质复杂混合物的方法。目前的方法学依赖于将蛋白质混合物分离成其单独的组分,然后分析以鉴定分离的蛋白质。拟议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工作量。蛋白质的混合物将被酶消化,并且所得的蛋白水解肽的混合物将通过液相色谱法分离并通过高分辨率质谱法分析。通过使用产生的准确质量数据,从蛋白水解片段中鉴定原始混合物中的蛋白质。目前,只有一小部分的肽可以通过使用精确的质量测量分配给蛋白质。大多数拟议的努力将致力于开发方法,以增加可以分配给其亲本蛋白质的肽的比例。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。提出了几种新的试剂用于质量缺陷标记,并将作为该项目的一部分合成。这些试剂不仅可用于辅助蛋白质鉴定,而且可用于进行定量蛋白质组学。另外的实验将探索使用内源性标记与稳定同位素的音乐会使用质量缺陷标签,以实现高特异性的蛋白质鉴定。使用这些方法一起,计算表明,对于原核蛋白质组的分析,高达95%的肽可以被分配到它们所来源的蛋白质。这些发展的成功将对生物学研究、药物发现和医学产生重大影响。研究生和本科生都将开展这项工作,这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仪。这将为社会提供这一关键技术领域训练有素的科学家。

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(1)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

I JONATHAN AMSTER其他文献

I JONATHAN AMSTER的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('I JONATHAN AMSTER', 18)}}的其他基金

T32 Predoctoral training grant in Glycosciences
T32 糖科学博士前培训补助金
  • 批准号:
    10410757
  • 财政年份:
    2022
  • 资助金额:
    $ 25.76万
  • 项目类别:
T32 Predoctoral training grant in Glycosciences
T32 糖科学博士前培训补助金
  • 批准号:
    10650310
  • 财政年份:
    2022
  • 资助金额:
    $ 25.76万
  • 项目类别:
An Automated Platform for the CE-MS Analysis of Glycosaminoglycans
用于糖胺聚糖 CE-MS 分析的自动化平台
  • 批准号:
    9753175
  • 财政年份:
    2018
  • 资助金额:
    $ 25.76万
  • 项目类别:
An Automated Platform for the CE-MS Analysis of Glycosaminoglycans
用于糖胺聚糖 CE-MS 分析的自动化平台
  • 批准号:
    10005264
  • 财政年份:
    2018
  • 资助金额:
    $ 25.76万
  • 项目类别:
Rapid Sequencing of Sulfated Glycans By CE-MS/MS
通过 CE-MS/MS 对硫酸化聚糖进行快速测序
  • 批准号:
    9336350
  • 财政年份:
    2016
  • 资助金额:
    $ 25.76万
  • 项目类别:
Glycoscience Training Program
糖科学培训计划
  • 批准号:
    10192521
  • 财政年份:
    2014
  • 资助金额:
    $ 25.76万
  • 项目类别:
Purchase of a Thermo Fisher Scientific LTQ Orbitrap XL Mass Spectrometer
购买 Thermo Fisher Scientific LTQ Orbitrap XL 质谱仪
  • 批准号:
    7838622
  • 财政年份:
    2011
  • 资助金额:
    $ 25.76万
  • 项目类别:
Proteomic Analysis Using FTICR/MS
使用 FTICR/MS 进行蛋白质组分析
  • 批准号:
    6936468
  • 财政年份:
    2003
  • 资助金额:
    $ 25.76万
  • 项目类别:
Proteomic Analysis Using FTICR/MS
使用 FTICR/MS 进行蛋白质组分析
  • 批准号:
    6719692
  • 财政年份:
    2003
  • 资助金额:
    $ 25.76万
  • 项目类别:

相似海外基金

PFI-TT: Chemical Synthesis of a Natural Product Family of Compounds for Tick-Targeted Prevention and Control
PFI-TT:用于蜱目标预防和控制的天然产物化合物家族的化学合成
  • 批准号:
    2345757
  • 财政年份:
    2024
  • 资助金额:
    $ 25.76万
  • 项目类别:
    Standard Grant
Reactions without walls: Droplet Reaction Module for rapid chemical synthesis (DReaM)
无壁反应:用于快速化学合成的液滴反应模块 (DReaM)
  • 批准号:
    2896295
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
    Studentship
Chemical synthesis and exploration of concerted optical properties of anisotropic three-dimensional quantum dot superlattices
各向异性三维量子点超晶格的化学合成及协同光学性质探索
  • 批准号:
    23H01802
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
domino4chem: Semi-biological Domino Catalysis for Solar Chemical Synthesis
domino4chem:用于太阳能化学合成的半生物多米诺催化
  • 批准号:
    EP/X030563/1
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
    Research Grant
Chemical Synthesis and Biological Application of Carbohydrates and Glycoconjugates
碳水化合物和糖复合物的化学合成和生物应用
  • 批准号:
    10552167
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
Deconvolution of Galbulimima bark pharmacology through chemical synthesis and target assignment
通过化学合成和目标分配对 Galbulimima 树皮药理学进行解卷积
  • 批准号:
    10682293
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
Microfluidic Systems to Enable Enzyme Engineering for Chemical Synthesis
微流体系统使酶工程能够用于化学合成
  • 批准号:
    10715356
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
CAREER: Merging Graph Theory and Automation for Chemical Synthesis
职业:将图论与化学合成自动化相结合
  • 批准号:
    2236215
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
    Continuing Grant
ChemDecEpi: A Chemical Synthesis Approach towards Decoding the Epitranscriptome
ChemDecEpi:解码表观转录组的化学合成方法
  • 批准号:
    EP/X032043/1
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
    Research Grant
Next Generation Photocatalysis for Chemical Synthesis and Manufacture
用于化学合成和制造的下一代光催化
  • 批准号:
    FT220100345
  • 财政年份:
    2023
  • 资助金额:
    $ 25.76万
  • 项目类别:
    ARC Future Fellowships
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了