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Multi-Dimensional Studies of Protein Folding

Multi-Dimensional Studies of Protein Folding
蛋白质折叠的多维研究
批准号:
9808635
负责人:
Maurice Eftink
金额:
$40.5万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-09-01 至 2002-08-31

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中文摘要
翻译
这项研究将集中在小的球状蛋白质的解折叠的热力学上,重点是收集多个扰动轴上的平衡解折叠数据(例如,温度、压力、变性剂浓度、pH),并对这些数据集进行全局非线性最小二乘法,以便对蛋白质解折叠的双态模型进行更严格的测试,以确定热力学参数的完整集合(例如,焓、熵、自由能、热容量和体积变化、扰动pKas和可能的更高阶参数,例如((V/(P,压缩性差))。 将使用组合的圆二色性/荧光计收集展开数据,同时监测两种类型的信号。 色氨酸类似物,包括5-羟基色氨酸和荧光色氨酸,将被纳入蛋白质中,以提供额外的位点特异性光谱探针用于监测展开。 待研究的蛋白质包括野生型葡萄球菌核酸酶(用作良好行为模型)、其一些突变体(包括一组电荷变化突变体)、全β蛋白、白细胞介素1-β和一些其他β型小球状蛋白。 除了这些热力学研究,将努力开发新的策略来解决和量化的人口中间状态展开平衡。 其中一种策略是快速冷冻/淬灭蛋白质(在不同的初始条件下),随后进行固态19 F-NMR以识别中间体的峰(化学交换因冷冻而停止)。 第二种策略将涉及在适度低温下使用毛细管电泳来分离平衡中的物种。 除了与理解蛋白质解折叠热力学相关的基本问题之外,研究人员能够描述蛋白质的稳定性仍然具有实际重要性,例如,当比较一组突变蛋白质时。 如何以及是否可以根据蛋白质的稳定性来解释数据取决于所假设的解折叠模型(例如,两个状态等)。 本研究的目的是测试所选蛋白质的两态模型的限制,并制定实验策略,以确定存在的平衡展开中间体。 通过探讨双态模型的局限性,希望能对如何解释蛋白质稳定性数据有所了解。
英文摘要
9808635 Eftink This research will focus on the thermodynamics of the unfolding of small, globular proteins, with emphasis on collecting equilibrium unfolding data over multiple perturbation axes (e.g., temperature, pressure, denaturant concentration, pH) and subjecting such data sets to global nonlinear least-squares in order to perform more rigorous tests of the two-state model for protein unfolding, to determine a full set of thermodynamic parameters (e.g., enthalpy, entropy, free energy, heat capacity, and volume changes, perturbed pKas and possibly higher order parameters such as the ((V/(P, the difference in compressibility). A combined circular dichroism/fluorometer will be used to collect unfolding data, with both types of signals being simultaneously monitored. Tryptophan analogues, including 5-hydroxytryptophan and the fluorotryptophans, will be incorporated into proteins to provide additional site-specific spectroscopic probes for monitoring unfolding. The proteins to be studied include wild type Staphylococcal nuclease (used as a well behaved model), some of its mutants ( including a set of charge change mutants), an all beta protein, interleukin 1-(, and a few other small globular proteins of the beta type. In addition to these thermodynamic studies, effort will be made to develop new strategies to resolve and quantitate the population of intermediate states in an unfolding equilibrium. One such strategy will involve rapid freeze/quenching of proteins (at various initial conditions), with subsequent solid-state 19F-nmr to identify peaks for an intermediate (chemical exchange being halted by the freezing). A second strategy will involve the use of capillary electrophoresis at moderately low temperature to separate species in an equilibrium. In addition to the fundamental issues related to understanding the thermodynamics of protein unfolding, it continues to be of practical importance for researchers to be able to describe the stability of proteins, for example, when compar ing a set of mutant proteins. How and whether data can be interpreted in terms of the stability of a protein depends on the unfolding model that is assumed (e.g., two-state, etc). The goal of this research is to test the limits of the two-state model for selected proteins and to develop experimental strategies for determining the presence of an equilibrium unfolding intermediate. By exploring the limitations of the two-state model, it is hoped to achieve some understanding as to how to interpret protein stability data.
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Assessment of Success of the Mississippi AGEM Program: Charting the Direction for the Future
  • 批准号:
    1111227
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.0万
  • 财政年份:
    2011
  • 负责人:
    Maurice Eftink
  • 依托单位:
AGEP: Alliance for Graduate Education in Mississippi
  • 批准号:
    0450362
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $502.68万
  • 财政年份:
    2004
  • 负责人:
    Maurice Eftink
  • 依托单位:
Alliance for Graduate Education in Mississippi
  • 批准号:
    9978889
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $250.0万
  • 财政年份:
    1999
  • 负责人:
    Maurice Eftink
  • 依托单位:
Fluorescence and Thermodynamics Studies with Proteins
  • 批准号:
    9407167
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $52.93万
  • 财政年份:
    1994
  • 负责人:
    Maurice Eftink
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis