DISTANCE DISTRIBUTIONS FROM ANALYSIS OF DQC ESR DATA USING REGULARIZATION METH

使用正则化方法分析 DQC ESR 数据的距离分布

基本信息

  • 批准号:
    7723905
  • 负责人:
  • 金额:
    $ 0.16万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-09-01 至 2009-08-31
  • 项目状态:
    已结题

项目摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Distance distributions provide valuable structural information that could help to provide insight into the static structure of membrane proteins and conformationally heterogeneous water soluble proteins as well as fluctuations in these structures. Another important aspect of determining distance distributions is the case of more than two spins. For example, in fully-labeled KcsA channels there are four spin-labels, with two possible distances due to symmetry considerations. The two distances and the stoichiometry could be used as additional parameters that could help to determine distance distributions with a high degree of confidence. These distributions could then be used to find the change in distances upon channel gating when only a fraction of the channels is in the open state. T4-Lysozyme served as testing ground for determining methods useful for solving the inverse problem of finding the distributions from the DQC-ESR spectra. High-quality data were obtained on T4-L 65/135 and 61/135 mutants at 17GHz with use of deuterated solvents. The DQC signals with excellent SNR were recorded on a time-scale of 6s and analyzed by the Tikhonov regularization method. The shapes of the distributions in this work are consistent with the distributions found in our previous study of T4-L by trial and error. In the theoretical part of this work, regularization methods were shown to outperform SVD methods. A direct conversion of DQC-ESR signals into distance distributions by the Tikhonov regularization method was facilitated by obtaining the regularization parameter from the L-curve criterion.
这个子项目是众多研究子项目之一

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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YUN-WEI CHIANG其他文献

YUN-WEI CHIANG的其他文献

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{{ truncateString('YUN-WEI CHIANG', 18)}}的其他基金

USE OF QMR ALGORITHM TO CALCULATE VERY SLOW-MOTIONAL SPECTRA
使用 QMR 算法计算非常慢运动的光谱
  • 批准号:
    8363977
  • 财政年份:
    2011
  • 资助金额:
    $ 0.16万
  • 项目类别:
DISTANCE DISTRIBUTIONS FROM ANALYSIS OF DQC ESR DATA USING REGULARIZATION METH
使用正则化方法分析 DQC ESR 数据的距离分布
  • 批准号:
    8363954
  • 财政年份:
    2011
  • 资助金额:
    $ 0.16万
  • 项目类别:
DISTANCE DISTRIBUTIONS FROM ANALYSIS OF DQC ESR DATA USING REGULARIZATION METH
使用正则化方法分析 DQC ESR 数据的距离分布
  • 批准号:
    8172083
  • 财政年份:
    2010
  • 资助金额:
    $ 0.16万
  • 项目类别:
USE OF QMR ALGORITHM TO CALCULATE VERY SLOW-MOTIONAL SPECTRA
使用 QMR 算法计算非常慢运动的光谱
  • 批准号:
    8172118
  • 财政年份:
    2010
  • 资助金额:
    $ 0.16万
  • 项目类别:
DISTANCE DISTRIBUTIONS FROM ANALYSIS OF DQC ESR DATA USING REGULARIZATION METH
使用正则化方法分析 DQC ESR 数据的距离分布
  • 批准号:
    7956600
  • 财政年份:
    2009
  • 资助金额:
    $ 0.16万
  • 项目类别:
USE OF QMR ALGORITHM TO CALCULATE VERY SLOW-MOTIONAL SPECTRA
使用 QMR 算法计算非常慢运动的光谱
  • 批准号:
    7956636
  • 财政年份:
    2009
  • 资助金额:
    $ 0.16万
  • 项目类别:
USE OF QMR ALGORITHM TO CALCULATE VERY SLOW-MOTIONAL SPECTRA
使用 QMR 算法计算非常慢运动的光谱
  • 批准号:
    7723943
  • 财政年份:
    2008
  • 资助金额:
    $ 0.16万
  • 项目类别:
DISTANCE DISTRIBUTIONS FROM ANALYSIS OF DQC ESR DATA USING REGULARIZATION METH
使用正则化方法分析 DQC ESR 数据的距离分布
  • 批准号:
    7602617
  • 财政年份:
    2007
  • 资助金额:
    $ 0.16万
  • 项目类别:
USE OF QMR ALGORITHM TO CALCULATE VERY SLOW-MOTIONAL SPECTRA
使用 QMR 算法计算非常慢运动的光谱
  • 批准号:
    7602665
  • 财政年份:
    2007
  • 资助金额:
    $ 0.16万
  • 项目类别:
USE OF QMR ALGORITHM TO CALCULATE VERY SLOW-MOTIONAL SPECTRA
使用 QMR 算法计算非常慢运动的光谱
  • 批准号:
    7420511
  • 财政年份:
    2006
  • 资助金额:
    $ 0.16万
  • 项目类别:

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