The equilibrium unfolding of MerP characterized by multivariate analysis of 2D NMR data

被引:5
|
作者
Berglund, A
Brorsson, AC
Jonsson, BH
Sethson, I [1 ]
机构
[1] Umea Univ, Dept Chem, Umea, Sweden
[2] Umea Univ, S-90187 Umea, Sweden
[3] Linkoping Univ, IFM, SE-58183 Linkoping, Sweden
关键词
multivariate NMR data analysis; protein folding; PCA; PLS; GuHCl;
D O I
10.1016/j.jmr.2004.09.010
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A general problem when analysing NMR spectra that reflect variations in the environment of target molecules is that different resonances are affected to various extents. Often a few resonances that display the largest frequency changes are selected as probes to reflect the examined variation, especially in the case, where the NMR spectra contain numerous resonances. Such a selection is dependent on more or less intuitive judgements and relying on the observed spectral variation being primarily caused by changes in the NMR sample. Second, recording changes observed for a few (albeit significant) resonances is inevitably accompanied by not using all available information in the analysis. Likewise, the commonly used chemical shift mapping (CSM) [Biochemistry 39 (2000) 26, Biochemistry 39 (2000) 12595] constitutes a loss of information since the total variation in the data is not retained in the projection into this single variable. Here, we describe a method for subjecting 2D NMR time-domain data to multivariate analysis and illustrate it with an analysis of multiple NNIR experiments recorded at various folding conditions for the protein MerP. The calculated principal components provide an unbiased model of variations in the NNIR spectra and they can consequently be processed as NMR data, and all the changes as reflected in the principal components are thereby made available for visual inspection in one single NMR spectrum. This approach is much less laborious than consideration of large numbers of individual spectra, and it greatly increases the interpretative power of the analysis. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:24 / 30
页数:7
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