QUANTITATIVE-ANALYSIS OF VIBRATIONAL CIRCULAR-DICHROISM SPECTRA OF PROTEINS - PROBLEMS AND PERSPECTIVES

被引:33
作者
PANCOSKA, P [1 ]
BITTO, E [1 ]
JANOTA, V [1 ]
KEIDERLING, TA [1 ]
机构
[1] UNIV ILLINOIS, DEPT CHEM, CHICAGO, IL 60607 USA
来源
FARADAY DISCUSSIONS | 1994年 / 99卷
关键词
D O I
10.1039/fd9949900287
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Experimental and computational aspects of the quantitative analysis of vibrational circular dichroism (VCD) of proteins are discussed. Experimentally, the effect of spectral resolution, sample concentration, cell selection and spectral normalization effects are considered. The influence of random intensity variations on the results of quantitative analysis of amide I' VCD are shown to be minor up to a 15% variation in spectral intensity. A computational algorithm, based on factor analysis of the spectra and multiple linear regression calculation of fractions of secondary structures (FC), was designed to analyse quantitatively the details of the VCD spectra-structure relationship It also enabled the results of VCD measured independently for the amide I' and amide II regions to be combined. Our study is based primarily on the optimization of the calculation to predict FC values for proteins not included in the reference data set used for regression. The best prediction is obtained with the function using only part of the observable independent VCD spectral components. Inclusion of all components actually reduces the prediction accuracy of the analysis. Spectroscopic reasons for such behaviour and the consequences of the interdependence of the crystallographic FC values on the spectra-structure analysis are discussed. Finally, the possibility of utilizing VCD spectra to obtain quantitative structural information about the protein beyond the conventional secondary structure composition is explored. A matrix descriptor of super-secondary structure features for proteins is designed, and preliminary results for prediction of this descriptor from amide I' VCD spectra are presented. These latter calculations use a novel design of the back-propagation neural network.
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页码:287 / 310
页数:24
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