Pancoska P, Bitto E, Janota V, Keiderling T A
Department of Chemical Physics, Charles University Prague, Czech Republic.
Faraday Discuss. 1994(99):287-310. doi: 10.1039/fd9949900287.
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.
本文讨论了蛋白质振动圆二色性（VCD）定量分析的实验和计算方面。在实验上，考虑了光谱分辨率、样品浓度、样品池选择和光谱归一化的影响。结果表明，在光谱强度变化高达15%时，随机强度变化对酰胺I' VCD定量分析结果的影响较小。设计了一种基于光谱因子分析和二级结构分数（FC）多元线性回归计算的算法，用于定量分析VCD光谱与结构关系的细节。该算法还能够将酰胺I'和酰胺II区域独立测量的VCD结果进行合并。我们的研究主要基于计算的优化，以预测回归参考数据集中未包含的蛋白质的FC值。仅使用部分可观测的独立VCD光谱分量的函数可获得最佳预测结果。实际上，包含所有分量会降低分析的预测准确性。讨论了这种行为的光谱学原因以及晶体学FC值相互依赖对光谱-结构分析的影响。最后，探讨了利用VCD光谱获取超出传统二级结构组成的蛋白质定量结构信息的可能性。设计了一种蛋白质超二级结构特征的矩阵描述符，并给出了从酰胺I' VCD光谱预测该描述符的初步结果。后一种计算使用了反向传播神经网络的新颖设计。
