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蛋白质二级结构片段的新型矩阵描述符:基于圆二色光谱的可预测性证明

Novel matrix descriptor for secondary structure segments in proteins: demonstration of predictability from circular dichroism spectra.

作者信息

Pancoska P, Janota V, Keiderling T A

机构信息

Department of Chemistry, University of Illinois at Chicago, 845 West Taylor Street, M/C 111, Chicago, Illinois, 60607-7061, USA.

出版信息

Anal Biochem. 1999 Feb 1;267(1):72-83. doi: 10.1006/abio.1998.2960.

Abstract

An extension to standard protein secondary structure predictions using optical spectra that encompasses the number and average lengths of segments of uniform secondary structure in the sequence is demonstrated. The connectivity and numbers of segments can be described by a matrix descriptor [sij] (i, j representing segment types such as helix and beta-sheet strands). Independent knowledge of the fractional concentration of each secondary structure type and of the total number of residues in the protein then with [sij] yields the average segment length of each type. The physical background for prediction of this extended structural descriptor from spectral data is summarized, rules for its generation from reference X-ray structures are defined, and formal variants of its form are discussed. Using a novel neural network approach to analyze a training set of electronic circular dichroism (ECD) and vibrational circular dichroism (VCD) spectra for 23 proteins, matrix descriptors encompassing helix, sheet, and other forms are predicted. The results show that the matrix descriptor can be predicted to an accuracy comparable to that of conventionally predicted average fractional secondary structures. In this respect the ECD predictions of [sij] were significantly more accurate than the VCD ones, which may result from the longer range length dependence of the ECD bandshape and intensity. Summary results for a parallel analysis using Fourier transform infrared spectra indicate somewhat lower reliability than those for VCD.

摘要

本文展示了一种对标准蛋白质二级结构预测的扩展方法,该方法利用光谱来涵盖序列中均匀二级结构片段的数量和平均长度。片段的连通性和数量可以用矩阵描述符[sij]来描述(i、j代表片段类型,如螺旋和β折叠链)。然后,结合每种二级结构类型的分数浓度以及蛋白质中残基总数的独立知识,再加上[sij],就可以得出每种类型的平均片段长度。总结了从光谱数据预测这种扩展结构描述符的物理背景,定义了从参考X射线结构生成它的规则,并讨论了其形式的形式变体。使用一种新颖的神经网络方法分析了23种蛋白质的电子圆二色性(ECD)和振动圆二色性(VCD)光谱的训练集,预测了包含螺旋、折叠和其他形式的矩阵描述符。结果表明,矩阵描述符的预测精度与传统预测的平均分数二级结构相当。在这方面,[sij]的ECD预测比VCD预测明显更准确,这可能是由于ECD谱带形状和强度对更长范围长度的依赖性。使用傅里叶变换红外光谱进行平行分析的总结结果表明,其可靠性略低于VCD分析的结果。

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