蛋白质三级结构
超空间
圆二色性
谱线
数学
化学
结晶学
生物系统
物理
纯数学
生物
天文
生物化学
作者
S.Yu. Venyaminov,Konstantin S. Vassilenko
标识
DOI:10.1006/abio.1994.1470
摘要
Fifty-three circular dichroism (CD) spectra consisting of the spectra of 46 native proteins, 3 denatured proteins, and one oligopeptide (the spectra of two denatured proteins and oligopeptide were taken at two different temperatures) were investigated in order to examine the correlation between the shape of the CD spectrum and the tertiary structure class of the protein. Five classes were considered-all −α, all −β, α + β, α/β, and denatured proteins. Spectra from 190 to 236 nm with 2 nm interval were described as points in 24-dimensional hyperspace, where coordinates were values of ellipticities at fixed wavelengths. This allows the spectra to be treated as patterns and subsequently analyzed using pattern recognition algorithms. Cluster analysis, which does not need predefined information about protein structure, divides spectra into several compact groups or clusters with good correlation with tertiary structure class. To visualize these results, orthogonalization procedures were imposed on the original data set in 24-dimensional space. The new 3-dimensional coordinate system demonstrated well-separated all-β class and denatured proteins. Regions corresponding to all −α and especially α + β and α/β proteins were not as well resolved. The following approach was then applied to the original data set to obtain an objective mathematical algorithm for the determination of a protein′s tertiary structure class from its CD spectrum. Regions in 24-dimensional hyperspace corresponding to all of the tertiary structure classes were found by calculating the decision functions, or equations of hyperplanes, which separate groups of spectral patterns of different classes. The class representing the region which involves the pattern of a protein spectrum can be interpreted as a tertiary structure class of this protein. The accuracy of the method was checked by removing one of the proteins from the training set, finding all the decision functions, and determinating the class of the excluded protein. This test gives 100% accuracy for all −α, α/β, and denatured proteins; 85% for α + β and 75% for all −β proteins.
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