van Stokkum I H, Spoelder H J, Bloemendal M, van Grondelle R, Groen F C
Faculty of Physics and Astronomy, Free University, Amsterdam, The Netherlands.
Anal Biochem. 1990 Nov 15;191(1):110-8. doi: 10.1016/0003-2697(90)90396-q.
The estimation of protein secondary structure from circular dichroism spectra is described by a multivariate linear model with noise (Gauss-Markoff model). With this formalism the adequacy of the linear model is investigated, paying special attention to the estimation of the error in the secondary structure estimates. It is shown that the linear model is only adequate for the alpha-helix class. Since the failure of the linear model is most likely due to nonlinear effects, a locally linearized model is introduced. This model is combined with the selection of the estimate whose fractions of secondary structure summate to approximately one. Comparing the estimation from the CD spectra with the X-ray data (by using the data set of W.C. Johnson Jr., 1988, Annu. Rev. Biophys. Chem. 17, 145-166) the root mean square residuals are 0.09 (alpha-helix), 0.12 (anti-parallel beta-sheet), 0.08 (parallel beta-sheet), 0.07 (beta-turn), and 0.09 (other). These residuals are somewhat larger than the errors estimated from the locally linearized model. In addition to alpha-helix, in this model the beta-turn and "other" class are estimated adequately. But the estimation of the antiparallel and parallel beta-sheet class remains unsatisfactory. We compared the linear model and the locally linearized model with two other methods (S. W. Provencher and J. Glöckner, 1981, Biochemistry 20, 1085-1094; P. Manavalan and W. C. Johnson Jr., 1988, Anal. Biochem. 167, 76-85). The locally linearized model and the Provencher and Glöckner method provided the smallest residuals. However, an advantage of the locally linearized model is the estimation of the error in the secondary structure estimates.
通过带有噪声的多元线性模型(高斯 - 马尔可夫模型)来描述从圆二色光谱估计蛋白质二级结构的方法。基于这种形式体系,对线性模型的适用性进行了研究,特别关注二级结构估计中误差的估计。结果表明,线性模型仅适用于α - 螺旋类别。由于线性模型的失效很可能是由于非线性效应,因此引入了局部线性化模型。该模型与二级结构分数总和约为1的估计值选择相结合。将圆二色光谱的估计结果与X射线数据进行比较(使用W.C. Johnson Jr. 1988年《生物物理化学年度评论》第17卷,第145 - 166页中的数据集),均方根残差分别为0.09(α - 螺旋)、0.12(反平行β - 折叠)、0.08(平行β - 折叠)、0.07(β - 转角)和0.09(其他)。这些残差略大于从局部线性化模型估计的误差。除了α - 螺旋外,该模型对β - 转角和“其他”类别估计得较为充分。但对反平行和平行β - 折叠类别的估计仍不令人满意。我们将线性模型和局部线性化模型与另外两种方法进行了比较(S.W. Provencher和J. Glöckner,1981年,《生物化学》第20卷,第1085 - 1094页;P. Manavalan和W.C. Johnson Jr.,1988年,《分析生物化学》第167卷,第76 - 85页)。局部线性化模型和Provencher和Glöckner方法提供了最小的残差。然而,局部线性化模型的一个优点是能够估计二级结构估计中的误差。