Baumruk V, Pancoska P, Keiderling T A
Department of Chemistry, University of Illinois at Chicago, 60607-7061, USA.
J Mol Biol. 1996 Jun 21;259(4):774-91. doi: 10.1006/jmbi.1996.0357.
Vibrational circular dichroism (VCD) and Fourier transform IR (FTIR) methods for prediction of protein secondary structure are systematically compared using selective regression analysis. VCD and FTIR spectra over the amide I and II bands of 23 proteins dissolved in H2O were analyzed using the principal component method of factor analysis (PC/FA) and regression fits to fractional components (FC) of secondary structure. Predictive capability was determined by computing structures for proteins sequentially left out of the regression. All possible combinations of PC/FA spectral parameters (coefficients) were used to form a full set of restricted multiple regressions (RMR) of PC/FA coefficients with FC values, both independently for each spectral data set as well as for the VCD and FTIR sets grouped together and with similarly obtained electronic CD (ECD) data. The distribution of predictive error for a set of the best RMR relationships that use a given number of spectral coefficients was used to select the optimal prediction algorithm. Minimum predictive error resulted for a small subset (three to six) of spectral coefficients, which is consistent with our earlier findings using VCD measured for proteins in 2H2O and ECD data. Subtracting the average absorption spectrum from all the training set FTIR spectra before analysis yields more variance in the FTIR band shape and improves the predictive ability of the best PC/FA RMR to near that for the VCD. Both methods (FTIR and VCD) using data for proteins in H2O are somewhat better predictors than amide I' (in 2H2O) VCD alone and, for helix, worse than ECD alone. Combining FTIR and VCD data did not dramatically change the prediction results. Predictions are improved by combining both with ECD data, indicating that the improvement is due to using their very different structural sensitivities. The coupled H2O-based spectral analyses and the mixed amide I' + II VCD plus ECD analysis are comparable for the helix and sheet components, indicating that partial deuteration is not a major source of prediction error.
利用选择性回归分析系统地比较了振动圆二色性（VCD）和傅里叶变换红外（FTIR）预测蛋白质二级结构的方法。使用因子分析的主成分法（PC/FA）以及对二级结构分数成分（FC）的回归拟合，分析了溶解于H2O中的23种蛋白质在酰胺I和II谱带的VCD和FTIR光谱。通过计算依次从回归中剔除的蛋白质结构来确定预测能力。PC/FA光谱参数（系数）的所有可能组合用于形成PC/FA系数与FC值的一整套受限多元回归（RMR），分别针对每个光谱数据集以及将VCD和FTIR数据集组合在一起，并与类似获得的电子圆二色性（ECD）数据独立进行。使用给定数量光谱系数的一组最佳RMR关系的预测误差分布用于选择最佳预测算法。对于一小部分（三到六个）光谱系数，预测误差最小，这与我们早期使用在2H2O中测量的蛋白质的VCD和ECD数据的发现一致。在分析之前从所有训练集FTIR光谱中减去平均吸收光谱，可使FTIR谱带形状产生更多变化，并将最佳PC/FA RMR的预测能力提高到接近VCD的水平。使用H2O中蛋白质数据的两种方法（FTIR和VCD）在预测方面都比单独使用酰胺I'（在2H2O中）VCD稍好，对于螺旋结构，比单独使用ECD差。结合FTIR和VCD数据并没有显著改变预测结果。将两者与ECD数据结合可改善预测，表明这种改善是由于利用了它们非常不同的结构敏感性。基于耦合H2O的光谱分析以及混合酰胺I'+II VCD加ECD分析对于螺旋和片状成分具有可比性，表明部分氘代不是预测误差的主要来源。
