Secondary structure determination of proteins in aqueous solution by infrared spectroscopy: a comparison of multivariate data analysis methods

The accuracy of the secondary structure prediction from an infrared spectra data base of 39 proteins with known X-ray structure was investigated by different methods of multivariate data analysis. The best agreements with the secondary structure determined by X-ray crystallography are obtained if both the amide I and amide II bands are used for calibration. With optimized parameters the methods singular value decomposition, partial least squares, and ridge regression yield similar results. As judged by the standard error of prediction, the secondary structure elements helix and beta-sheet can be predicted with the highest accuracy. Small data sets of less than 20 protein spectra, which exhibit the variance in secondary structure content of the whole set, can pretend an increased prediction accuracy only if column cross-validation is used as reference; however, with these calibration sets the average secondary structure prediction of all 39 proteins is debased. The hydrogen-bonded turns or bridges are predicted with higher accuracy than the assigned secondary structure types helix and beta-sheet.