Determination of protein secondary structure using factor analysis of infrared spectra

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Abstract
A method is presented for determining the secondary structural composition of a protein in aqueous solution from its infrared spectrum. A factor analysis approach is used to analyze the infrared spectra of 18 proteins whose crystal structures are know from X-ray studies. Factor analysis followed by multiple linear regression identifies those eigenspectra that correlate with the variation in properties described by the calibration set. The properties of interest in this study are %-.alpha.-helix, %-.beta.-sheet, and % turns. In the analysis of an unknown, the factor loadings required to reproduce its spectrum are substituted in the regression equation for each property to predict its secondary structural composition. The accuracy of the method was determined by removing each standard, in turn, from the calibration set and using a calibration set generated from the remainder to predict it composition. By this method we obtained standard errors of predictions of 3.9% for .alpha.-helix, 8.3% for .beta.-sheet, and 6.6% for turns. The method may also be applied to the spectra of protein in 2H2O. The method has important advantages over those currently in use for the quantitative analysis of the infrared spectra of proteins. Manipulation of the spectrum is kept to a minimum, no curve-fitting is necessary, and the several amide I band components need not be assigned.