Determination of protein secondary structure using factor analysis of infrared spectra

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 known 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 its composition. By this method we obtain standard errors of prediction 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 proteins 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.

Conformation of wheat gluten proteins Comparison between functional and solution states as determined by infrared spectroscopy

“…The methods of Dousseau and Pezolet [18] and Lee et al [19] have been used to quantify the secondary structure content of gluten proteins in solution. The results obtained with the method of Dousseau and PCzolet [ 181 were, however, subjected to large prediction errors.…”

“…This discrepancy might be due either to the fact that infrared spectroscopy is more sensitive than CD for the determination of the p-sheet conformation since the characteristic bands due to this type of structure are well resolved, or to the higher protein concentration used for infrared measurements since gluten proteins have a high tendency for intermolecular association. It has not been possible to obtain quantitative results with low prediction errors on the conformation of functional gluten proteins since the methods of Dousseau and Pkzolzt [18] and Lee et al [19] have been developed for proteins in solution. Nevertheless, it is clear from Fig.…”

FT-IR spectroscopy of the major coat protein of M13 and Pf1 in the phage and reconstituted into phospholipid systems

“…In this method, the amide I region is compared with a reference set of 20 proteins (Lee et al, 1990). This gave an unusual result of over 100% a-helix for M l3 coat protein reconstituted in lipid bilayers.…”

β‐Sheet secondary structure of an LDL receptor domain from complement factor I by consensus structure predictions and spectroscopy

“…4a and 4c) showed a broad absorbance band at 1645 cm -1 and 1638 cm -1, respectively. Within this band, the second derivative spectra showed a single intense component at 1641 cm-1 in LDLr2 and 1637 cm-' in factor I. fl-Sheet bands commonly occur at 1634-1638 cm -1, with an anti-parallel 13-sheet component in the region of 1670-1680 cm -~ [23]. For LDLr2, the band at 1641 cm -1 was consistent with 13-sheet, while for factor I the bands at 1682 and 1637 cm -~ agreed with this assignment.…”

“…1). 13-Turns are characterised by bands close to 1670 cm -~, and loop regions by bands close to 1640 cm -l [23]. For LDLr2, strong bands were seen at 1673 cm -~ and 1641 cm -~ Wavenumber (cm -1) Fig.…”