Fourier transform infrared spectroscopy (FTIR) can be used for conformational analysis of peptides in a wide range of environments. Measurements can be performed in aqueous solution, organic solvents, detergent micelles as well as in phospholipid membranes. Information on the secondary structure of peptides can be derived from the analysis of the strong amide I band. Orientation of secondary structural elements within a lipid bilayer matrix can be determined by means of polarized attenuated total reflectance-FTIR spectroscopy. Hydrogen-deuterium exchange can be monitored by the analysis of the amide II band. This review gives some example of peptide systems studied by FTIR spectroscopy. Studies on alamethicin and alpha-aminoisobutyric acid containing peptides have shown that FTIR spectroscopy is a sensitive tool for identifying 3(10)-helical structures. Changes in the structure of the magainins upon interaction with charged lipids were detected using FTIR spectroscopy. Tachyplesin is an example of a beta-sheet containing membrane active peptide. Polarized ir spectroscopy reveals that the antiparallel beta-sheet structures of tachyplesin are oriented parallel to the membrane surface. Synthesis of peptides corresponding to functionally/structurally important regions of large proteins is becoming increasingly popular. FTIR spectroscopy has been used to analyze the structure of synthetic peptides corresponding to the ion-selective pore of the voltage-gated potassium channel. In biomembrane systems these peptides adopt a highly helical structure. Under conditions, where these peptides are aggregated the presence of some intermolecular beta-sheet structure can also be detected.

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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.