PREDICTIONS OF PROTEIN SECONDARY STRUCTURES USING FACTOR-ANALYSIS ON FOURIER-TRANSFORM INFRARED-SPECTRA - EFFECT OF FOURIER SELF-DECONVOLUTION OF THE AMIDE-I AND AMIDE-II BANDS

Fourier self-deconvolution (FSD) was performed on protein amide I and II Fourier transform infrared (FTIR) spectra to test if the resultant increased band shape variation would lead to improvements in protein s econdary structure prediction with our factor analysis based restricte d multiple regression (RMR) methods. FTIR spectra of 23 proteins disso lved in H2O were measured and normalized to a constant amide I peak ab sorbance. The deconvolved spectra were renormalized by area so that th e deconvolved spectra sets had the same area as before. Principal comp onent analysis of the deconvolved spectra sets was carried out, which was followed by a selective multiple linear regression (RMR) analysis of the principal component loadings with regard to the fractional comp onents (FC) of secondary structure. As compared to analyses based on t he original spectra set, helix and sheet predictions were not noticeab ly improved by FSD; but, if a very large number of component spectra ( 16) were retained in the pool to select which loadings to be used in t he RMR optimization, better predictions of turn and ''other'' resulted . The prediction quality varied depending on the deconvolution paramet ers used. (C) 1998 John Wiley & Sons, Inc.