Removal of spectral noise in the quantitation of protein structure through infrared band decomposition

Abstract

The underlying noise in the infrared spectra of proteins may introduce artifacts in the quantitation of proteins by curve-fitting of the amide I band. Smoothing methods are able to reduce the noise but can introduce alterations in band shape that affect the information contained in the spectrum. Three methods to remove noise—Savitzky-Golay, Fourier filtering, and maximum entropy—have been used to ascertain their influence on the quantitative information when applied to protein bands. Use of artificial curves shows that whereas Savitzky-Golay and Fourier smoothing are able to reduce the noise, they distort the band shape. Maximum entropy is more efficient in reducing the noise in artificial curves with added noise, and provided a narrowest bandwidth below 12 cm⁻¹, no band-shape distortion is obtained. Using the smoothing in natural spectra, the presence of spurious bands in the initial parameters coming from artifacts introduced by deconvolution or derivation is reduced. Moreover, the dispersion in the percentage area values in a series of similar spectra is also decreased below 2%, a value that discriminates the effect of ligand binding to proteins. The maximum entropy method is proposed as a tool to improve the quantification of protein structure by infrared spectroscopy. © 1997 John Wiley & Sons, Inc. Biospectroscopy 3: 469–475, 1997