Method for the estimation of the mean lorentzian bandwidth in spectra composed of an unknown number of highly overlapped bands

Infrared Difference Spectroscopy of Proteins: From Bands to Bonds

Infrared difference spectroscopy probes vibrational changes of proteins upon their perturbation. Compared with other spectroscopic methods, it stands out by its sensitivity to the protonation state, H-bonding, and the conformation of different groups in proteins, including the peptide backbone, amino acid side chains, internal water molecules, or cofactors. In particular, the detection of protonation and H-bonding changes in a time-resolved manner, not easily obtained by other techniques, is one of the most successful applications of IR difference spectroscopy. The present review deals with the use of perturbations designed to specifically change the protein between two (or more) functionally relevant states, a strategy often referred to as reaction-induced IR difference spectroscopy. In the first half of this contribution, I review the technique of reaction-induced IR difference spectroscopy of proteins, with special emphasis given to the preparation of suitable samples and their characterization, strategies for the perturbation of proteins, and methodologies for time-resolved measurements (from nanoseconds to minutes). The second half of this contribution focuses on the spectral interpretation. It starts by reviewing how changes in H-bonding, medium polarity, and vibrational coupling affect vibrational frequencies, intensities, and bandwidths. It is followed by band assignments, a crucial aspect mostly performed with the help of isotopic labeling and site-directed mutagenesis, and complemented by integration and interpretation of the results in the context of the studied protein, an aspect increasingly supported by spectral calculations. Selected examples from the literature, predominately but not exclusively from retinal proteins, are used to illustrate the topics covered in this review.

Plasticization of Cottonseed Protein/Polyvinyl Alcohol Blend Films

The use of waste plant protein obtained from underutilized and non-food-producing plants may be a promising strategy in the development of bioactive packaging. A series of blend films were prepared by casting from cottonseed protein (CP) and poly(vinyl alcohol) (PVA) and modified with different plasticizers. The morphology, structure, and crystallinity of each of the blend films were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction. CP and PVA were found to be compatible in the appropriate ratios, and the CP/PVA blend films were partially crystalline. We compared the effects that four plasticizers, i.e., glycerol, triethanolamine (TEA), ethylene glycol, and polyethylene glycol, had on the performance of the CP/PVA blend films. Plasticizers altered the degree of interaction between CP and PVA, which changed the secondary structure of the CP but had little effect on the crystallinity of CP/PVA blend films. Among the different plasticizers tested, TEA was the most efficient at improving the elongation at the break, tensile strength, and oxygen barrier properties of the CP/PVA blend films. Such CP/PVA blend films plasticized using TEA can, therefore, be considered emerging and promising plastics for potential applications in food packaging and flower planting applications.

Soy Protein Isolate and Glycerol Hydrogen Bonding Using Two-Dimensional Correlation (2D-COS) Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy

It is a trend to substitute bioplastics for petroleum-based plastics in food packaging. Glycerol-plasticized soy protein isolate (SPI) is promising as a replacement for traditional petroleum-based plastics. Hydrogen bonding (H-bonding) plays a key role in plasticization of SPI film. However, few publications are concerned with the interactions of SPI and glycerol at the molecular level. In this paper, attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy was applied to investigate the effect of H-bonding on the secondary structures of glycerol-plasticized SPI films and thus on the plasticization. An "S" profile of the H-bonding between SPI and glycerol with an abrupt jump in the glycerol range of 10-30% was achieved. For more in-depth investigation of the H-bonding, two-dimensional correlation spectroscopy (2D-COS) and perturbation-correlation moving-window two-dimensional (PCMW2D) analyses were applied to the amide I and II bands of SPI films spectra series. The conformation change sequences under the effect of H-bonding were revealed. When glycerol was involved, it entered into the β-sheet and the H-bonds of the SPI peptide backbone (C = O···H-N-) were replaced by the new H-bonds between SPI and glycerol (C = O···H-O-). The transformations of parallel β-sheet to β-turn in the range of 0-20% and anti-parallel β-sheet to β-turn in the range of 20-35% were obtained. In the 35-60% concentration range, the β-sheet was first changed to a transition state conformation, then together with the β-turn, to the random coil. The 2D-COS results clearly suggest that the conformations of SPI gradually change from the ordered to the less ordered and disordered, which significantly improve the plasticity of SPI film.

A MAP-based algorithm for spectroscopic semi-blind deconvolution

Spectroscopic data often suffer from common problems of bands overlapping and random noise. In this paper, we show that the issue of overlapping peaks can be considered as a maximum a posterior (MAP) problem and be solved by minimizing an object functional that includes a likelihood term and two prior terms. In the MAP framework, the likelihood probability density function (PDF) is constructed based on a spectral observation model, a robust Huber-Markov model is used as spectra prior PDF, and the kernel prior is described based on a parametric Gaussian function. Moreover, we describe an efficient optimization scheme that alternates between latent spectrum recovery and blur kernel estimation until convergence. The major novelty of the proposed algorithm is that it can estimate the kernel slit width and latent spectrum simultaneously. Comparative results with other deconvolution methods suggest that the proposed method can recover spectral structural details as well as suppress noise effectively.

The role and selection of the filter function in Fourier self-deconvolution revisited

Overlapped bands often appear in applications of infrared spectroscopy, for instance in the analysis of the amide I band of proteins. Fourier self-deconvolution (FSD) is a popular band-narrowing mathematical method, allowing for the resolution of overlapped bands. The filter function used in FSD plays a significant role in the factor by which the deconvolved bands are actually narrowed (the effective narrowing), as well as in the final signal-to-noise degradation induced by FSD. Moreover, the filter function determines, to a good extent, the band-shape of the deconvolved bands. For instance, the intensity of the harmful side-lobule oscillations that appear in over-deconvolution depends importantly on the filter function used. In the present paper we characterized the resulting band shape, effective narrowing, and signal-to-noise degradation in infra-, self-, and over-deconvolution conditions for several filter functions: Triangle, Bessel, Hanning, Gaussian, Sinc2, and Triangle2. We also introduced and characterized new filters based on the modification of the Blackmann filter. Our conclusion is that the Bessel filter (in infra-, self-, and mild over-deconvolution), the newly introduced BL3 filter (in self- and mild/moderate over-deconvolution), and the Gaussian filter (in moderate/strong over-deconvolution) are the most suitable filter functions to be used in FSD.

Secondary structure of food proteins by Fourier transform spectroscopy in the mid-infrared region

Fourier transform spectroscopy in the mid-infrared (400-5,000 cm(-1)) (FT-IR) is being recognized as a powerful tool for analyzing chemical composition of food, with special concern to molecular architecture of food proteins. Unlike other spectroscopic techniques, it provides high-quality spectra with very small amount of protein, in various environments irrespective of the molecular mass. The fraction of peptide bonds in alpha-helical, beta-pleated sheet, turns and aperiodic conformations can be accurately estimated by analysis of the amide I band (1,600-1,700 cm(-1)) in the mid-IR region. In addition, FT-IR measurement of secondary structure highlights the mechanism of protein aggregation and stability, making this technique of strategic importance in the food proteomic field. Examples of applications of FT-IR spectroscopy in the study of structural features of food proteins critical of nutritional and technological performance are discussed.