Development Of Advanced Chemometric Methods For The Analysis Of Deep Uv Resonance Raman Spectra Of Proteins

Development of Advanced Chemometric Methods for the Analysis of Deep-UV Resonance Raman Spectra of Proteins

Ultra violet resonance Raman (UVRR) is a powerful spectroscopic technique for determining the secondary structural content of proteins in solution. However, the analyses of UVRR spectra can be problematic due to the difficulty of determining the pure secondary structure Raman spectra. The use of multi-excitation datasets can help to alleviate the difficulty in determining the pure secondary structure Raman spectra, but due to increasing spectral resolution as excitation wavelength increases, multi-excitation datasets are notoriously difficult to align spectral features. In addition, the subtraction of the water band can be difficult when relying on an internal intensity standard. To address these difficulties we demonstrate the use of a series of chemometric methods. To determine the pure secondary structure Raman spectra, we demonstrate the use of multivariate curve resolution using the alternating least squares algorithm (MCRALS) with a multi-excitation data set. To alleviate mis-alignment in multi-excitation data, we demonstrate the use of correlation optimized warping (COW). We also propose a new water band subtraction method which will reliably determine the water band concentration and remove it, without an over subtraction. Finally, we demonstrate the use of parallel factor analysis (PARAFAC) for the characterization of the behavior of the flavonoid quercetin in solution with the protein bovine serum albumin.

Dissertation Abstracts International

Development of Advanced Chemometric Methods for Analysis of Deep-ultraviolet Resonance Raman and Circular Dichroism Spectroscopic Data for Protein Secondary Structure Determination

Determination of protein secondary structure ([alpha]-helical, [beta]-sheet, and disordered motifs) has become an area of great importance in biochemistry and biophysics as protein secondary structure is directly related to protein function and protein related diseases. While NMR and x-ray crystallography can predict placement of each atom in proteins to within an angstrom, optical methods (CD, Raman, IR) are the preferred techniques for rapid evaluation of protein secondary structure content. Such techniques require calibration data to predict unknown protein secondary structure content where accuracy may be improved with the application of multivariate analysis. We compare protein secondary structure predictions obtained from multivariate analysis of ultraviolet resonance Raman (UVRR) and circular dichroism (CD) spectroscopic data using classical and partial least squares, and multivariate curve resolution-alternating least squares is made. Based on this analysis, the suggested best approach to rapid and accurate secondary structure determination is a combination of both CD and UVRR spectroscopy.