A Study of Urea-dependent Denaturation of β-Lactoglobulin by Principal Component Analysis and Two-dimensional Correlation Spectroscopy

2009 ◽  
Vol 113 (2) ◽  
pp. 559-566 ◽  
Author(s):  
Bogusława Czarnik-Matusewicz ◽  
Seung Bin Kim ◽  
Young Mee Jung
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Correlation Spectroscopy ◽  
Two Dimensional ◽  
Β Lactoglobulin

Infrared Two-Dimensional Correlation and Principal Component Analyses Applied to β-Lactoglobulin Aggregation in Water—Ethanol Solution

2002 ◽  
Vol 56 (9) ◽  
pp. 1180-1185 ◽  
Author(s):  
P. Robert ◽  
L. Lavenant ◽  
D. Renard
Keyword(s):  
Principal Component Analysis ◽  
Secondary Structure ◽  
Water Solution ◽  
Principal Component ◽  
Component Analysis ◽  
Ethanol Solution ◽  
Correlation Spectroscopy ◽  
Two Dimensional ◽  
Sequence Of Events ◽  
Β Lactoglobulin

Changes of the secondary structure of β-lactoglobulin in water–ethanol solutions were studied using infrared spectroscopy. The efficiency of both principal component analysis and two-dimensional correlation spectroscopy in avoiding spectral subtraction of water was evaluated. The kinetic curves assessed from the scores of the first principal component indicated that changes were more pronounced in 50% ethanol solution than in 5% ethanol–water solution. The spectral patterns derived from the eigenvectors made it possible to characterize changes in the secondary structure of the protein. While aggregation was obtained in 50% ethanol solution, α-helices were formed at the detriment of turns in 5% ethanol solution. The two-dimensional correlation spectroscopy provided information on the sequence of events that occurred by adding ethanol to aqueous solutions of β-lactoglobulin. In 5% ethanol solution, the disappearance of turns preceded the formation of α-helices. Moreover, a small amount of aggregates were depicted at the end of the process. Aggregation of the protein was the main event observed in 50% ethanol–water solution. This event was preceded by the disappearance of α-helices. Application of both principal component analysis and two-dimensional correlation spectroscopy to spectra recorded in H2O made it possible to detect small changes not observed on second derivative spectra collected in D2O.

scholarly journals New Approach to Generalized Two-Dimensional Correlation Spectroscopy. 1: Combination of Principal Component Analysis and Two-Dimensional Correlation Spectroscopy

2002 ◽  
Vol 56 (12) ◽  
pp. 1562-1567 ◽  
Author(s):  
Young Mee Jung ◽  
Hyeon Suk Shin ◽  
Seung Bin Kim ◽  
Isao Noda
Keyword(s):  
Principal Component Analysis ◽  
Correlation Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Correlation Spectroscopy ◽  
Data Matrix ◽  
Two Dimensional ◽  
Noise Component ◽  
Reconstructed Data ◽  
2D Correlation Analysis

The direct combination of chemometrics and two-dimensional (2D) correlation spectroscopy is considered. The use of a reconstructed data matrix based on the significant scores and loading vectors obtained from the principal component analysis (PCA) of raw spectral data is proposed as a method to improve the data quality for 2D correlation analysis. The synthetic noisy spectra were analyzed to explore the novel possibility of the use of PCA-reconstructed spectra, which are highly noise suppressed. 2D correlation analysis of this reconstructed data matrix, instead of the raw data matrix, can significantly reduce the contribution of the noise component to the resulting 2D correlation spectra.

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