PubMed · 1246596
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J B Bates. 1976-01-09. Fourier transform infrared spectroscopy.. https://doi.org/10.1126/science.1246596
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Reversible phosphorylation of serine, threonine and tyrosine residues in proteins is one of the key events in signal transduction. To understand the process of signal transduction on a molecular level, it is imperative to identify phosphorylation sites in proteins. In this review, we offer an overview of the different methods/technologies currently available to identify protein phosphorylation sites.
Principal component analysis (PCA) is a ubiquitous method of multivariate statistics that focuses on the eigenvalues lambda and eigenvectors of the sample covariance matrix of a data set. We consider p, N-dimensional data vectors xi drawn from a distribution with covariance matrix C. We use the replica method to evaluate the expected eigenvalue distribution rho(lambda) as N--> infinity with p=alphaN for some fixed alpha. In contrast to existing studies we consider the case where C contains a number of symmetry-breaking directions, so that the sample data set contains some definite structure. Explicitly we set C=sigma2I+sigma(2)Sigma(S)(m=1)A(m)B(m)B(T)(m), with A(m)>0 for all m. We find that the bulk of the eigenvalues are distributed as for the case when the elements of xi are independent and identically distributed. With increasing alpha a series of phase transitions are observed, at alpha=A(-2)(m), m=1,2,..., S, each time a single delta function, delta(lambda-lambda(u)(A(m))), separates from the upper edge of the bulk distribution, where lambda(u)(A)=sigma(2)[1+A][1+(alphaA)(-1)]. We confirm the results of the replica analysis by studying the Stieltjes transform of rho(lambda). This suggests that the results obtained from the replica analysis are universal, irrespective of the distribution from which xi is drawn, provided the fourth moment of each element of xi exists.
FT-Raman spectroscopy (in combination with a fibre optic probe) was evaluated as an in-line tool to monitor a blending process of diltiazem hydrochloride pellets and paraffinic wax beads. The mean square of differences (MSD) between two consecutive spectra was used to identify the time required to obtain a homogeneous mixture. A traditional end-sampling thief probe was used to collect samples, followed by HPLC analysis to verify the Raman data. Large variations were seen in the FT-Raman spectra logged during the initial minutes of the blending process using a binary mixture (ratio: 50/50, w/w) of diltiazem pellets and paraffinic wax beads (particle size: 800-1200 microm). The MSD-profiles showed that a homogeneous mixture was obtained after about 15 min blending. HPLC analysis confirmed these observations. The Raman data showed that the mixing kinetics depended on the particle size of the material and on the mixing speed. The results of this study proved that FT-Raman spectroscopy can be successfully implemented as an in-line monitoring tool for blending processes.