Factor analysis of the near-ultraviolet absorption spectrum of plastocyanin using bilinear, trilinear, and quadrilinear models. 1990

S R Durell, and C H Lee, and R T Ross, and E L Gross
Biophysics Program, Ohio State University, Columbus, 43210.

Factor analysis was used to resolve the spectral components in the near-uv absorption spectrum of plastocyanin. The data set was absorption as a function of four variables: wavelength, species of plastocyanin, oxidation state of the copper center, and environmental pH. The data were fit with the traditional bilinear model, as well as with trilinear and quadrilinear models. Trilinear and quadrilinear models have the advantage that they uniquely define the components, avoiding the indeterminacy of bilinear models. Bilinear analysis using the absorption spectra of tyrosine and copper metallothionein as targets resulted in a two-component solution which was nearly identical to that obtained using trilinear and quadrilinear models, for which no targets are required. The two-component models separate the absorption into tyrosine and copper center components. The absorption of tyrosine is found to be pH dependent in reduced plastocyanin, and the absorption magnitude of the reduced copper center is the same in the four different plastocyanin species. Further resolution is provided by a three-component quadrilinear model. The results indicate that there are at least two different electronic transitions which cause the absorption of the reduced copper center and that one of them couples to a tyrosine residue. It is the absorption of this coupled tyrosine residue which is pH dependent. Correlation of the results with previous studies indicates that it is Tyr 83 which is the perturbed residue. The separation of the absorption of the copper center and Tyr 83 provides spectroscopic probes for the conformations of the north pole and east face reaction sites on the plastocyanin protein.

UI MeSH Term Description Entries
D010940 Plant Proteins Proteins found in plants (flowers, herbs, shrubs, trees, etc.). The concept does not include proteins found in vegetables for which PLANT PROTEINS, DIETARY is available. Plant Protein,Protein, Plant,Proteins, Plant
D010970 Plastocyanin A copper-containing plant protein that is a fundamental link in the electron transport chain of green plants during the photosynthetic conversion of light energy by photophosphorylation into the potential energy of chemical bonds. Plastocyanine,Silver Plastocyanin,Plastocyanin, Silver
D005163 Factor Analysis, Statistical A set of statistical methods for analyzing the correlations among several variables in order to estimate the number of fundamental dimensions that underlie the observed data and to describe and measure those dimensions. It is used frequently in the development of scoring systems for rating scales and questionnaires. Analysis, Factor,Analysis, Statistical Factor,Factor Analysis,Statistical Factor Analysis,Analyses, Factor,Analyses, Statistical Factor,Factor Analyses,Factor Analyses, Statistical,Statistical Factor Analyses
D001665 Binding Sites The parts of a macromolecule that directly participate in its specific combination with another molecule. Combining Site,Binding Site,Combining Sites,Site, Binding,Site, Combining,Sites, Binding,Sites, Combining
D013056 Spectrophotometry, Ultraviolet Determination of the spectra of ultraviolet absorption by specific molecules in gases or liquids, for example Cl2, SO2, NO2, CS2, ozone, mercury vapor, and various unsaturated compounds. (McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed) Ultraviolet Spectrophotometry
D014443 Tyrosine A non-essential amino acid. In animals it is synthesized from PHENYLALANINE. It is also the precursor of EPINEPHRINE; THYROID HORMONES; and melanin. L-Tyrosine,Tyrosine, L-isomer,para-Tyrosine,L Tyrosine,Tyrosine, L isomer,para Tyrosine
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model

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