On the analysis of membrane protein circular dichroism spectra (original) (raw)
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Analytical Biochemistry, 2000
We have expanded the reference set of proteins used in SELCON3 by including 11 additional proteins (selected from the reference sets of Yang and co-workers and Keiderling and co-workers). Depending on the wavelength range and whether or not denatured proteins are included in the reference set, five reference sets were constructed with the number of reference proteins varying from 29 to 48. The performance of three popular methods for estimating protein secondary structure fractions from CD spectra (implemented in software packages CONTIN, SELCON3, and CDSSTR) and a variant of CONTIN, CONTIN/LL, that incorporates the variable selection method in the locally linearized model in CONTIN, were examined using the five reference sets described here, and a 22-protein reference set. Secondary structure assignments from DSSP were used in the analysis. The performances of all three methods were comparable, in spite of the differences in the algorithms used in the three software packages. While CDSSTR performed the best with a smaller reference set and larger wavelength range, and CONTIN/LL performed the best with a larger reference set and smaller wavelength range, the performances for individual secondary structures were mixed. Analyzing protein CD spectra using all three methods should improve the reliability of predicted secondary structural fractions. The three programs are provided in CDPro software package and have been modified for easier use with the different reference sets described in this paper. CDPro software is available at the website: http://lamar.colostate.edu/ ϳsreeram/CDPro.
Analytical Biochemistry, 2006
We present here a simple and rapid method to extract good estimates of protein secondary structure content from circular dichroism (CD) spectra without any prior knowledge of the sample concentration. The method involves two steps: first, a singlewavelength normalization procedure and, second, the application for each secondary structure of a quadratic model based on one or two wavelength intensities. These quadratic models were derived by a cross-validation analysis of a new protein CD spectrum database. Tested on CD spectra of proteins at different concentrations, the normalization was shown to render the method virtually independent of the sample concentration. Further tests on CD spectra not recorded in our laboratory showed that our quadratic models are of general applicability. Even though the success of the present approach is less than that for currently available methods, its simplicity and the fact that the concentration is not needed may be very attractive for the study of small amounts of membrane proteins or peptides for which an accurate concentration determination might be very difficult or impossible to obtain.
Analytical Biochemistry, 2003
We present here a simple and rapid method to extract good estimates of protein secondary structure content from circular dichroism (CD) spectra without any prior knowledge of the sample concentration. The method involves two steps: first, a singlewavelength normalization procedure and, second, the application for each secondary structure of a quadratic model based on one or two wavelength intensities. These quadratic models were derived by a cross-validation analysis of a new protein CD spectrum database. Tested on CD spectra of proteins at different concentrations, the normalization was shown to render the method virtually independent of the sample concentration. Further tests on CD spectra not recorded in our laboratory showed that our quadratic models are of general applicability. Even though the success of the present approach is less than that for currently available methods, its simplicity and the fact that the concentration is not needed may be very attractive for the study of small amounts of membrane proteins or peptides for which an accurate concentration determination might be very difficult or impossible to obtain.
Protein Science, 2008
A simple approach to estimate the number of a-helical and b-strand segments from protein circular dichroism spectra is described. The a-helix and b-sheet conformations in globular protein structures, assigned by DSSP and STRIDE algorithms, were divided into regular and distorted fractions by considering a certain number of terminal residues in a given a-helix or b-strand segment to be distorted. The resulting secondary structure fractions for 29 reference proteins were used in the analyses of circular dichroism spectra by the SELCON method. From the performance indices of the analyses, we determined that, on an average, four residues per a-helix and two residues per b-strand may be considered distorted in proteins. The number of a-helical and b-strand segments and their average length in a given protein were estimated from the fraction of distorted a-helix and b-strand conformations determined from the analysis of circular dichroism spectra. The statistical test for the reference protein set shows the high reliability of such a classification of protein secondary structure. The method was used to analyze the circular dichroism spectra of four additional proteins and the predicted structural characteristics agree with the crystal structure data. Keywords: circular dichroism; distorted b-strand; distorted a-helix; helix and strand segments; protein secondary structure Circular dichroism~CD! spectroscopy is a widely used technique for studying protein and nucleic acid conformations. Over the last three decades, various methods have been developed for the analysis of protein CD spectra based upon the spectral characteristics of protein secondary structures~Greenfield !. In these methods, spectra of either model polypeptides or of a set of reference proteins with known crystal structure are used, and the CD spectrum of a given protein is treated as a linear combination of component secondary structure spectra. For the set of proteins considered, the CD spectra and the secondary structure fractions form either a set of linear equations that is solved by least-squares-based methods or a pattern that is analyzed by pattern recognition methods, and the secondary structure content corresponding to a given CD spectrum is determined. These have been reviewed recently by Venyaminov and Yang~1996! and by Greenfield~1996!. Similar methods have also been used in the analyses of infrared~IR!~Kalnin et al !, Raman~Williams, 1983!, and vibrational CD~VCD!~Pancoska et al., 1991! spectra of proteins. The information derived from these analyses have been largely limited to the estimation of fractional content of a-helix, b-sheet, b-turns, and~in one case! poly~Pro!II structures in proteins.
K2D2: Estimation of protein secondary structure from circular dichroism spectra
BMC Structural Biology, 2008
Background: Circular dichroism spectroscopy is a widely used technique to analyze the secondary structure of proteins in solution. Predictive methods use the circular dichroism spectra from proteins of known tertiary structure to assess the secondary structure contents of a protein with unknown structure given its circular dichroism spectrum.
Protein secondary structure from circular dichroism spectra
Journal of Biosciences, 1985
Circular dichroism spectra of proteins are extremely sensitive to secondary structure. Nevertheless, circular dichroism spectra should not be analyzed for protein secondary structure unless they are measured to at least 184 nm. Even if all the various types of β-turns are lumped together, there are at least 5 different types of secondary structure in a protein (α-helix, antiparallel β-sheet, parallel β-sheet, β-turn, and other structures not included in the first 4 categories). It is not possible to solve for these 5 parameters unless there are 5 equations. Singular value decomposition can be used to show that circular dichroism spectra of proteins measured to 200 nm contain only 2 pieces of information, while spectra measured to 190 nm contain about 4. Adding the constraint that the sum of secondary structures must equal 1 provides another piece of information, but even with this constraint, spectra measured to 190 nm simply do not analyze well for the 5 unknowns in secondary structure. Spectra measured to 184 nm do contain 5 pieces of information and we have used such spectra successfully to analyze a variety of proteins for their component secondary structures.
Proteins, 2006
Protein classification and characterization often rely on the information contained in the protein secondary structure. Protein class assignment is usually based on X-ray diffraction measurements, which need the protein in a crystallized form, or on NMR spectra, to obtain the structure of a protein in solution. Simple spectroscopic techniques, such as circular dichroism (CD) and infrared (IR) spectroscopies, are also known to be related to protein secondary structure, but they have seldom been used for protein classification. To see the potential of CD, IR, and combined CD/IR measurements for protein classification, unsupervised pattern recognition methods, Principal Component Analysis (PCA) and cluster analysis, are proposed first to check for natural grouping tendencies of proteins according to their measured spectra. Partial Least Squares Discriminant Analysis (PLS-DA), a supervised pattern recognition method, is used afterwards to test the possibility to model explicitly each pr...
Journal of Pharmaceutical Sciences, 2011
Circular dichroism (CD) spectroscopy is routinely used in the biopharmaceutical industry to study the effects of manufacturing, formulation, and storage conditions on protein conformation and stability, and these results are often included in regulatory filings. In this context, the purpose of CD spectroscopy is often to verify that a change in the formulation or manufacturing process of a product has not produced a change in the conformation of a protein. A comparison of two or more spectra is often required to confirm that the protein's structure has been maintained. Traditionally, such comparisons have been qualitative in nature, based on visually inspecting the overlaid spectra. However, visual assessment is inherently subjective and therefore prone to error. Furthermore, recent requests from regulatory agencies to demonstrate the suitability of the CD spectroscopic method for the purpose of comparing spectra have highlighted the need to appropriately qualify CD spectroscopy for characterization of biopharmaceutical protein products. In this study, we use a numerical spectral comparison approach to establish the precision of the CD spectroscopic method and to demonstrate that it is suitable for protein structural characterization in numerous biopharmaceutical applications.