International comparability in spectroscopic measurements of protein structure by circular dichroism: CCQM-P59.1 (original) (raw)
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Metrologia, 2010
Circular dichroism (CD) is a spectroscopic technique that is widely used to obtain information about protein structure, and hence is an important tool with many applications, including the characterization of biopharmaceuticals. A previous inter-laboratory study, CCQM-P59, showed that there was a poor level of comparability between laboratories in CD spectroscopy. In a follow-up study reported here, we achieved our goal of demonstrating improved comparability and data quality, primarily by addressing the problems identified in the previous study, which included cell path-length measurement, instrument calibration and good practice in general. Multivariate analysis techniques (principal component analysis and soft independent modelling of class analogies) were shown to be useful in comparing large spectral data sets and in classifying spectra. However, our results also show that there is more work to be done to improve confidence in the technique as the discrepancies observed were partially due to systematic effects, which the statistical approaches do not consider. We therefore conclude that there is a need for an improved understanding of the uncertainties in CD measurement.
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.
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.
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.
Least-Squares Analysis of Circular Dichroic Spectra of Proteins
European Journal of Biochemistry, 1977
It is shown that the method proposed by Baker and Isenberg [Biochemistry, 15, 629 (1976)l for estimating secondary structure composition of proteins from circular dichroic spectra is a leastsquares fitting technique. Estimates obtained by this method for myoglobin, lysozyme, lactate dehydrogenase, papain, and ribonuclease are not substantively different from those obtained using unconstrained linear least squares.
Protein Science, 1995
This work provides a systematic comparison of vibrational CD (VCD) and electronic CD (ECD) methods for spectral prediction of secondary structure. The VCD and ECD data are simplified to a small set of spectral parameters using the principal component method of factor analysis (PC/FA). Regression fits of these parameters are made to the X-ray-determined fractional components (FC) of secondary structure. Predictive capability is determined by computing structures for proteins sequentially left out of the regression. All possible combinations of PC/FA spectral parameters (coefficients) were used to form a full set of restricted multiple regressions with the FC values, both independently for each spectral data set as well as for the two VCD sets and all the data grouped together. The complete search over all possible combinations of spectral parameters for different types of spectral data is a new feature of this study, and the focus on prediction is the strength of this approach. The PC/FA method was found to be stable in detail to expansion of the training set. Coupling amide I1 to amide I' parameters reduced the standard deviations of the VCD regression relationships, and combining VCD and ECD data led to the best fits. Prediction results had a minimum error when dependent on relatively few spectral coefficients. Such a limited dependence on spectral variation is the key finding of this work, which has ramifications for previous studies as well as suggests future directions for spectral analysis of structure. The best ECD prediction for helix and sheet uses only one parameter, the coefficient of the first subspectrum. With VCD, the best predictions sample coefficients of both the amide I' and I1 bands, but error is optimized using only a few coefficients. In this respect, ECD is more accurate than VCD for a-helix, and the combined VCD (amide I'+II) predicts the P-sheet component better than does ECD. Combining VCD and ECD data sets yields exceptionally good predictions by utilizing the strengths of each. However, the residual error, its distribution, and, most importantly, the lack of dependence of the method on many of the significant components derived from the spectra leads to the conclusion that the heterogeneity of protein structure is a fundamental limitation to the use of such spectral analysis methods. The underutilization of these data for prediction of secondary structure suggests spectral data could predict a more detailed descriptor.
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, 2004
CDtool is a software package written to facilitate circular dichroism (CD) spectroscopic studies on both conventional lab-based instruments and synchrotron beamlines. It takes format-independent input data from any type of CD instrument, enables a wide range of standard and advanced processing methods, and, in a single user-friendly graphics-based package, takes raw data through the entire processing procedure and, importantly, uses data-mining techniques to retain in the final output all the information associated with the processing. It permits the facile comparison of data obtained from different instruments without the need for reformatting and displays it in graphical formats suitable for publication. It also includes the ability to automatically archive the processed data. This latter feature may be especially useful in light of recent funding institution directives with regard to data sharing and archiving and requirements for ''good practice'' and ''traceability'' within the pharmaceutical industry. In addition, CDtool includes a means of interfacing with protein data bank coordinate files and calculating secondary structures from them using alternate definitions and algorithms. This feature, along with a function that permits the facile production of new reference databases, enables the creation of specialized databases for secondary structural analyses of specific types of proteins. Thus the CDtool software not only enables rapid data processing and analyses but also includes many enhanced features not available in other CD data processing/analysis packages.