Novel methods for secondary structure determination using low wavelength (VUV) circular dichroism spectroscopic data.
BACKGROUND
Circular Dichroism (CD) spectroscopy is a widely used method for studying protein structures in solution. Modern synchrotron radiation CD (SRCD) instruments have considerably higher photon fluxes than do conventional lab-based CD instruments, and hence have the ability to routinely measure CD data to much lower wavelengths. Recently a new reference dataset of SRCD spectra of proteins of known structure, designed to cover secondary structure and fold space, has been produced which includes low wavelength (vacuum ultraviolet - VUV) data. However, the existing algorithms used to calculate protein secondary structures from CD data have not been designed to take optimal advantage of the additional information in these low wavelength data.


RESULTS
In this study, we have optimised secondary structure calculation methods based on the low wavelength CD data by examining existing algorithms and secondary structure assignment schemes, and then developing new methods which have produced clear improvements in prediction accuracy, especially for beta-sheet components. We have further shown that if precise measurements of protein concentrations, and therefore spectral magnitudes, are not available, the inclusion of the low wavelength data will significantly improve the analyses. However, we have also demonstrated that the new reference dataset, methods, and assignments can also improve the analyses of conventional circular dichroism data, even if the low wavelength data is not available.


CONCLUSIONS
VUV CD data include important information on protein structure which can be exploited with the algorithms and methodologies described.
Lees
Jonathan G
JG
School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. j.lees@mail.cryst.bbk.ac.uk <j.lees@mail.cryst.bbk.ac.uk>
Miles
Andrew J
AJ
Janes
Robert W
RW
Wallace
B A
BA
D000465:Algorithms; D002942:Circular Dichroism / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D015233:Models, Statistical; D016571:Neural Networks, Computer; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D015203:Reproducibility of Results; D013053:Spectrophotometry / Q000379:methods*