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Søren Vrønning Hoffmann

SESCA: Predicting Circular Dichroism Spectra from Protein Molecular Structures

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  • Gabor Nagy, Max Planck Institute for Biophysical Chemistry, Göttingen, Tyskland
  • Maxim Igaev, Max Planck Institute for Biophysical Chemistry, Göttingen, Tyskland
  • Nykola C. Jones
  • Søren Vrønning Hoffmann
  • Helmut Grubmüller, Max Planck Institute for Biophysical Chemistry, Göttingen, Tyskland

Circular dichroism (CD) spectroscopy is a highly sensitive but low-resolution technique to study the structure of proteins. Combined with molecular modeling or other complementary techniques, CD spectroscopy can provide essential information at higher resolution. To this end, we introduce a new computational method to calculate the electronic circular dichroism spectra of proteins from a structural model or ensemble using the average secondary structure composition and a precalculated set of basis spectra. The method is designed for model validation to estimate the error of a given protein structural model based on the measured CD spectrum. We compared the predictive power of our method to that of existing algorithms, namely, DichroCalc and PDB2CD, and found that it predicts CD spectra more accurately. Our results indicate that the derived basis sets are robust to both experimental errors in the reference spectra and the choice of the secondary structure classification algorithm. For over 80% of the globular reference proteins, our basis sets accurately predict the experimental spectrum solely from their secondary structure composition. For the remaining 20%, correcting for intensity normalization considerably improves the prediction power. Additionally, we show that the predictions for short peptides and an example complex of intrinsically disordered proteins strongly benefit from accounting for side-chain contributions and structural flexibility.

OriginalsprogEngelsk
TidsskriftJournal of Chemical Theory and Computation
Vol/bind15
Nummer9
Sider (fra-til)5087-5102
Antal sider16
ISSN1549-9618
DOI
StatusUdgivet - sep. 2019

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