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  Statistical analysis of ENDOR spectra

Pokern, Y., Eltzner, B., Huckemann, S. F., Beeken, C., Stubbe, J., Tkach, I., et al. (2021). Statistical analysis of ENDOR spectra. Proceedings of the National Academy of Sciences of the USA, 118(27): e2023615118. doi:10.1073/pnas.2023615118.

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Pokern, Y., Author
Eltzner, B., Author
Huckemann, S. F., Author
Beeken, C., Author
Stubbe, J., Author
Tkach, I.1, Author           
Bennati, M.2, Author           
Hiller, M., Author
Affiliations:
1Research Group of Electron Paramagnetic Resonance, MPI for biophysical chemistry, Max Planck Society, ou_578606              
2Research Group of Electron Paramagnetic Resonance, MPI for Biophysical Chemistry, Max Planck Society, ou_578606              

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Free keywords: ENDOR; error model; bootstrap; statistical test; styrosyl radical
 Abstract: Electron–nuclear double resonance (ENDOR) measures the hyperfine interaction of magnetic nuclei with paramagnetic centers and is hence a powerful tool for spectroscopic investigations extending from biophysics to material science. Progress in microwave technology and the recent availability of commercial electron paramagnetic resonance (EPR) spectrometers up to an electron Larmor frequency of 263 GHz now open the opportunity for a more quantitative spectral analysis. Using representative spectra of a prototype amino acid radical in a biologically relevant enzyme, the Y∙122 in Escherichia coli ribonucleotide reductase, we developed a statistical model for ENDOR data and conducted statistical inference on the spectra including uncertainty estimation and hypothesis testing. Our approach in conjunction with 1H/2H isotopic labeling of Y∙122 in the protein unambiguously established new unexpected spectral contributions. Density functional theory (DFT) calculations and ENDOR spectral simulations indicated that these features result from the beta-methylene hyperfine coupling and are caused by a distribution of molecular conformations, likely important for the biological function of this essential radical. The results demonstrate that model-based statistical analysis in combination with state-of-the-art spectroscopy accesses information hitherto beyond standard approaches.

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Language(s): eng - English
 Dates: 2021-06-06
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1073/pnas.2023615118
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Title: Proceedings of the National Academy of Sciences of the USA
Source Genre: Journal
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Pages: 11 Volume / Issue: 118 (27) Sequence Number: e2023615118 Start / End Page: - Identifier: -