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Bayesian optimization to estimate hyperfine couplings from 19F ENDOR spectra

MPS-Authors
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Kehl,  Annemarie
Research Group of Electron Paramagnetic Resonance, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

/persons/resource/persons232625

Hiller,  Markus
Research Group of Electron Paramagnetic Resonance, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

/persons/resource/persons288636

Eltzner,  Benjamin
Research Group of Computational Biomolecular Dynamics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

/persons/resource/persons224498

Meyer,  Andreas
Research Group of Electron Paramagnetic Resonance, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

/persons/resource/persons15928

Tkach,  Igor
Research Group of Electron Paramagnetic Resonance, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

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Bennati,  M.
Research Group of Electron Paramagnetic Resonance, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

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Citation

Wiechers, H., Kehl, A., Hiller, M., Eltzner, B., Huckemann, S., Meyer, A., et al. (2023). Bayesian optimization to estimate hyperfine couplings from 19F ENDOR spectra. Journal of Magnetic Resonance, 353: 107491. doi:10.1016/j.jmr.2023.107491.


Cite as: https://hdl.handle.net/21.11116/0000-000D-44E8-1
Abstract
ENDOR spectroscopy is a fundamental method to detect nuclear spins in the vicinity of paramagnetic centers and their mutual hyperfine interaction. Recently, site-selective introduction of 19F as nuclear labels has been proposed as a tool for ENDOR-based distance determination in biomolecules, complementing pulsed dipolar spectroscopy in the range of angstrom to nanometer. Nevertheless, one main challenge of ENDOR still consists of its spectral analysis, which is aggravated by a large parameter space and broad resonances from hyperfine interactions. Additionally, at high EPR frequencies and fields (94 GHz/3.4 Tesla), chemical shift anisotropy might contribute to broadening and asymmetry in the spectra. Here, we use two nitroxide-fluorine model systems to examine a statistical approach to finding the best parameter fit to experimental 263 GHz 19F ENDOR spectra. We propose Bayesian optimization for a rapid, global parameter search with little prior knowledge, followed by a refinement by more standard gradient-based fitting procedures. Indeed, the latter suffer from finding local rather than global minima of a suitably defined loss function. Using a new and accelerated simulation procedure, results for the semi-rigid nitroxide-fluorine two and three spin systems lead to physically reasonable solutions, if minima of similar loss can be distinguished by DFT predictions. The approach also delivers the stochastic error of the obtained parameter estimates. Future developments and perspectives are discussed.