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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
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Application of spherical harmonics for DEER data analysis in systems with a conformational distribution
1School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK.
Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|June 24, 2020
Summary
This study develops advanced theory for Double Electron-Electron Resonance (DEER) to analyze distance and orientation in paramagnetic centers, even with conformational disorder. The new methods improve data analysis for applications in biophysics and materials science.
Area of Science:
- Biophysics
- Chemical Physics
- Spectroscopy
Background:
- Double electron-electron resonance (DEER) and pulse electron paramagnetic resonance (EPR) are key for distance measurements between paramagnetic centers.
- Existing DEER theory is limited when relative orientations significantly affect data, often requiring model-based simulations.
- Orientation selection effects in DEER are not fully addressed by current analytical theories.
Purpose of the Study:
- To elaborate the theory of DEER, specifically addressing orientation selection effects in systems with moderate conformational disorder.
- To develop analytical and computational methods for extracting distance and orientation information from DEER data.
- To validate the developed theoretical framework and algorithms using experimental data.
Main Methods:
- Analytical treatment of DEER data using expansions into spherical harmonics to account for orientation distribution.
- Representation of DEER spectra with orientation selection as linear combinations of modified Pake pattern (MPP) components.
- Development of a model-free iterative processing algorithm based on Tikhonov regularization for disentangling distance and orientation information.
Main Results:
- Conformational disorder acts as a filter, suppressing higher-degree modified Pake pattern (MPP) components in DEER spectra.
- The developed theory enables model-based simulations with analytically defined orientation distributions.
- A novel iterative algorithm successfully disentangles distance and orientation information from multiple DEER datasets.
- Validation of both model-based and model-free approaches using a nitroxide biradical and a spin-labeled protein.
Conclusions:
- The developed spherical harmonics expansion theory provides crucial insights into DEER data structure under orientation selection effects.
- The new methods offer a robust pathway for analyzing complex systems where orientation distribution is significant.
- The validated approaches enhance the utility of DEER spectroscopy for structural studies of biomolecules and materials.
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