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Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy
Published on: March 5, 2017
Membrane protein structure determination from Paramagnetic Relaxation Enhancement and internuclear distance
Raoul F Vaz1, Leonid S Brown1, Vlad Ladizhansky2
1Department of Physics and Biophysics Interdepartmental Group, University of Guelph, 50 Stone Rd. E., Guelph, ON, N1G 2W1, Canada.
Paramagnetic Relaxation Enhancements (PRE) from 2D MAS NMR spectra aid protein structure determination. This method, using Anabaena Sensory Rhodopsin, improves spectral assignment and structural modeling for membrane proteins.
Area of Science:
- Biochemistry
- Structural Biology
- Biophysics
Background:
- Magic angle spinning nuclear magnetic resonance (MAS NMR) is crucial for protein structure determination.
- Spectral overlap in MAS NMR spectra complicates the assignment of cross peaks, hindering structural analysis.
Purpose of the Study:
- To demonstrate the utility of transverse Paramagnetic Relaxation Enhancements (PRE) from 2D MAS NMR spectra for protein structural modeling.
- To develop an improved method for assigning spectral cross peaks in complex protein systems.
Main Methods:
- Utilized a seven-helical membrane protein, Anabaena Sensory Rhodopsin (ASR), as a model system.
- Combined TALOS+ predicted dihedral angles and hydrogen bond restraints with PRE-based restraints to generate an initial structural model.
- Employed an iterative cross-peak assignment process using the generated model as a template.
Main Results:
- Successfully generated a coarse structural model of ASR using combined restraints.
- Facilitated automated assignment of ambiguous internuclear correlations through iterative refinement.
- Achieved convergence to a low root-mean-square-deviation structural model with improved helix packing.
Conclusions:
- Transverse PREs extracted from 2D MAS NMR spectra are effective for protein structure determination and spectral assignment.
- The iterative approach using a PRE-enhanced template model improves structural modeling efficiency and accuracy.
- PREs enhance the packing of helices within alpha-helical bundles, providing valuable insights into membrane protein structure.
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