PSI Structural Biology Knowledgebase

PSI | Structural Biology Knowledgebase
Header Icons

Related Articles
Automating NMR Structures
April 2015
Protein Folding and Misfolding: A TRiC-ster that Follows the Rules
March 2015
Virology: Making Sensitive Magic
March 2014
Microbiome: Solid-State NMR, Crystallized
September 2013
Membrane Proteome: Making DNA Nanotubes for NMR Structure Determination
August 2013
Protein-Nucleic Acid Interaction: Inhibition Through Allostery
July 2013
Cell-Cell Interaction: Magic Structure from Microcrystals
March 2013
Membrane Proteome: Soft Sampling
December 2012
Membrane Proteome: Specific vs. Non-specific weak interactions
November 2012
Automatic NMR
September 2012
NMR structure test
September 2012
To structure, faster
August 2012
S is for solubility
June 2012
Blind faith
April 2012
Follow the RNA leader
December 2011
Making invisible proteins visible
October 2011
A fragmented approach to membrane protein structures
September 2011
Molecular replacement by magnetic resonance
August 2011
Solutions in the solution
June 2011
No more labeled lipids
May 2011
Capsid assembly in motion
April 2011
NMR challenges current protein hydration dogma
March 2011
Solving homodimeric structures with NMR
November 2010
CASD-NMR: assessing automated structure determination by NMR
June 2010
Peptidoglycan binding: Calcium-free killing
June 2010
Removing the NMR bottleneck
April 2010
NMR has its wiki way
March 2010
Extremely salty
February 2010
The future of NMR
September 2009
Tips for crystallizing membrane proteins
June 2009
Faster solid-state NMR
May 2009
Powerful NMR
April 2009
Activating BAX
December 2008

Membrane Proteome: Soft Sampling

SBKB [doi:10.1038/sbkb.2012.114]
Technical Highlight - December 2012
Short description: A novel method for processing non-uniformly sampled NMR data is orders of magnitude faster and permits very sparse sampling for challenging applications.

Outline of the IST procedure for processing NMR data containing signals of varying intensities. Figure courtesy of Gerhard Wagner and Sven Hyberts.

NMR spectroscopy can now tackle many challenging systems, including protein-protein complexes, nucleic acids, and membrane proteins. Such applications have relied on the development of higher magnetic field strengths and the resolution and sensitivity provided by these instruments. The sampling requirements at higher magnetic fields, however, have a drawback: optimal resolution cannot be achieved with current experimental schemes since, for typical measurement times, more data points would be required to fully characterize the range of frequencies in the spectrum. This is particularly evident in higher dimensional 3D and 4D data.

These developments have led to a renewed interest in non-uniform sampling (NUS) methods. In contrast to uniform sampling, NUS sparsely samples data points and, in principle, promises to deliver optimal resolution in a fraction of the time while using instruments to full potential. Whereas data processing for regular sampling schedules uses a simple Fourier transformation (FT), NUS data reconstruction typically requires alternative, and computationally intensive, digital signal processing methods.

Wagner and colleagues (PSI MPSbyNMR) have developed an algorithm based on iterative soft thresholding (IST), an approach previously used to reconstruct signals from the noisy data of MRI and other imaging methods. Using a Poisson-gap sampling scheme, the authors found that IST can be used in conjunction with iterative FT to gradually extract the signal from noise-like artifacts resulting from NUS. Their scheme, implemented in a convenient graphical user interface (GUI), has the significant advantage of using FT, dramatically reducing processing times.

The authors applied their method to several data sets, including a 4D spectrum of a 28 kDa protein-protein complex. The 4D spectrum was acquired with a sampling density of 14.5% and processed orders of magnitude faster, revealing many methyl-methyl interactions. A further experiment aimed at achieving fully optimal resolution using the same 4D experiment sampled at only 0.8% reproduced known assignments. An important requirement for any processing method is the faithful reproduction of relative signal intensities used to generate distance restraints for structure calculations. A comparison of intensities in two IST-processed spectra with equivalent uniformly sampled data demonstrated excellent fidelity in relative peak intensities.

The IST method will be particularly beneficial for α-helical membrane proteins where methyl-methyl contacts provide invaluable structural data. Combined with the convenient GUI and fast processing times, the IST method promises to be widely adopted.

Michael A. Durney


  1. S. G. Hyberts et al. Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson gap scheduling.
    J Biomol NMR. 52, 315-327 (2012). doi:10.1007/s10858-012-9611-z

Structural Biology Knowledgebase ISSN: 1758-1338
Funded by a grant from the National Institute of General Medical Sciences of the National Institutes of Health