Nuclear magnetic resonance (NMR) spectroscopy is one of the most versatile tools available for probing biomolecular structure, dynamics, and interactions. It is the only method capable of determining molecular structure in solution at atomic resolution, and it has a host of important biomedical applications, including screening potential drug candidates and quantifying metabolites in biofluids or intact cells. Sensitivity and resolution present twin challenges in biomolecular NMR. Both are improved by performing experiments at the highest attainable magnetic field, on instruments that can be staggeringly expensive. Signal processing methods have also long been used in NMR to enhance sensitivity and resolution to the fullest possible extent. Linear methods of signal processing based on the Fourier transform invariably encounter a sensitivity/resolution tradeoff, where one can be enhanced at the expense of the other, but both cannot be simultaneously optimized. Nonlinear methods of spectrum analysis can in some cases avoid this tradeoff, and simultaneously improve both sensitivity and resolution. Anecdotal examples of simultaneously improving sensitivity and resolution in one dimension using maximum entropy deconvolution have been reported, but the gains achieved with this approach are typically modest. In this project we will develop methods for employing maximum entropy to simultaneously deconvolve two or more dimensions to enhance sensitivity and resolution. Preliminary data indicate the resulting gains in sensitivity and resolution are substantially increased compared to one-dimensional deconvolution, and are comparable to the gains associated with collecting data at much higher magnetic field.

Public Health Relevance

NMR spectroscopy is a versatile method for probing the structure, dynamics, and interactions of biomolecules. By improving the sensitivity and resolution of multidimensional NMR experiments, the application of multidimensional deconvolution methods developed in this project will bring the power of expensive ultra high field instruments to the much broader community of labs with lower field instrumentation. For higher field instruments multidimensional deconvolution will further extend the size and complexity of biomolecular systems that can be investigated using NMR, and both applications will contribute to advances in important biomedical applications of NMR in structural biology, drug discovery, and metabolomics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21GM104517-02
Application #
8724528
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
2013-09-01
Project End
2015-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Connecticut
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
City
Farmington
State
CT
Country
United States
Zip Code
06030
Maciejewski, Mark W; Schuyler, Adam D; Hoch, Jeffrey C (2018) Practical Nonuniform Sampling and Non-Fourier Spectral Reconstruction for Multidimensional NMR. Methods Mol Biol 1688:341-352
Zambrello, Matthew A; Maciejewski, Mark W; Schuyler, Adam D et al. (2017) Robust and transferable quantification of NMR spectral quality using IROC analysis. J Magn Reson 285:37-46
Hoch, Jeffrey C (2017) Beyond Fourier. J Magn Reson 283:117-123
Stern, Alan S; Hoch, Jeffrey C (2015) A new approach to compressed sensing for NMR. Magn Reson Chem 53:908-12
Mobli, Mehdi; Hoch, Jeffrey C (2014) Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR. Prog Nucl Magn Reson Spectrosc 83:21-41