The overall objectives of this research are to develop and apply new nuclear magnetic resonance (NMR) methods and web-based technology for the rapid and reliable collection, processing, and analysis of NMR spectra of large and small biomolecules. The principles of Covariance NMR Spectroscopy, developed in the previous funding period, will be extended to higher dimensional spectroscopy, including GFT and projection reconstruction NMR, in order to gain substantial increase in spectral resolution along indirect dimensions and to enable the automated assignment of backbone and side-chain resonances of proteins. Covariance-based resolution enhancement methods will be developed for new 4D NOESY-schemes to increase the number of short- and long-range NMR distance constraints, including stereo-specific assignments, necessary for the determination of high-quality protein structures. Covariance NMR and other matrix-based methods for the analysis of complex metabolite mixtures will be developed to obtain quantitative information on the mixture components, not available by other methods, with the goal toward automated high-throughput fingerprinting and profiling in the emerging field of metabolomics. The methods will be made available to a broad range of users through a suite of interconnected web servers.
Advanced covariance NMR methods enable the efficient assignment of resonances and the extraction of better distance information for the accurate determination of protein structures. These are a prerequisite for understanding protein function and protein-ligand interactions for the development of new and better drugs. New NMR-based metabolomics tools provide comprehensive information about the chemistry of cells, tissues, and biofluids. They will provide a new perspective on disease and treatment and will lead the way to personalized medicine.
|Bingol, Kerem; Bruschweiler, Rafael (2014) Multidimensional approaches to NMR-based metabolomics. Anal Chem 86:47-57|
|Bingol, Kerem; Bruschweiler-Li, Lei; Li, Da-Wei et al. (2014) Customized metabolomics database for the analysis of NMR ¹H-¹H TOCSY and ¹³C-¹H HSQC-TOCSY spectra of complex mixtures. Anal Chem 86:5494-501|
|Bingol, Kerem; Zhang, Fengli; Bruschweiler-Li, Lei et al. (2013) Quantitative analysis of metabolic mixtures by two-dimensional 13C constant-time TOCSY NMR spectroscopy. Anal Chem 85:6414-20|
|Robinette, Steven L; Bruschweiler, Rafael; Schroeder, Frank C et al. (2012) NMR in metabolomics and natural products research: two sides of the same coin. Acc Chem Res 45:288-97|
|Bingol, Kerem; Zhang, Fengli; Bruschweiler-Li, Lei et al. (2012) Carbon backbone topology of the metabolome of a cell. J Am Chem Soc 134:9006-11|
|Short, Timothy; Alzapiedi, Leigh; Bruschweiler, Rafael et al. (2011) A covariance NMR toolbox for MATLAB and OCTAVE. J Magn Reson 209:75-8|
|Bingol, Kerem; Bruschweiler, Rafael (2011) Deconvolution of chemical mixtures with high complexity by NMR consensus trace clustering. Anal Chem 83:7412-7|
|Zhang, Fengli; Bruschweiler-Li, Lei; Bruschweiler, Rafael (2010) Simultaneous de novo identification of molecules in chemical mixtures by doubly indirect covariance NMR spectroscopy. J Am Chem Soc 132:16922-7|
|Weingarth, Markus; Tekely, Piotr; Bruschweiler, Rafael et al. (2010) Improving the quality of 2D solid-state NMR spectra of microcrystalline proteins by covariance analysis. Chem Commun (Camb) 46:952-4|
|Bingol, Kerem; Salinas, Roberto K; Bruschweiler, Rafael (2010) Higher-Rank Correlation NMR Spectra with Spectral Moment Filtering. J Phys Chem Lett 1:1086-1089|
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