Bio

Rafael Brüschweiler received his Ph.D. in Physical Chemistry from ETH Zurich, Switzerland, before doing a postdoc at the Department of Molecular Biology at the Scripps Research Institute, La Jolla. He joined the Florida State University, Tallahassee, as full professor and the National High Magnetic Field Laboratory as Associate Director for Biophysics.  Professor Brüschweiler joined Ohio State in 2013 with joint appointments at the Department of Chemistry and Biochemistry and the Department of Biological Chemistry and Pharmacology.  He is a full Professor, an Ohio Research Scholar (endowed), and the NMR Executive Director for the Ohio State Campus Chemical Instrument Center and the NSF-funded National Gateway Ultrahigh Field NMR Center to feature the first 1.2 GHz NMR Spectrometer in the U.S. His research is funded primarily by the National Science Foundation and the National Institutes of Health. 

Research Overview

Professor Brüschweiler's research is highly cross-disciplinary in the area of biophysical chemistry as well as analytical chemistry. It focuses on the understanding of the role of dynamics and interactions of proteins for their function and on the analysis of complex biological mixtures in the context of metabolomics. The main research tools are high-field nuclear magnetic resonance (NMR) and high-performance computation, which includes the development of new and improved techniques to enhance resolution, sensitivity, and speed. Biological systems studied in the lab include the following proteins: the GTPase K-Ras and its oncogenic mutants, p53/MDM2, sodium-calcium exchanger NCX, Cu2+-ATPase, ubiquitin, and the enzymes arginine kinase and glucokinase. Metabolic studies are conducted on opportunistic biofilm-forming microbes, such as Pseudomonas aeruginosa and Staphylocuccus aureus, drosophila, E. coli, yeast, and cancer cell lines for the identification of biomarkers, biochemical pathways and the characterization of novel metabolites in health and disease. We also combine biophysical chemistry with nano-science, for example, for nanoparticle-assisted NMR spin relaxation. We also develop machine-learning tools for the better and automated analysis and interpretation of NMR data. 

Dr. Brüschweiler is accepting new graduate students for the Fall that have interest in studying (1) protein dynamics, interactions, and function by state-of-the-art NMR spectroscopy, (2) protein dynamics and function by computational methods (molecular dynamics simulations) toward a predictive understanding of complex biomolecular systems, (3) complex mixture analysis and metabolomics by NMR for biomedical diagnostics in collaboration with the OSU Medical School, and/or (4) the development of new NMR methods (pulse sequences, enhanced sampling, rapid spectral reconstruction). Graduate students from any of the chemistry (bio, physical, analytical) programs, the Biophysics program, and OSBP are encouraged to contact Dr. Brüschweiler to learn more about his group's research, meet current graduate students and postdocs in the lab, and discuss the possibility of a research rotation. More detailed information can be found on the Brüschweiler website.

Past members of the Brüschweiler group have been successful in a wide range of professional positions in the US and abroad in industry, national labs, and academia. 

Publications

Hansen, A.L., Xiang, X., Yuan, C., Bruschweiler-Li, L. and Brüschweiler, R., 2023. Excited-state observation of active K-Ras reveals differential structural dynamics of wild-type versus oncogenic G12D and G12C mutants. Nature Structural & Molecular Biology, pp.1-10.

Xiang, X., Hansen, A.L., Yu, L., Jameson, G., Bruschweiler-Li, L., Yuan, C. and Brüschweiler, R., 2021. Observation of sub-microsecond protein methyl-side chain dynamics by nanoparticle-assisted NMR spin relaxation. Journal of the American Chemical Society, 143(34), pp.13593-13604.

Li, D.W., Hansen, A.L., Yuan, C., Bruschweiler-Li, L. and Brüschweiler, R., 2021. DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra. Nature communications, 12(1), p.5229.

Hansen, A.L., Kupče, E., Li, D.W., Bruschweiler-Li, L., Wang, C. and Brüschweiler, R., 2021. 2D NMR-based metabolomics with HSQC/TOCSY NOAH supersequences. Analytical Chemistry, 93(15), pp.6112-6119.

Yu, L., Li, D.W. and Brüschweiler, R., 2019. Balanced amino-acid-specific molecular dynamics force field for the realistic simulation of both folded and disordered proteins. Journal of chemical theory and computation, 16(2), pp.1311-1318.

Li, D.W., Leggett, A., Bruschweiler-Li, L. and Brüschweiler, R., 2022. COLMARq: A web server for 2D NMR peak picking and quantitative comparative analysis of cohorts of metabolomics samples. Analytical Chemistry, 94(24), pp.8674-8682.

Ma, P., Li, D.W. and Brüschweiler, R., 2023. Predicting protein flexibility with AlphaFold. Proteins: Structure, Function, and Bioinformatics, 91(6), pp.847-855.

Leggett, A., Li, D.W., Bruschweiler-Li, L., Sullivan, A., Stoodley, P. and Brüschweiler, R., 2022. Differential metabolism between biofilm and suspended Pseudomonas aeruginosa cultures in bovine synovial fluid by 2D NMR-based metabolomics. Scientific Reports, 12(1), p.17317.

Wardenfelt, S., Xiang, X., Xie, M., Yu, L., Bruschweiler‐Li, L. and Brüschweiler, R., 2021. Broadband dynamics of ubiquitin by anionic and cationic nanoparticle assisted NMR spin relaxation. Angewandte Chemie, 133(1), pp.150-154.

Li, D.W., Hansen, A.L., Bruschweiler-Li, L., Yuan, C. and Brüschweiler, R., 2022. Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra. Journal of Biomolecular NMR, 76(3), pp.49-57.

Leggett, A., Li, D.W., Sindeldecker, D., Staats, A., Rigel, N., Bruschweiler-Li, L., Brüschweiler, R. and Stoodley, P., 2022. Cadaverine is a switch in the lysine degradation pathway in Pseudomonas aeruginosa biofilm identified by untargeted metabolomics. Frontiers in Cellular and Infection Microbiology, 12, p.833269.

Yu, L. and Brüschweiler, R., 2022. Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins. PLOS Computational Biology, 18(9), p.e1010036.

Li, D.W., Xie, M. and Brüschweiler, R., 2020. Quantitative cooperative binding model for intrinsically disordered proteins interacting with nanomaterials. Journal of the American Chemical Society, 142(24), pp.10730-10738.

Wang, C., Timári, I., Zhang, B., Li, D.W., Leggett, A., Amer, A.O., Bruschweiler-Li, L., Kopec, R.E. and Brüschweiler, R., 2020. COLMAR lipids web server and ultrahigh-resolution methods for two-dimensional nuclear magnetic resonance-and mass spectrometry-based lipidomics. Journal of proteome research, 19(4), pp.1674-1683.

Timári, I., Wang, C., Hansen, A.L., Costa dos Santos, G., Yoon, S.O., Bruschweiler-Li, L. and Brüschweiler, R., 2019. Real-time pure shift HSQC NMR for untargeted metabolomics. Analytical chemistry, 91(3), pp.2304-2311.

Jameson, G., Hansen, A.L., Li, D., Bruschweiler-Li, L. and Brüschweiler, R., 2019. Extreme nonuniform sampling for protein NMR dynamics studies in minimal time. Journal of the American Chemical Society, 141(42), pp.16829-16838.

Yu, L., Li, D.W. and Brüschweiler, R., 2021. Systematic differences between current molecular dynamics force fields to represent local properties of intrinsically disordered proteins. The Journal of Physical Chemistry B, 125(3), pp.798-804.

Xie, M., Yu, L., Bruschweiler-Li, L., Xiang, X., Hansen, A.L. and Brüschweiler, R., 2019. Functional protein dynamics on uncharted time scales detected by nanoparticle-assisted NMR spin relaxation. Science advances, 5(8), p.eaax5560.

Jameson, G. and Bruschweiler, R., 2021. NMR spin relaxation theory of biomolecules undergoing highly asymmetric exchange with large interaction partners. Journal of chemical theory and computation, 17(4), pp.2374-2382.

Li, D.W., Bruschweiler-Li, L., Hansen, A.L. and Brüschweiler, R., 2023. DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra. Magnetic Resonance, 4(1), pp.19-26.

Allpas, R.C., Hansen, A.L. and Brüschweiler, R., 2022. NOAH-(15 N/13 C)-CEST NMR supersequence for dynamics studies of biomolecules. Chemical Communications, 58(66), pp.9258-9261.

Allpas, R.C., Hansen, A.L. and Brüschweiler, R., 2023. ARCHE-NOAH: NMR supersequence with five different CEST experiments for studying protein conformational dynamics. Physical Chemistry Chemical Physics.

Li, D.-W.; Showalter, S.A.; Brüschweiler, R. J. Phys. Chem. B 2010,114: 16036-16044. Entropy localization in proteins.

Li, D-W.; Brüschweiler, R. J. Chem. Theor. Comput. 2011, 7: 1773-1782. Iterative optimization of molecular mechanics force fields from NMR data of full-length proteins.

Niu, X.; Bruschweiler-Li, L.; Davulcu, O.; Skalicki, J.; Brüschweiler, R.; Chapman, M.S. J. Mol. Biol 2011, 405: 479-496. Arginine kinase: Joint crystallographic and NMR RDC analyses link substrate-associated motions to intrinsic flexibility.

Long, D.; Brüschweiler, R. PLoS Comput. Biol. 2011, 7: e1002035. In silico elucidation of the recognition dynamics of ubiquitin.

Salinas, R.K.; Bruschweiler-Li, L.; Johnson, E.; Brüschweiler, R. J. Biol. Chem. 2011, 286: 32123 – 32131. Ca2+ binding alters the interdomain flexibility between the two cytoplasmic calcium-binding domains in the Na+/Ca2+ exchanger.

Long, D.; Li, D.-W.; Walter, K. F.; Griesinger, C.; Brüschweiler, R. Biophys. J. 2011, 101: 910-915. Toward a predictive understanding of slow methyl group dynamics in proteins.

Bingol, K.; Brüschweiler, R., Anal. Chem. 2011, 3, 7412-7417. Deconvolution of Chemical Mixtures with High Complexity by NMR Consensus Trace Clustering.

Long, D.; Brüschweiler, R. J. Am. Chem. Soc. 2011, 133: 18999-19005. Atomistic kinetic model for population shift and allostery in biomolecules.

Shan, B.; Li, D.-W.; Bruschweiler-Li, L.; Brüschweiler, R. J. Chem. Biol. 2012, 287: 30376-30384. Competitive binding between dynamic p53 transactivation subdomains to human MDM2: Implications for regulating the p53:MDM2/MDMX interaction.

Long, D; Brüschweiler, R. J. Phys. Chem. Letters 2012, 3: 1722-1726. Structural and entropic allosteric signal transduction strength via correlated motions.

Li, D-W.; Brüschweiler, R. J. Chem. Theor. Comput. 2012, 8: 2531-2539. Dynamic and thermodynamic signatures of native and non-native protein states with application to the improvement of protein structures.

D.-W. Li and R. Brüschweiler, J Biomol NMR. 2012, 3: 257-265. PPM: a side-chain and backbone chemical shift predictor for the assessment of protein conformational ensembles.

Larion, M.; Salinas, R.K.; Bruschweiler-Li, L; Miller, B.; Brüschweiler, R. PLoS Biology 2012, 10: e1001452. Order-disorder transitions govern kinetic cooperativity and allostery of monomeric human glucokinase.

Anderson, K.M.; Esadze, A.; Manoharan, M.; Brüschweiler, R.; Gorenstein, D.G.; Iwahara, J. J. Am. Chem. Soc. 2013, 135: 3613-3619. Direct observation of the ion-pair dynamics at a protein-DNA interface by NMR spectroscopy.

Long, D.; Brüschweiler, R. Angew. Chem. 2013, 52: 3709-3711. Directional selection precedes conformational selection in ubiquitin-UIM binding.

Li, D.-W.; Brüschweiler, R. J. Chem. Theory Comput. 2014, 10: 1781–1787. Protocol To Make Protein NMR Structures Amenable to Stable Long Time Scale Molecular Dynamics Simulations.

Bingol, K.; Zhang, F.; Bruschweiler-Li, L.; Brüschweiler, R. J. Am. Chem. Soc. 2012, 21: 9006-9011. Carbon Backbone Topology of the Metabolome of a Cell.

Bingol, K.; Zhang, F.; Bruschweiler-Li, L.; Brüschweiler, R., Anal. Chem. 2012, 84: 9395-9401.TOCCATA, A Customized Carbon Total Correlation Spectroscopy NMR Metabolomics Database.

Bingol, K.; Zhang, F.; Bruschweiler-Li, L.; Brüschweiler, R., Anal. Chem. 2013, 85: 6414-6420. Quantitative analysis of metabolic mixtures by 2D 13C constant-time TOCSY NMR spectroscopy.