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ZZ-exchange spectroscopy is widely used to study slow exchange processes in biomolecules, especially determination of exchange rates and assignment of minor peaks. However, if the exchange cross peaks overlap or the populations are skewed, kinetic analysis is hindered. In order to analyze slow exchange protein dynamics under such conditions, here we have developed a new method by combining ZZ-exchange and F1F2-selective NMR spectroscopy. We demonstrate the utility of this method by examining the monomer-dimer transition of the ubiquitin-associated domain of p62, successfully assigning the minor (monomeric) peaks and obtaining the exchange rates, which cannot be achieved by ZZ-exchange alone.

ZZ-exchange spectroscopy is widely used to study slow exchange processes in biomolecules, especially determination of exchange rates and assignment of minor peaks. However, if the exchange cross peaks overlap or the populations are skewed, kinetic analysis is hindered. In order to analyze slow exchange protein dynamics under such conditions, here we have developed a new method by combining ZZ-exchange and F

Fourier transform NMR spectroscopy has provided unprecedented insight into the structure, interaction and dynamic motion of proteins and nucleic acids. Conventional biomolecular NMR relies on the acquisition of three-dimensional and four-dimensional (4D) data matrices to establish correlations between chemical shifts in the frequency domains F 1, F 2, F 3 and F 1, F 2, F 3, F 4 respectively. While rich in information, these datasets require a substantial amount of acquisition time, are visually highly unintuitive, require expert knowledge to process, and sample dark and bright regions of the frequency domains equally. Here, we present an alternative approach to obtain multidimensional chemical shift correlations for biomolecules. This strategy focuses on one narrow frequency range, F 1 F 2, at a time and records the resulting F 3 F 4 correlation spectrum by two-dimensional NMR. As a result, only regions of the frequency domain that contain signals in F 1 F 2 (“bright regions”) are sampled. F 1 F 2 selection is achieved by Hartmann–Hahn cross-polarization using weak radio frequency fields. This approach reveals information equivalent to that of a conventional 4D experiment, while the dimensional reduction may shorten the total acquisition time and simplifies spectral processing, interpretation and comparative analysis. Potential applicability of the F 1 F 2-selective approach is illustrated by de novo assignment, structural and dynamics studies of ubiquitin and fatty-acid binding protein 4 (FABP4). Further extension of this concept may spawn new selective NMR experiments to aid studies of site-specific structural dynamics, protein–protein interactions and allosteric modulation of protein structure.

It is becoming increasingly apparent that proteins are not static entities and that their function often critically depends on accurate sampling of multiple conformational states in aqueous solution. Accordingly, the development of methods to study conformational states in proteins beyond their ground-state structure (“excited states”) has crucial biophysical importance. Here we investigate experimental schemes for optimally probing chemical exchange processes in proteins on the micro- to millisecond timescale by 15N R 1ρ relaxation dispersion. The schemes use selective Hartmann–Hahn cross-polarization (CP) transfer for excitation, and derive peak integrals from 1D NMR spectra (Korzhnev et al. in J Am Chem Soc 127:713–721, 2005; Hansen et al. in J Am Chem Soc 131:3818–3819, 2009). Simulation and experiment collectively show that in such CP-based schemes care has to be taken to achieve accurate suppression of undesired off-resonance coherences, when using weak spin-lock fields. This then (i) ensures that relaxation dispersion profiles in the absence of chemical exchange are flat, and (ii) facilitates extraction of relaxation dispersion profiles in crowded regions of the spectrum. Further improvement in the quality of the experimental data is achieved by recording the free-induction decays in an interleaved manner and including a heating-compensation element. The reported considerations will particularly benefit the use of CP-based R 1ρ relaxation dispersion to analyze conformational exchange processes in larger proteins, where resonance line overlap becomes the main limiting factor.

Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

Fourier transform NMR spectroscopy has provided unprecedented insight into the structure, interaction and dynamic motion of proteins and nucleic acids. Conventional biomolecular NMR relies on the acquisition of three-dimensional and four-dimensional (4D) data matrices to establish correlations between chemical shifts in the frequency domains F

It is becoming increasingly apparent that proteins are not static entities and that their function often critically depends on accurate sampling of multiple conformational states in aqueous solution. Accordingly, the development of methods to study conformational states in proteins beyond their ground-state structure ("excited states") has crucial biophysical importance. Here we investigate experimental schemes for optimally probing chemical exchange processes in proteins on the micro- to millisecond timescale by

Relaxation dispersion spectroscopy is one of the most widely used techniques for the analysis of protein dynamics. To obtain a detailed understanding of the protein function from the view point of dynamics, it is essential to fit relaxation dispersion data accurately. The grid search method is commonly used for relaxation dispersion curve fits, but it does not always find the global minimum that provides the best-fit parameter set. Also, the fitting quality does not always improve with increase of the grid size although the computational time becomes longer. This is because relaxation dispersion curve fitting suffers from a local minimum problem, which is a general problem in non-linear least squares curve fitting. Therefore, in order to fit relaxation dispersion data rapidly and accurately, we developed a new fitting program called GLOVE that minimizes global and local parameters alternately, and incorporates a Monte-Carlo minimization method that enables fitting parameters to pass through local minima with low computational cost. GLOVE also implements a random search method, which sets up initial parameter values randomly within user-defined ranges. We demonstrate here that the combined use of the three methods can find the global minimum more rapidly and more accurately than grid search alone.

We developed a new method to elucidate the binding kinetics k(on) and k(off), and the dissociation constant K(D) (=k(off)/k(on)), of protein-protein interactions without observable bound resonances of the protein of interest due to high molecular weight in a complex with a large target protein. In our method, k(on) and k(off) rates are calculated from the analysis of longitudinal relaxation rates of free resonances measured for multiple samples containing different concentration ratios of (15)N-labeled protein and substoichiometric amounts of the target protein. The method is applicable to interactions that cannot be analyzed by relaxation dispersion spectroscopy due to slow interactions on millisecond to second timescale and/or minimal conformational (chemical shift) change upon binding. We applied the method to binding of the B1 domain of protein G (GB1) to immunoglobulin G, and derived the binding kinetics despite the absence of observable bound GB1 resonances.