Covariance spectroscopy in high-resolution multi-dimensional solid-state NMR

Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction

A single experimental method alone often fails to provide the resolution, accuracy, and coverage needed to model integral membrane proteins (IMPs). Integrating computation with experimental data is a powerful approach to supplement missing structural information with atomic detail. We combine RosettaNMR with experimentally-derived paramagnetic NMR restraints to guide membrane protein structure prediction. We demonstrate this approach using the disulfide bond formation protein B (DsbB), an α-helical IMP. Here, we attached a cyclen-based paramagnetic lanthanide tag to an engineered non-canonical amino acid (ncAA) using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry reaction. Using this tagging strategy, we collected 203 backbone HN pseudocontact shifts (PCSs) for three different labeling sites and used these as input to guide de novo membrane protein structure prediction protocols in Rosetta. We find that this sparse PCS dataset combined with 44 long-range NOEs as restraints in our calculations improves structure prediction of DsbB by enhancements in model accuracy, sampling, and scoring. The inclusion of this PCS dataset improved the Cα-RMSD transmembrane segment values of the best-scoring and best-RMSD models from 9.57 Å and 3.06 Å (no NMR data) to 5.73 Å and 2.18 Å, respectively.

Covariance NMR: Theoretical concerns, practical considerations, contemporary applications and related techniques

The family of resolution enhancement and spectral reconstruction techniques collectively known as covariance NMR continues to expand, along with the list of applications for these techniques. Recent advances in covariance NMR include the utilization of covariance to reconstruct pure shift NMR spectra, and the growing use of covariance NMR in processing non-uniformly sampled data, especially in solid state NMR and metabolomics. This review describes theoretical and practical considerations for direct and indirect covariance NMR techniques, and summarizes recent additions to the covariance NMR family. The review also outlines some of the applications of covariance NMR, and places covariance NMR in the larger context of methods that use statistical and algebraic approaches to enhance and combine various kinds of spectroscopic data, including tensor-based approaches for multidimensional NMR and heterocovariance spectroscopy.

T2* weighted Deconvolution of NMR Spectra: Application to 2D Homonuclear MAS Solid-State NMR of Membrane Proteins

2D homonuclear NMR spectroscopy is an essential technique to characterize small and large molecules, such as organic compounds, metabolites, and biomacromolecules at atomic resolution. However, for complex samples 2D homonuclear spectra display poor resolution, making spectral assignment very cumbersome. Here, we propose a new method that exploits the differential T2* relaxation times of individual resonances and resolves the 2D NMR peaks into pseudo-3D spectra, where time is the 3rd dimension. T2* weIghted DEconvolution or TIDE analyzes individual free induction decays (FIDs) and dissects them into sub-FIDs that are transformed into pseudo-3D spectra combining Fourier transformation and covariance NMR. TIDE achieves higher resolution and sensitivity for NMR spectra than classical covariance NMR reducing offset-dependent artifacts. We demonstrate the performance of TIDE for magic angle spinning (MAS) [13C,13C]-DARR NMR spectra of single- and multi-span membrane proteins embedded in lipid bilayers. Since TIDE is applicable to all type of homonuclear correlation experiments for liquid and solid samples, we anticipate that it will be a general method for processing NMR data of biomacromolecules, complex mixtures of metabolites as well as material samples.

Inner-product NMR spectroscopy: A variant of covariance NMR spectroscopy

We propose a variant of covariance NMR spectroscopy, namely, inner-product NMR spectroscopy, originally suggested in Takeda (2015). The mathematical operation of inner-product NMR is the same as that of covariance NMR, except that subtraction of the average value of the variable is intentionally omitted, so that the correspondence of the spectrum with that of conventional two-dimensional Fourier-transformation is established without having to request the average to become vanishingly small. We demonstrate inner-product NMR for ¹³C DARR correlation experiments in a polycrystalline sample of ¹³C-labeled l-alanine. In covariance, we show that the mixing-time dependence of the peaks is influenced considerably by the choice of the carrier frequency and thereby the center of the spectrum, whereas the inner-product approach is free from such an undesirable effect, while keeping the merit of the covariance NMR.

Applications of NMR to membrane proteins

Membrane proteins present a challenge for structural biology. In this article, we review some of the recent developments that advance the application of NMR to membrane proteins, with emphasis on structural studies in detergent-free, lipid bilayer samples that resemble the native environment. NMR spectroscopy is not only ideally suited for structure determination of membrane proteins in hydrated lipid bilayer membranes, but also highly complementary to the other principal techniques based on X-ray and electron diffraction. Recent advances in NMR instrumentation, spectroscopic methods, computational methods, and sample preparations are driving exciting new efforts in membrane protein structural biology.

Fast acquisition of multidimensional NMR spectra of solids and mesophases using alternative sampling methods

Unique information about the atom-level structure and dynamics of solids and mesophases can be obtained by the use of multidimensional nuclear magnetic resonance (NMR) experiments. Nevertheless, the acquisition of these experiments often requires long acquisition times. We review here alternative sampling methods, which have been proposed to circumvent this issue in the case of solids and mesophases. Compared to the spectra of solutions, those of solids and mesophases present some specificities because they usually display lower signal-to-noise ratios, non-Lorentzian line shapes, lower spectral resolutions and wider spectral widths. We highlight herein the advantages and limitations of these alternative sampling methods. A first route to accelerate the acquisition time of multidimensional NMR spectra consists in the use of sparse sampling schemes, such as truncated, radial or random sampling ones. These sparsely sampled datasets are generally processed by reconstruction methods differing from the Discrete Fourier Transform (DFT). A host of non-DFT methods have been applied for solids and mesophases, including the G-matrix Fourier transform, the linear least-square procedures, the covariance transform, the maximum entropy and the compressed sensing. A second class of alternative sampling consists in departing from the Jeener paradigm for multidimensional NMR experiments. These non-Jeener methods include Hadamard spectroscopy as well as spatial or orientational encoding of the evolution frequencies. The increasing number of high field NMR magnets and the development of techniques to enhance NMR sensitivity will contribute to widen the use of these alternative sampling methods for the study of solids and mesophases in the coming years.

Proton-detected 3D (1)H/(13)C/(1)H correlation experiment for structural analysis in rigid solids under ultrafast-MAS above 60 kHz

A proton-detected 3D (1)H/(13)C/(1)H chemical shift correlation experiment is proposed for the assignment of chemical shift resonances, identification of (13)C-(1)H connectivities, and proximities of (13)C-(1)H and (1)H-(1)H nuclei under ultrafast magic-angle-spinning (ultrafast-MAS) conditions. Ultrafast-MAS is used to suppress all anisotropic interactions including (1)H-(1)H dipolar couplings, while the finite-pulse radio frequency driven dipolar recoupling (fp-RFDR) pulse sequence is used to recouple dipolar couplings among protons and the insensitive nuclei enhanced by polarization transfer technique is used to transfer magnetization between heteronuclear spins. The 3D experiment eliminates signals from non-carbon-bonded protons and non-proton-bonded carbons to enhance spectral resolution. The 2D (F1/F3) (1)H/(1)H and 2D (13)C/(1)H (F2/F3) chemical shift correlation spectra extracted from the 3D spectrum enable the identification of (1)H-(1)H proximity and (13)C-(1)H connectivity. In addition, the 2D (F1/F2) (1)H/(13)C chemical shift correlation spectrum, incorporated with proton magnetization exchange via the fp-RFDR recoupling of (1)H-(1)H dipolar couplings, enables the measurement of proximities between (13)C and even the remote non-carbon-bonded protons. The 3D experiment also gives three-spin proximities of (1)H-(1)H-(13)C chains. Experimental results obtained from powder samples of L-alanine and L-histidine ⋅ H2O ⋅ HCl demonstrate the efficiency of the 3D experiment.

Magic angle spinning NMR of viruses

Viruses, relatively simple pathogens, are able to replicate in many living organisms and to adapt to various environments. Conventional atomic-resolution structural biology techniques, X-ray crystallography and solution NMR spectroscopy provided abundant information on the structures of individual proteins and nucleic acids comprising viruses; however, viral assemblies are not amenable to analysis by these techniques because of their large size, insolubility, and inherent lack of long-range order. In this article, we review the recent advances in magic angle spinning NMR spectroscopy that enabled atomic-resolution analysis of structure and dynamics of large viral systems and give examples of several exciting case studies.