Non-uniform sampling: post-Fourier era of NMR data collection and processing

Unlocking the Potential of Water-Insoluble Natural Polymers: Isolation, Characterization, and 2D NMR Quantification of cis-1,4-Poly-β-myrcene in Chios Mastic Gum

Natural polymers have garnered attention due to their unique properties, i.e., structural versatility, biocompatibility, and modifiability. Recent efforts focus on sustainable raw materials to develop environmentally friendly processes and products that align with global sustainability goals. Among these, Chios mastic gum, derived from the mastic tree (Pistacia lentiscus var. Chia), is notable for its diverse food, pharmaceutical, and cosmetics applications. One of its key components is cis-1,4-poly-β-myrcene, a natural polyterpene polymer, constituting 20-30% of the resin's composition. Despite its potential, the complex composition of Chios mastic gum poses challenges in extracting, isolating, and quantifying its polymeric content. NMR spectroscopy offers a nondestructive approach and may be instrumental in developing standardized methods for quantifying cis-1,4-poly-β-myrcene in Chios mastic gum. Such methods are vital for understanding the resin's composition and exploring potential applications, particularly in sustainable materials and biomedical fields. This study addresses these challenges by producing a cis-1,4-poly-β-myrcene sample as a standard in quantification procedures. Centrifugal partition chromatography, a support-free liquid-liquid chromatography technique, was employed to purify the polymeric fraction. The polymer was then characterized through size exclusion chromatography and NMR methods, including DOSY and quantitative HSQC experiments, to facilitate an accurate analysis and open the door to further applications of this natural polymer.

The NOAH HSQC-COSY module revisited: A theoretical and practical comparison of pulse sequences

NMR supersequences, as exemplified by the NOAH (NMR by Ordered Acquisition using 1H detection) technique, are a powerful way of acquiring multiple 2D data sets in much shorter durations. This is accomplished through targeted excitation and detection of the magnetisation belonging to specific isotopologues ('magnetisation pools'). Separately, the HSQC-COSY experiment has recently seen an increase in popularity due to the high signal dispersion in the indirect dimension and the removal of ambiguity traditionally associated with HSQC-TOCSY experiments. Here, we describe how the HSQC-COSY experiment can be integrated as a 'module' within NOAH supersequences. The benefits and drawbacks of several different pulse sequence implementations are discussed, with a particular focus on how sensitivities of other modules in the same supersequence are affected.

Influence of Solvent Polarity on the Conformer Ratio of Bicalutamide in Saturated Solutions: Insights from NOESY NMR Analysis and Quantum-Chemical Calculations

The study presents a thorough and detailed analysis of bicalutamide's structural and conformational properties. Quantum chemical calculations were employed to explore the conformational properties of the molecule, identifying significant energy differences between conformers. Analysis revealed that hydrogen bonds stabilise the conformers, with notable variations in torsion angles. Conformers were classified into 'closed' and 'open' types based on the relative orientation of the cyclic fragments. NOE spectroscopy in different solvents (CDCl3 and DMSO-d6) was used to study the conformational preferences of the molecule. NOESY experiments provided the predominance of 'closed' conformers in non-polar solvents and a significant presence of 'open' conformers in polar solvents. The proportions of open conformers were 22.7 ± 3.7% in CDCl3 and 59.8 ± 6.2% in DMSO-d6, while closed conformers accounted for 77.3 ± 3.7% and 40.2 ± 6.2%, respectively. This comprehensive study underscores the solvent environment's impact on its structural behaviour. The findings significantly contribute to a deeper understanding of conformational dynamics, stimulating further exploration in drug development.

Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction

Chemical shift assignment is vital for nuclear magnetic resonance (NMR)-based studies of protein structures, dynamics, and interactions, providing crucial atomic-level insight. However, obtaining chemical shift assignments is labor intensive and requires extensive measurement time. To address this limitation, we previously proposed ARTINA, a deep learning method for automatic assignment of two-dimensional (2D)-4D NMR spectra. Here, we present an integrative approach that combines ARTINA with AlphaFold and UCBShift, enabling chemical shift assignment with reduced experimental data, increased accuracy, and enhanced robustness for larger systems, as presented in a comprehensive study with more than 5000 automated assignment calculations on 89 proteins. We demonstrate that five 3D spectra yield more accurate assignments (92.59%) than pure ARTINA runs using all experimentally available NMR data (on average 10 3D spectra per protein, 91.37%), considerably reducing the required measurement time. We also showcase automated assignments of only 15N-labeled samples, and report improved assignment accuracy in larger synthetic systems of up to 500 residues.

GRIN-toolbox: A versatile and light toolbox for NMR inversion

NMR technique serves as a powerful analytical tool with diverse applications in fields such as chemistry, biology, and material science. However, the effectiveness of NMR heavily relies on data post-processing which is often modeled as regularized inverse problem. Recently, we proposed the Generally Regularized INversion (GRIN) algorithm and demonstrated its effectiveness in NMR data processing. GRIN has been integrated as a friendly graphic user interface-based toolbox which was not detailed in the original paper. In this paper, to make GRIN more practically accessible to NMR practitioners, we focus on introducing the usage of GRIN-Toolbox with processing examples and the corresponding processing graphic interfaces, and the user manual is attached as Supplementary Material. GRIN-Toolbox is versatile and lightweight, where various kinds of data processing tasks can be completed with one click, including but not limited to diffusion-ordered spectroscopy processing, magnetic resonance imaging under-sampling reconstruction, Laplace (diffusion or relaxation) NMR inversion, spectrum denoising, etc. In addition, GRIN-Toolbox could be extended to more applications with user-designed inversion models and freely available at https://github.com/EricLin1993/GRIN.

nus-tool: A unified program for generating and analyzing sample schedules for nonuniformly sampled NMR experiments

Increases in digital resolution achieved by high-field NMR require increases in spectral width. Additionally, the ability to resolve two overlapping peaks requires a sufficiently long acquisition time. These constraints combine, so that achieving high resolution spectra on high-field magnets requires long experiment times when employing uniform sampling and Fourier Transform processing. These limitations may be addressed by using nonuniform sampling (NUS), but the complexity of the parameter space across the variety of available NUS schemes greatly hinders the establishment of optimal approaches and best practices. We address these challenges with nus-tool, which is a software package for generating and analyzing NUS schedules. The nus-tool software internally implements random sampling and exponentially biased sampling. Through pre-configured plug-ins, it also provides access to quantile sampling and Poisson gap sampling. The software computes the relative sensitivity, mean evolution time, point spread function, and peak-to-sidelobe ratio; all of which can be determined for a candidate sample schedule prior to running an experiment to verify expected sensitivity, resolution, and artifact suppression. The nus-tool package is freely available on the NMRbox platform through an interactive GUI and via the command line, which is especially useful for scripted workflows that investigate the effectiveness of various NUS schemes.

Application of Spectroscopy Techniques for Monitoring (Bio)Catalytic Processes in Continuously Operated Microreactor Systems

In the last twenty years, the application of microreactors in chemical and biochemical industrial processes has increased significantly. The use of microreactor systems ensures efficient process intensification due to the excellent heat and mass transfer within the microchannels. Monitoring the concentrations in the microchannels is critical for a better understanding of the physical and chemical processes occurring in micromixers and microreactors. Therefore, there is a growing interest in performing in-line and on-line analyses of chemical and/or biochemical processes. This creates tremendous opportunities for the incorporation of spectroscopic detection techniques into production and processing lines in various industries. In this work, an overview of current applications of ultraviolet–visible, infrared, Raman spectroscopy, NMR, MALDI-TOF-MS, and ESI-MS for monitoring (bio)catalytic processes in continuously operated microreactor systems is presented. The manuscript includes a description of the advantages and disadvantages of the analytical methods listed, with particular emphasis on the chemometric methods used for spectroscopic data analysis.

Primary Structure of Glycans by NMR Spectroscopy

Glycans, carbohydrate molecules in the realm of biology, are present as biomedically important glycoconjugates and a characteristic aspect is that their structures in many instances are branched. In determining the primary structure of a glycan, the sugar components including the absolute configuration and ring form, anomeric configuration, linkage(s), sequence, and substituents should be elucidated. Solution state NMR spectroscopy offers a unique opportunity to resolve all these aspects at atomic resolution. During the last two decades, advancement of both NMR experiments and spectrometer hardware have made it possible to unravel carbohydrate structure more efficiently. These developments applicable to glycans include, inter alia, NMR experiments that reduce spectral overlap, use selective excitations, record tilted projections of multidimensional spectra, acquire spectra by multiple receivers, utilize polarization by fast-pulsing techniques, concatenate pulse-sequence modules to acquire several spectra in a single measurement, acquire pure shift correlated spectra devoid of scalar couplings, employ stable isotope labeling to efficiently obtain homo- and/or heteronuclear correlations, as well as those that rely on dipolar cross-correlated interactions for sequential information. Refined computer programs for NMR spin simulation and chemical shift prediction aid the structural elucidation of glycans, which are notorious for their limited spectral dispersion. Hardware developments include cryogenically cold probes and dynamic nuclear polarization techniques, both resulting in enhanced sensitivity as well as ultrahigh field NMR spectrometers with a 1H NMR resonance frequency higher than 1 GHz, thus improving resolution of resonances. Taken together, the developments have made and will in the future make it possible to elucidate carbohydrate structure in great detail, thereby forming the basis for understanding of how glycans interact with other molecules.

NMR-Based Chromatography Readouts: Indispensable Tools to “Translate” Analytical Features into Molecular Structures

Gaining structural information is a must to allow the unequivocal structural characterization of analytes from natural sources. In liquid state, NMR spectroscopy is almost the only possible alternative to HPLC-MS and hyphenating the effluent of an analyte separation device to the probe head of an NMR spectrometer has therefore been pursued for more than three decades. The purpose of this review article was to demonstrate that, while it is possible to use mass spectrometry and similar methods to differentiate, group, and often assign the differentiating variables to entities that can be recognized as single molecules, the structural characterization of these putative biomarkers usually requires the use of NMR spectroscopy.

Interdomain Dynamics via Paramagnetic NMR on the Highly Flexible Complex Calmodulin/Munc13-1

Paramagnetic NMR constraints are very useful to study protein interdomain motion, but their interpretation is not always straightforward. On the example of the particularly flexible complex Calmodulin/Munc13-1, we present a new approach to characterize this motion with pseudocontact shifts and residual dipolar couplings. Using molecular mechanics, we sampled the conformational space of the complex and used a genetic algorithm to find ensembles that are in agreement with the data. We used the Bayesian information criterion to determine the ideal ensemble size. This way, we were able to make an accurate, unambiguous, reproducible model of the interdomain motion of Calmodulin/Munc13-1 without prior knowledge about the domain orientation from crystallography.

NOAH-(15N/13C)-CEST NMR supersequence for dynamics studies of biomolecules

An NMR supersequence is introduced for the rapid acquisition of ¹⁵N-CEST and methyl-¹³C-CEST experiments in the same pulse sequence for applications to proteins. The high sensitivity and accuracy allows the simultaneous quantitative characterization of backbone and side-chain dynamics on the millisecond timescale ideal for routine screening for alternative protein states.

Enhanced Nuclear Magnetic Resonance Spectroscopy with Isotropic Mixing as a Pseudodimension

Chemical analysis based on liquid-state nuclear magnetic resonance spectroscopy exploits numerous observables, mainly chemical shifts, relaxation rates, and internuclear coupling constants. Regarding the latter, the efficiencies of internuclear coherence transfers may be encoded in spectral peak intensities. The dependencies of these intensities on the experimental parameter that influences the transfer, for example, mixing time, are an important source of structural information. Yet, they are costly to measure and difficult to analyze. Here, we show that peak intensity build-up curves in two-dimensional total correlation spectroscopy (2D TOCSY) experiments may be quickly measured by employing nonuniform sampling and that their analysis can be effective if supported by quantum mechanical calculations. Thus, such curves can be used to form a new, third pseudodimension of the TOCSY spectrum. Similarly to the other two frequency dimensions, this one also resolves ambiguities and provides characteristic information. We show how the approach supports the analysis of a fragment of protein Tau Repeat-4 domain. Yet, its potential applications are far broader, including the analysis of complex mixtures or other polymers.

Use of Diethanolamine as a Viscous Solvent for Mixture Analysis by Multidimensional Heteronuclear ViscY NMR Experiments

Diethanolamine/DMSO-d₆ as a viscous binary solvent is first reported for the individualization of low-polarity mixture components by multidimensional heteronuclear ViscY NMR experiments under spin diffusion conditions. Solvent viscosity induces the slowing down of molecular tumbling, hence promoting magnetization transfer by dipolar longitudinal cross-relaxation. As a result, all ¹H nuclei resonances within the same molecule may correlate in a 2D nuclear Overhauser effect spectroscopy (NOESY) spectrum, giving access to mixture analysis. We offer a new way to analyze mixtures by considering 3D heteronuclear heteronuclear single-quantum coherence-NOESY (HSQC-NOESY) experiments under viscous conditions. We state the individualization of four low-polarity chemical compounds dissolved in the diethanolamine/DMSO-d₆ solvent blend using homonuclear selective 1D, 2D ¹H-¹H NOESY experiments and heteronuclear 1D, 2D ¹H-¹⁹F heteronuclear Overhauser effect spectroscopy, 2D ¹H-¹⁹F, ¹H-³¹P HSQC-NOESY, and 3D ¹H-¹⁹F-¹H, ¹H-³¹P-¹H HSQC-NOESY experiments by taking profit from spin diffusion.

Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra

Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) designed for spectral peak picking are capable of deconvoluting highly crowded NMR spectra rivaling the facilities of human experts. Superior DNN-based peak picking is one of a series of critical steps during NMR spectral processing, analysis, and interpretation where machine learning is expected to have a major impact. In this perspective, we lay out some of the unique strengths as well as challenges of machine learning approaches in this new era of automated NMR spectral analysis. Such a discussion seems timely and should help define common goals for the NMR community, the sharing of software tools, standardization of protocols, and calibrate expectations. It will also help prepare for an NMR future where machine learning and artificial intelligence tools will be common place.

Radio Signals from Live Cells: The Coming of Age of In-Cell Solution NMR

A detailed knowledge of the complex processes that make cells and organisms alive is fundamental in order to understand diseases and to develop novel drugs and therapeutic treatments. To this aim, biological macromolecules should ideally be characterized at atomic resolution directly within the cellular environment. Among the existing structural techniques, solution NMR stands out as the only one able to investigate at high resolution the structure and dynamic behavior of macromolecules directly in living cells. With the advent of more sensitive NMR hardware and new biotechnological tools, modern in-cell NMR approaches have been established since the early 2000s. At the coming of age of in-cell NMR, we provide a detailed overview of its developments and applications in the 20 years that followed its inception. We review the existing approaches for cell sample preparation and isotopic labeling, the application of in-cell NMR to important biological questions, and the development of NMR bioreactor devices, which greatly increase the lifetime of the cells allowing real-time monitoring of intracellular metabolites and proteins. Finally, we share our thoughts on the future perspectives of the in-cell NMR methodology.

Neural networks in pulsed dipolar spectroscopy: A practical guide

This is a methodological guide to the use of deep neural networks in the processing of pulsed dipolar spectroscopy (PDS) data encountered in structural biology, organic photovoltaics, photosynthesis research, and other domains featuring long-lived radical pairs and paramagnetic metal ions. PDS uses distance dependence of magnetic dipolar interactions; measuring a single well-defined distance is straightforward, but extracting distance distributions is a hard and mathematically ill-posed problem requiring careful regularisation and background fitting. Neural networks do this exceptionally well, but their "robust black box" reputation hides the complexity of their design and training - particularly when the training dataset is effectively infinite. The objective of this paper is to give insight into training against simulated databases, to discuss network architecture choices, to describe options for handling DEER (double electron-electron resonance) and RIDME (relaxation-induced dipolar modulation enhancement) experiments, and to provide a practical data processing flowchart.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

The MYC oncoprotein directly interacts with its chromatin cofactor PNUTS to recruit PP1 phosphatase

Despite MYC dysregulation in most human cancers, strategies to target this potent oncogenic driver remain an urgent unmet need. Recent evidence shows the PP1 phosphatase and its regulatory subunit PNUTS control MYC phosphorylation, chromatin occupancy, and stability, however the molecular basis remains unclear. Here we demonstrate that MYC interacts directly with PNUTS through the MYC homology Box 0 (MB0), a highly conserved region recently shown to be important for MYC oncogenic activity. By NMR we identified a distinct peptide motif within MB0 that interacts with PNUTS residues 1–148, a functional unit, here termed PNUTS amino-terminal domain (PAD). Using NMR spectroscopy we determined the solution structure of PAD, and characterised its MYC-binding patch. Point mutations of residues at the MYC-PNUTS interface significantly weaken their interaction both in vitro and in vivo, leading to elevated MYC phosphorylation. These data demonstrate that the MB0 region of MYC directly interacts with the PAD of PNUTS, which provides new insight into the control mechanisms of MYC as a regulator of gene transcription and a pervasive cancer driver.

Modular Pulse Program Generation for NMR Supersequences

NMR supersequences allow multiple 2D NMR data sets to be acquired in greatly reduced experiment durations through tailored detection of NMR responses within concatenated modules. In NOAH (NMR by Ordered Acquisition using ¹H detection) experiments, up to five modules can be combined (or even more when parallel modules are employed), which in theory leads to thousands of plausible supersequences. However, constructing a pulse program for a supersequence is highly time-consuming, requires specialized knowledge, and is error-prone due to its complexity; this has prevented the true potential of the NOAH concept from being fully realized. We introduce here an online tool named GENESIS (GENEration of Supersequences In Silico), available via https://nmr-genesis.co.uk, which systematically generates pulse programs for arbitrary NOAH supersequences compatible with Bruker spectrometers. The GENESIS website provides a unified “one-stop” interface where users may obtain customized supersequences for specific applications, together with all associated acquisition and processing scripts, as well as detailed instructions for running NOAH experiments. Furthermore, it enables the rapid dissemination of new developments in NOAH sequences, such as new modules or improvements to existing modules. Here, we present several such enhancements, including options for solvent suppression, new modules based on pure shift NMR, and improved artifact reduction in HMBC and HMQC modules.

Lipid Nanodiscs for High-Resolution NMR Studies of Membrane Proteins

Membrane proteins (MPs) play essential roles in numerous cellular processes. Because around 70% of the currently marketed drugs target MPs, a detailed understanding of their structure, binding properties, and functional dynamics in a physiologically relevant environment is crucial for a more detailed understanding of this important protein class. We here summarize the benefits of using lipid nanodiscs for NMR structural investigations and provide a detailed overview of the currently used lipid nanodisc systems as well as their applications in solution-state NMR. Despite the increasing use of other structural methods for the structure determination of MPs in lipid nanodiscs, solution NMR turns out to be a versatile tool to probe a wide range of MP features, ranging from the structure determination of small to medium-sized MPs to probing ligand and partner protein binding as well as functionally relevant dynamical signatures in a lipid nanodisc setting. We will expand on these topics by discussing recent NMR studies with lipid nanodiscs and work out a key workflow for optimizing the nanodisc incorporation of an MP for subsequent NMR investigations. With this, we hope to provide a comprehensive background to enable an informed assessment of the applicability of lipid nanodiscs for NMR studies of a particular MP of interest.

ViscY NMR experiments in phosphoric acid as a viscous solvent for individualization of small molecules within mixtures by spin diffusion

The analysis of small molecules within complex mixtures is a particularly difficult task when dealing with the study of metabolite mixtures or chemical reaction media. This issue has fostered in recent years an active search for effective and practical solutions. In this context, the ViscY NMR approach has been recently proposed. ViscY collectively designates the NMR experiments that take advantage of spin diffusion in highly viscous solvents or solvent blends for the individualization of the NMR spectra of small molecule mixture components. Two viscous media were prepared from ortho-phosphoric acid (85%) solution by dilution with either D2O or DMSO-d6, thus providing solvent blends with slightly different polarities in which all liquid-state NMR experiments can be carried out easily. Two mixtures, one of four structurally close dipeptides and one of four low-polarity phosphorus-containing compounds, were used for the method assessment, using ViscY experiments such as homonuclear selective 1D and 2D 1H NOESY experiments, heteronuclear 2D 1H-15N/1H-31P HSQC-NOESY and 1H-13C/1H-15N/1H-31P NOAH experiments.

Increasing sensitivity and versatility in NMR supersequences with new HSQC-based modules

The sensitivity-enhanced HSQC, as well as HSQC-TOCSY, experiments have been modified for incorporation into NOAH (NMR by Ordered Acquisition using ¹H detection) supersequences, adding diversity for ¹³C and ¹⁵N modules. Importantly, these heteronuclear modules have been specifically tailored to preserve the magnetisation required for subsequent acquisition of other heteronuclear or homonuclear modules in a supersequence. In addition, we present protocols for optimally combining HSQC and HSQC-TOCSY elements within the same supersequences, yielding high-quality 2D spectra suitable for structure characterisation but with greatly reduced experiment durations. We further demonstrate that these time savings can translate to increased detection sensitivity per unit time.

NORD: NO Relaxation Delay NMR Spectroscopy

The novel concept of NORD (NO relaxation delay) NMR spectroscopy is introduced. The idea is to design concatenated experiments in a way that the magnetization used in the first relaxes toward equilibrium during the second and vice versa, thus saving instrument time. Applications include complete well-resolved 1 H-1 H and 1 H-13 C one-bond and long-range correlation maps of an 80 mM solution of a trisaccharide recorded in less than two minutes and hydrocortisone with extensive spectral overlap.

Non-uniform sampling in pulse dipolar spectroscopy by EPR: the redistribution of noise and the optimization of data acquisition

Pulse dipolar spectroscopy (PDS) in Electron Paramagnetic Resonance (EPR) is the method of choice for determining the distance distribution function for mono-, bi- or multi- spin-labeled macromolecules and nanostructures. PDS acquisition schemes conventionally use uniform sampling of the dipolar trace, but non-uniform sampling (NUS) schemes can decrease the total measurement time or increase the accuracy of the resulting distance distributions. NUS requires optimization of the data acquisition scheme, as well as changes in data processing algorithms to accommodate the non-uniformly sampled data. We investigate in silico the applicability of the NUS approach in PDS, considering its effect on random, truncation and sampling noise in the experimental data. Each type of noise in the time-domain data propagates differently and non-uniformly into the distance spectrum as errors in the distance distribution. NUS schemes seem to be a valid approach for increasing sensitivity and/or throughput in PDS by decreasing and redistributing noise in the distance spectrum so that it has less impact on the distance spectrum.

Structural features of the plant N-recognin ClpS1 and sequence determinants in its targets that govern substrate selection

In the N-degron pathway of protein degradation of Escherichia coli, the N-recognin ClpS identifies substrates bearing N-terminal phenylalanine, tyrosine, tryptophan, or leucine and delivers them to the caseinolytic protease (Clp). Chloroplasts contain the Clp system, but whether chloroplastic ClpS1 adheres to the same constraints is unknown. Moreover, the structural underpinnings of substrate recognition are not completely defined. We show that ClpS1 recognizes canonical residues of the E. coli N-degron pathway. The residue in second position influences recognition (especially in N-terminal ends starting with leucine). N-terminal acetylation abrogates recognition. ClpF, a ClpS1-interacting partner, does not alter its specificity. Substrate binding provokes local remodeling of residues in the substrate-binding cavity of ClpS1. Our work strongly supports the existence of a chloroplastic N-degron pathway.

Tailoring the nuclear Overhauser effect for the study of small and medium-sized molecules by solvent viscosity manipulation

The nuclear Overhauser effect (NOE) is a consequence of cross-relaxation between nuclear spins mediated by dipolar coupling. Its sensitivity to internuclear distances has made it an increasingly important tool for the determination of through-space atom proximity relationships within molecules of sizes ranging from the smallest systems to large biopolymers. With the support of sophisticated FT-NMR techniques, the NOE plays an essential role in structure elucidation, conformational and dynamic investigations in liquid-state NMR. The efficiency of magnetization transfer by the NOE depends on the molecular rotational correlation time, whose value depends on solution viscosity. The magnitude of the NOE between ¹H nuclei varies from +50% when molecular tumbling is fast to -100% when it is slow, the latter case corresponding to the spin diffusion limit. In an intermediate tumbling regime, the NOE may be vanishingly small. Increasing the viscosity of the solution increases the motional correlation time, and as a result, otherwise unobservable NOEs may be revealed and brought close to the spin diffusion limit. The goal of this review is to report the resolution of structural problems that benefited from the manipulation of the negative NOE by means of viscous solvents, including examples of molecular structure determination, conformation elucidation and mixture analysis (the ViscY method).

Improved NMR Detection of Phospho-Metabolites in a Complex Mixture

Phosphorylated metabolites are omnipresent in cells, but their analytical characterization faces several technical hurdles. Here, we detail an improved NMR workflow aimed at assigning the high-resolution subspectrum of the phospho-metabolites in a complex mixture. Combining a pure absorption J-resolved spectrum (Pell, A. J.; J. Magn. Reson. 2007, 189 (2), 293-299) with alternate on- and off-switching of the ³¹P coupling interaction during the t₁ evolution with a pure in-phase (PIP) HSQMBC experiment (Castañar, L.; Angew. Chem., Int. Ed. 2014, 53 (32), 8379-8382) without or with total correlation spectroscopy (TOCSY) transfer during the insensitive nuclei enhancement by polarization transfer (INEPT) gives access to selective identification of the individual subspectra of the phosphorylated metabolites. Returning to the initial J-res spectra, we can extract with optimal resolution the full trace for the individual phospho-metabolites, which can then be transposed on the high-resolution quantitative one dimensional spectrum.

Hadamard acquisition of 13 C-13 C 2-D correlation NMR spectra

We show that a multiselective excitation with Hadamard encoding is a powerful tool for 2-D acquisition of ¹³ C─¹³ C homonuclear correlations. This method is not designed to improve the sensitivity, but rather to reduce the experiment time, provided there is sufficient sensitivity. Therefore, it allows fast acquisition of such 2-D spectra in labeled molecules. The technique has been demonstrated using a U─¹³ C─¹⁵ N histidine hydrochloride monohydrate sample allowing each point of the build-up curves of the ¹³ C─¹³ C cross-peaks to be recorded within 4 min 35 s, which is very difficult with conventional methods. Using the U─¹³ C─¹⁵ N f-MLF sample, we have demonstrated that the method can be applied to molecules with 14 ¹³ C resonances with a minimum frequency separation of 240 Hz.

Temperature as an Extra Dimension in Multidimensional Protein NMR Spectroscopy

NMR spectroscopy is a particularly informative method for studying protein structures and dynamics in solution; however, it is also one of the most time-consuming. Modern approaches to biomolecular NMR spectroscopy are based on lengthy multidimensional experiments, the duration of which grows exponentially with the number of dimensions. The experimental time may even be several days in the case of 3D and 4D spectra. Moreover, the experiment often has to be repeated under several different conditions, for example, to measure the temperature-dependent effects in a spectrum (temperature coefficients (TCs)). Herein, a new approach that involves joint sampling of indirect evolution times and temperature is proposed. This allows TCs to be measured through 3D spectra in even less time than that needed to acquire a single spectrum by using the conventional approach. Two signal processing methods that are complementary, in terms of sensitivity and resolution, 1) dividing data into overlapping subsets followed by compressed sensing reconstruction, and 2) treating the complete data set with a variant of the Radon transform, are proposed. The temperature-swept 3D HNCO spectra of two intrinsically disordered proteins, osteopontin and CD44 cytoplasmic tail, show that this new approach makes it possible to determine TCs and their non-linearities effectively. Non-linearities, which indicate the presence of a compact state, are particularly interesting. The complete package of data acquisition and processing software for this new approach are provided.

Developing nonuniform sampling strategies to improve sensitivity and resolution in 1,1-ADEQUATE experiments

Nonuniform sampling (NUS) strategies are developed for acquiring highly resolved 1,1-ADEQUATE spectra, in both conventional and homodecoupled (HD) variants with improved sensitivity. Specifically, the quantile-directed and Poisson gap methods were critically compared for distributing the samples nonuniformly, and the quantile schedules were further optimized for weighting. Both maximum entropy and iterative soft thresholding spectral estimation algorithms were evaluated. All NUS approaches were robust when the degree of data reduction is moderate, on the order of a 50% reduction of sampling points. Further sampling reduction by NUS is facilitated by using weighted schedules designed by the quantile method, which also suppresses sampling noise well. Seed independence and the ability to specify the sample weighting in quantile scheduling are important in optimizing NUS for 1,1-ADEQUATE data acquisition. Using NUS yields an improvement in sensitivity, while also making longer evolution times accessible that would be difficult or impractical to attain by uniform sampling. Theoretical predictions for the sensitivity enhancements in these experiments are in the range of 5-20%; NUS is shown to disambiguate weak signals, reveal some ⁿ J_CC correlations obscured by noise, and improve signal strength relative to uniform sampling in the same experimental time. This work presents sample schedule development for applying NUS to challenging experiments. The schedules developed here are made available for general use and should facilitate the broader utilization of ADEQUATE experiments (including 1,1-, 1,n-, and HD- variants) for challenging structure elucidation problems.

Non-Uniform Sampling in NMR Spectroscopy and the Preservation of Spectral Knowledge in the Time and Frequency Domains

The increased sensitivity under weighted non-uniform sampling (NUS) is demonstrated and quantified using Monte Carlo simulations of nuclear magnetic resonance (NMR) time- and frequency-domain signals. The concept of spectral knowledge is introduced and shown to be superior to the frequency-domain signal-to-noise ratio for assessing the quality of NMR data. Two methods for rigorously preserving spectral knowledge and the time-domain NUS knowledge enhancement upon transformation to the frequency domain are demonstrated, both theoretically and numerically. The first, non-uniform weighted sampling using consistent root-mean-square noise, is applicable to data sampled on the Nyquist grid, whereas the second, the block Fourier transform using consistent root-mean-square noise, can be used to transform time-domain data acquired with arbitrary, off-grid NUS.

A brief introduction to the basics of NMR spectroscopy and selected examples of its applications to materials characterization

Nuclear magnetic resonance (NMR) spectroscopy is an analytical technique that gives information on the local magnetic field around atomic nuclei. Since the local magnetic field of the nucleus is directly influenced by such features of the molecular structure as constitution, configuration, conformation, intermolecular interactions, etc., NMR can provide exhaustive information on the chemical structure, which is unrivaled by any other analytical method. Starting from the 1950s, NMR spectroscopy first revolutionized organic chemistry and became an indispensable tool for the structure elucidation of small, soluble molecules. As the technique evolved, NMR rapidly conquered other disciplines of chemical sciences. When the analysis of macromolecules and solids also became feasible, the technique turned into a staple in materials characterization, too. All aspects of NMR spectroscopy, including technical and technological development, as well as its applications in natural sciences, have been growing exponentially since its birth. Hence, it would be impossible to cover, or even touch on, all topics of importance related to this versatile analytical tool. In this tutorial, we aim to introduce the reader to the basic principles of NMR spectroscopy, instrumentation, historical development and currently available brands, practical cost aspects, sample preparation, and spectrum interpretation. We show a number of advanced techniques relevant to materials characterization. Through a limited number of examples from different fields of materials science, we illustrate the immense scope of the technique in the analysis of materials. Beyond our inherently limited introduction, an ample list of references should help the reader to navigate further in the field of NMR spectroscopy.

Signal Deconvolution and Noise Factor Analysis Based on a Combination of Time-Frequency Analysis and Probabilistic Sparse Matrix Factorization

Nuclear magnetic resonance (NMR) spectroscopy is commonly used to characterize molecular complexity because it produces informative atomic-resolution data on the chemical structure and molecular mobility of samples non-invasively by means of various acquisition parameters and pulse programs. However, analyzing the accumulated NMR data of mixtures is challenging due to noise and signal overlap. Therefore, data-cleansing steps, such as quality checking, noise reduction, and signal deconvolution, are important processes before spectrum analysis. Here, we have developed an NMR measurement informatics tool for data cleansing that combines short-time Fourier transform (STFT; a time-frequency analytical method) and probabilistic sparse matrix factorization (PSMF) for signal deconvolution and noise factor analysis. Our tool can be applied to the original free induction decay (FID) signals of a one-dimensional NMR spectrum. We show that the signal deconvolution method reduces the noise of FID signals, increasing the signal-to-noise ratio (SNR) about tenfold, and its application to diffusion-edited spectra allows signals of macromolecules and unsuppressed small molecules to be separated by the length of the T₂* relaxation time. Noise factor analysis of NMR datasets identified correlations between SNR and acquisition parameters, identifying major experimental factors that can lower SNR.

Escherichia coli O176 LPS structure and dynamics: A NMR spectroscopy and MD simulation study

A lipopolysaccharide (LPS) molecule is a key component of the bacterial outer membrane used to protect the bacterium and to interact with the environment. To gain insight into its function, the study of the LPS conformation and dynamics at the molecular and cellular levels is necessary, but these highly diverse and dynamic membrane-LPS systems are difficult to study. In this work, by using NMR spectroscopy and molecular dynamics (MD) simulations, we determined the conformational preferences of an E. coli O176 O-antigen polysaccharide at the atomic level. Moreover, we analyzed the use of non-uniform sampling (NUS) for the acquisition of high dynamic range spectra, like ¹H,¹H-NOESY NMR experiments. A comparison of the effective transglycosidic distances derived from conventional uniformly sampled and NUS ¹H,¹H-NOESY data showed high similarity under equal measuring time conditions. Furthermore, the experimentally derived internuclear distances of the O-antigen polysaccharide with ten repeating units (RUs) showed very good agreement to those calculated from the MD simulations of the same O-antigen polysaccharide in solution. Analysis of the LPS bilayer simulations with five and with ten RUs revealed that, although similar with respect to populated states in solution, the O-antigen in LPS bilayers had more extended chains as a result of spatial limitations due to close packing. Additional MD simulations of O-antigen polysaccharides from E. coli O6 (branched repeating unit) and O91 (negatively charged linear repeating unit) in solution and LPS bilayers were performed and compared to those of O176 (linear polymer). For all three O-antigens, the ensemble of structures present for the polysaccharides in solution were consistent with the results from their ¹H,¹H-NOESY experiments. In addition, the similarities between the O-antigen on its own and as a constituent of the full LPS in bilayer environment makes it possible to realistically describe the LPS conformation and dynamics from the MD simulations.

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Uniform and non-uniform sampled NOESY NMR data yield similar internuclear distances.

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O-antigen internuclear distances from NMR and MD show excellent agreement.

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O-antigen ensemble structures from MD are consistent with NMR observations.

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O-antigen structures are more extended in LPS bilayers than in solution.

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MD simulations can describe realistic LPS conformation and dynamics.

Rapid Biophysical Characterization and NMR Spectroscopy Structural Analysis of Small Proteins from Bacteria and Archaea

Proteins encoded by small open reading frames (sORFs) have a widespread occurrence in diverse microorganisms and can be of high functional importance. However, due to annotation biases and their technically challenging direct detection, these small proteins have been overlooked for a long time and were only recently rediscovered. The currently rapidly growing number of such proteins requires efficient methods to investigate their structure-function relationship. Herein, a method is presented for fast determination of the conformational properties of small proteins. Their small size makes them perfectly amenable for solution-state NMR spectroscopy. NMR spectroscopy can provide detailed information about their conformational states (folded, partially folded, and unstructured). In the context of the priority program on small proteins funded by the German research foundation (SPP2002), 27 small proteins from 9 different bacterial and archaeal organisms have been investigated. It is found that most of these small proteins are unstructured or partially folded. Bioinformatics tools predict that some of these unstructured proteins can potentially fold upon complex formation. A protocol for fast NMR spectroscopy structure elucidation is described for the small proteins that adopt a persistently folded structure by implementation of new NMR technologies, including automated resonance assignment and nonuniform sampling in combination with targeted acquisition.

Purification of native CCL7 and its functional interaction with selected chemokine receptors

Chemokine receptors form a major sub-family of G protein-coupled receptors (GPCRs) and they are involved in a number of cellular and physiological processes related to our immune response and regulation. A better structural understanding of ligand-binding, activation, signaling and regulation of chemokine receptors is very important to design potentially therapeutic interventions for human disorders arising from aberrant chemokine signaling. One of the key limitations in probing the structural details of chemokine receptors is the availability of large amounts of purified, homogenous and fully functional chemokine ligands, and the commercially available products, are not affordable for in-depth structural studies. Moreover, production of uniformly isotope-labeled chemokines, for example, suitable for NMR-based structural investigation, also remains challenging. Here, we have designed a streamlined approach to express and purify the human chemokine CCL7 as well as its ¹⁵N-, ¹⁵N/¹³C-, ²H/¹⁵N/¹³C- isotope-labeled derivatives, at milligram levels using E. coli expression system. Purified CCL7 not only maintains a well-folded three-dimensional structure as analyzed using circular dichroism and ¹H/¹⁵N NMR but it also induces coupling of heterotrimeric G-proteins and β-arrestins for selected chemokine receptors in cellular system. We compared cAMP response induced by histidine tagged CCL7 and native CCL7 and found that modification of the N-terminus of CCL7 compromises its functionality. Our strategy presented here may be applicable to other chemokines and therefore, provide a potentially generic and cost-effective approach to produce chemokines in large amounts for functional and structural studies.

Amino-acid selective isotope labeling enables simultaneous overlapping signal decomposition and information extraction from NMR spectra

Signal overlapping is a major bottleneck for protein NMR analysis. We propose a new method, stable-isotope-assisted parameter extraction (SiPex), to resolve overlapping signals by a combination of amino-acid selective isotope labeling (AASIL) and tensor decomposition. The basic idea of Sipex is that overlapping signals can be decomposed with the help of intensity patterns derived from quantitative fractional AASIL, which also provides amino-acid information. In SiPex, spectra for protein characterization, such as ¹⁵N relaxation measurements, are assembled with those for amino-acid information to form a four-order tensor, where the intensity patterns from AASIL contribute to high decomposition performance even if the signals share similar chemical shift values or characterization profiles, such as relaxation curves. The loading vectors of each decomposed component, corresponding to an amide group, represent both the amino-acid and relaxation information. This information link provides an alternative protein analysis method that does not require "assignments" in a general sense; i.e., chemical shift determinations, since the amino-acid information for some of the residues allows unambiguous assignment according to the dual selective labeling. SiPex can also decompose signals in time-domain raw data without Fourier transform, even in non-uniformly sampled data without spectral reconstruction. These features of SiPex should expand biological NMR applications by overcoming their overlapping and assignment problems.

Enhancing Compression Level for More Efficient Compressed Sensing and Other Lessons from NMR Spectroscopy

Modern nuclear magnetic resonance spectroscopy (NMR) is based on two- and higher-dimensional experiments that allow the solving of molecular structures, i.e., determine the relative positions of single atoms very precisely. However, rich chemical information comes at the price of long data acquisition times (up to several days). This problem can be alleviated by compressed sensing (CS)—a method that revolutionized many fields of technology. It is known that CS performs the most efficiently when measured objects feature a high level of compressibility, which in the case of NMR signal means that its frequency domain representation (spectrum) has a low number of significant points. However, many NMR spectroscopists are not aware of the fact that various well-known signal acquisition procedures enhance compressibility and thus should be used prior to CS reconstruction. In this study, we discuss such procedures and show to what extent they are complementary to CS approaches. We believe that the survey will be useful not only for NMR spectroscopists but also to inspire the broader signal processing community.

Fast time-resolved NMR with non-uniform sampling

NMR spectroscopy is a versatile tool for studying time-dependent processes: chemical reactions, phase transitions or macromolecular structure changes. However, time-resolved NMR is usually based on the simplest among available techniques - one-dimensional spectra serving as "snapshots" of the studied process. One of the reasons is that multidimensional experiments are very time-expensive due to costly sampling of evolution time space. In this review we summarize efforts to alleviate the problem of limited applicability of multidimensional NMR in time-resolved studies. We focus on techniques based on sparse or non-uniform sampling (NUS), which lead to experimental time reduction by omitting a significant part of the data during measurement and reconstructing it mathematically, adopting certain assumptions about the spectrum. NUS spectra are faster to acquire than conventional ones and thus better suited to the role of "snapshots", but still suffer from non-stationarity of the signal i.e. amplitude and frequency variations within a dataset. We discuss in detail how these instabilities affect the spectra, and what are the optimal ways of sampling the non-stationary FID signal. Finally, we discuss related areas of NMR where serial experiments are exploited and how they can benefit from the same NUS-based approaches.

A 300-fold enhancement of imino nucleic acid resonances by hyperpolarized water provides a new window for probing RNA refolding by 1D and 2D NMR

NMR sensitivity-enhancement methods involving hyperpolarized water could be of importance for solution-state biophysical investigations. Hyperpolarized water (HyperW) can enhance the ¹H NMR signals of exchangeable sites by orders of magnitude over their thermal counterparts, while providing insight into chemical exchange and solvent accessibility at a site-resolved level. As HyperW's enhancements are achieved by exploiting fast solvent exchanges associated with minimal interscan delays, possibilities for the rapid monitoring of chemical reactions and biomolecular (re)folding are opened. HyperW NMR can also accommodate heteronuclear transfers, facilitating the rapid acquisition of 2-dimensional (2D) ¹⁵N-¹H NMR correlations, and thereby combining an enhanced spectral resolution with speed and sensitivity. This work demonstrates how these qualities can come together for the study of nucleic acids. HyperW injections were used to target the guanine-sensing riboswitch aptamer domain (GSR^apt) of the xpt-pbuX operon in Bacillus subtilis Unlike what had been observed in proteins, where residues benefited of HyperW NMR only if/when sufficiently exposed to water, these enhancements applied to every imino resonance throughout the RNA. The >300-fold enhancements observed in the resulting ¹H NMR spectra allowed us to monitor in real time the changes that GSR^apt undergoes upon binding hypoxanthine, a high-affinity interaction leading to conformational refolding on a ∼1-s timescale at 36 °C. Structural responses could be identified for several nucleotides by 1-dimensional (1D) imino ¹H NMR as well as by 2D HyperW NMR spectra acquired upon simultaneous injection of hyperpolarized water and hypoxanthine. The folding landscape revealed by this HyperW strategy for GSR^apt, is briefly discussed.

Characterizing Post-Translational Modifications and Their Effects on Protein Conformation Using NMR Spectroscopy

The diversity of the cellular proteome substantially exceeds the number of genes coded by the DNA of an organism because one or more residues in a majority of eukaryotic proteins are post-translationally modified (PTM) by the covalent conjugation of specific chemical groups. We now know that PTMs alter protein conformation and function in ways that are not entirely understood at the molecular level. NMR spectroscopy has been particularly successful as an analytical tool in elucidating the themes underlying the structural role of PTMs. In this Perspective, we focus on the NMR-based characterization of three abundant PTMs: phosphorylation, acetylation, and glycosylation. We detail NMR methods that have found success in detecting these modifications at a site-specific level. We also highlight NMR studies that have mapped the conformational changes ensuing from these PTMs as well as evaluated their relation to function. The NMR toolbox is expanding rapidly with experiments available to probe not only the average structure of biomolecules but also how this structure changes with time on time scales ranging from picoseconds to seconds. The atomic resolution insights into the biomolecular structure, dynamics, and mechanism accessible from NMR spectroscopy ensure that NMR will continue to be at the forefront of research in the structural biology of PTMs.

Triplet NOAH supersequences optimised for small molecule structure characterisation

A series of NMR supersequences are presented for the time-efficient structure characterisation of small molecules in the solution state. These triplet sequences provide HMBC, HSQC, and one homonuclear correlation experiment of choice according to the NMR by Ordered Acquisition using ¹ H detection principle. The experiments are demonstrated to be compatible with non-uniform sampling schemes and may be acquired and processed under full automation.

Extreme Nonuniform Sampling for Protein NMR Dynamics Studies in Minimal Time

NMR spectroscopy is an extraordinarily rich source of quantitative dynamics of proteins in solution using spin relaxation or chemical exchange saturation transfer (CEST) experiments. However, ¹⁵N-CEST measurements require prolonged multidimensional, so-called pseudo-3D HSQC experiments where the pseudo dimension is a radio frequency offset Δω of a weak ¹⁵N saturation field. Nonuniform sampling (NUS) approaches have the potential to significantly speed up these measurements, but they also carry the risk of introducing serious artifacts and the systematic optimization of nonuniform sampling schedules has remained elusive. It is demonstrated here how this challenge can be addressed by using fitted cross-peaks of a reference 2D HSQC experiment as footprints, which are subsequently used to reconstruct cross-peak amplitudes of a pseudo-3D data set as a function of Δω by a linear least-squares fit. It is shown for protein Im7 how the approach can yield highly accurate CEST profiles based on an absolutely minimally sampled (AMS) data set allowing a speed-up of a factor 20-30. Spectrum-specific optimized nonuniform sampling (SONUS) schemes based on the Cramer-Rao lower bound metric were critical to achieve such a performance, revealing also more general properties of optimal sampling schedules. This is the first systematic exploration and optimization of NUS schedules for the dramatic speed-up of quantitative multidimensional NMR measurements that minimize unwanted errors.

Emerging solution NMR methods to illuminate the structural and dynamic properties of proteins

The first recognition of protein breathing was more than 50 years ago. Today, we are able to detect the multitude of interaction modes, structural polymorphisms, and binding-induced changes in protein structure that direct function. Solution-state NMR spectroscopy has proved to be a powerful technique, not only to obtain high-resolution structures of proteins, but also to provide unique insights into the functional dynamics of proteins. Here, we summarize recent technical landmarks in solution NMR that have enabled characterization of key biological macromolecular systems. These methods have been fundamental to atomic resolution structure determination and quantitative analysis of dynamics over a wide range of time scales by NMR. The ability of NMR to detect lowly populated protein conformations and transiently formed complexes plays a critical role in its ability to elucidate functionally important structural features of proteins and their dynamics.

A suite of solid-state NMR experiments to utilize orphaned magnetization for assignment of proteins using parallel high and low gamma detection

We present a suite of two-receiver solid-state NMR experiments for backbone and side chain resonance assignment. The experiments rely on either dipolar coupling or scalar coupling for polarization transfer and are devised to acquire a ¹H-detected 3D experiment AND a nested ¹³C-detected 2D from a shared excitation pulse. In order to compensate for the lower sensitivity of detection on ¹³C nucleus, 2D rows are signal averaged during 3D planes. The 3D dual receiver experiments do not suffer from any appreciable signal loss compared to their single receiver versions and require no extra optimization. The resulting data is higher in information content with no additional experiment time. The approach is expected to become widespread as multiple receivers become standard for new NMR spectrometers.

Nuclear Magnetic Resonance Spectroscopy to Identify Metabolite Biomarkers of Nonresponsiveness to Targeted Therapy in Glioblastoma Tumor Stem Cells

Glioblastoma is the most common and malignant brain tumor, and current therapies confer only modest survival benefits. A major obstacle is our ability to monitor treatment effect on tumors. Current imaging modalities are ambiguous, and repeated biopsies are not encouraged. To scout for markers of treatment response, we used NMR spectroscopy to study the effects of a survivin inhibitor on the metabolome of primary glioblastoma cancer stem cells. Applying high resolution NMR spectroscopy (¹H resonance frequency: 800.03 MHz) to just 3 million cells per sample, we achieved sensitive and high resolving determinations of, e.g., amino acids, nucleosides, and constituents of the citric acid cycle. For control samples that were cultured, prepared, and measured at varying dates, peak area relative standard deviations were 15-20%. Analyses of unfractionated lysates were performed for straightforward compound identification with COLMAR and HMDB databases. Principal component analysis revealed that citrate levels were clearly upregulated in nonresponsive cells, while lactate levels substantially decreased following treatment for both responsive and nonresponsive cells. Hence, lactate and citrate may be potential markers of successful drug uptake and poor response to survivin inhibitors, respectively. Our metabolomics approach provided alternative biomarker candidates compared to spectrometry-based proteomics, underlining benefits of complementary methodologies. These initial findings make a foundation for exploring in vivo MR spectroscopy (MRS) of brain tumors, as citrate and lactate are MRS-visible. In sum, NMR metabolomics is a tool for addressing glioblastoma.