Ultrafast NMR Research Articles

Measuring Protein-Ligand Binding by Hyperpolarized Ultrafast NMR.

Protein-ligand interactions can be detected by observing changes in the transverse relaxation rates of the ligand upon binding. The ultrafast NMR technique, which correlates the chemical shift with the transverse relaxation rate, allows for the simultaneous acquisition of R2 for carbon spins at different positions. In combination with dissolution dynamic nuclear polarization (D-DNP), where the signal intensity is enhanced by thousands of times, the R2 values of several carbon signals from unlabeled benzylamine are observable within a single scan. The hyperpolarized ultrafast chemical shift-R2 correlated experiment separates chemical shift encoding from the readout phase in the NMR pulse sequence, which allows it to beat the fundamental limit on the spectral resolution otherwise imposed by the sampling theorem. Applications enabled by the ability to measure multiple relaxation rates in a single scan include the study of structural properties of protein-ligand interactions.

Increasing particle concentration enhances particle penetration depth but slows down liquid imbibition in thin fibrous filters

The transport of particles within thin, porous media is a complex process which received growing attention due to its applications in filtration, printing and microfluidics devices. The effect of particles on liquid imbibition and particle clogging can reduce the performance and lifetime of these applications. However, these processes are still not clearly understood and are challenging to investigate. The goal of this study is to increase our understanding about the effect of particle concentration on the imbibition process in thin fibrous membrane filters. In this study, an Ultra-Fast Imaging NMR method is used to study the particle penetration inside nylon membrane filters for particle suspensions with varying particle concentrations (C0). The measurements revealed that increasing the particle concentration increases the particle penetration depth S(t) as governed by a Langmuir isotherm given by S(t)=l(t)(1+κC0)/1+κ(C0+Cb,m), with Cb,m the bound particles and κ the binding constant. Secondly, in droplet penetration, particles slow down liquid penetration in a Darcy like manner where effect on viscosity (η) and surface tension (σ) determine the penetration speed rather than changes within permeability (K0). The final liquid front (l), scaled according to l2∝σt/η. The particle penetration depths were verified using scanning electron microscopy images.

Crystal structure validation of verinurad via proton-detected ultra-fast MAS NMR and machine learning.

The recent development of ultra-fast magic-angle spinning (MAS) (>100 kHz) provides new opportunities for structural characterization in solids. Here, we use NMR crystallography to validate the structure of verinurad, a microcrystalline active pharmaceutical ingredient. To do this, we take advantage of 1H resolution improvement at ultra-fast MAS and use solely 1H-detected experiments and machine learning methods to assign all the experimental proton and carbon chemical shifts. This framework provides a new tool for elucidating chemical information from crystalline samples with limited sample volume and yields remarkably faster acquisition times compared to 13C-detected experiments, without the need to employ dynamic nuclear polarization.

Tracking Li atoms in real-time with ultra-fast NMR simulations.

We present for the first time a multiscale machine learning approach to jointly simulate atomic structure and dynamics with the corresponding solid state Nuclear Magnetic Resonance (ssNMR) observables. We study the use-case of spin-alignment echo (SAE) NMR for exploring Li-ion diffusion within the solid state electrolyte material Li3PS4 (LPS) by calculating quadrupolar frequencies of 7Li. SAE NMR probes long-range dynamics down to microsecond-timescale hopping processes. Therefore only a few machine learning force field schemes are able to capture the time- and length scales required for accurate comparison with experimental results. By using a new class of machine learning interatomic potentials, known as ultra-fast potentials (UFPs), we are able to efficiently access timescales beyond the microsecond regime. In tandem, we have developed a machine learning model for predicting the full 7Li electric field gradient (EFG) tensors in LPS. By combining the long timescale trajectories from the UFP with our model for 7Li EFG tensors, we are able to extract the autocorrelation function (ACF) for 7Li quadrupolar frequencies during Li diffusion. We extract the decay constants from the ACF for both crystalline β-LPS and amorphous LPS, and find that the predicted Li hopping rates are on the same order of magnitude as those predicted from the Li dynamics. This demonstrates the potential for machine learning to finally make predictions on experimentally relevant timescales and temperatures, and opens a new avenue of NMR crystallography: using machine learning dynamical NMR simulations for accessing polycrystalline and glass ceramic materials.

Ultra Fast Imaging NMR method for measuring fast transport processes in thin porous media

Measuring moisture distributions during fast transport processes in thin porous media is a challenging task. In this paper, Ultra Fast Imaging (UFI) NMR is proposed as a valuable measurement technique for investigating moisture uptake in porous media by achieving a temporal resolution of 10 ms and spatial resolution between 14.5 and 18 μm. This paper gives a detailed explanation about the methodology and the interpretation of the signal intensity. It is shown that there exist specific T1- and T2− relaxation time conditions for performing UFI experiments with signal-to-noise ratios that are sufficiently high. In most cases, a contrast agent is required to optimize these relaxation times and achieve the optimal measurement conditions. In the first part of this paper, both CuSO4 and Clariscan are discussed as possible contrast agents. Furthermore, it is shown that the signal intensity can be linked to the moisture content for water based liquids. The second part of this paper covers penetration experiments on porous PVDF membranes. These measurements show that the technique is able to measure moisture profiles during fast capillary penetration and allows to extract moisture front positions. Those front positions follow a linear time behavior in PVDF membranes. Lastly the NMR-measurements showed similar results when compared to scanning absorptometry (ASA).

CEST-based detection of labile protons by ultrafast 2D NMR

Chemical exchange saturation transfer (CEST) NMR is widely used for enhancing the sensitivity of low-abundance exchanging sites in general, and for the water-based detection of labile metabolite protons under in vivo conditions in particular. CEST, however, faces a number of limitations when targeting multiple metabolites, including a radiofrequency (RF)-induced broadening of the detected peaks, and relatively long acquisition times deriving from its continuous-wave nature. Methods have been proposed to overcome these limitations, including a Fourier-encoded version of CEST –the Frequency-Labeled EXchange (FLEX) experiment– and the incorporation of background gradients during the RF saturation time. This work explores an alternative avenue, based on spatiotemporally encoded ultrafast (UF) 2D NMR. UF NMR can compress the time-domain indirect-dimension encoding of 2D NMR into a single shot; to exploit these potential time savings, an UF version of the FLEX experiment was taken as starting point, and the multiple t1-incremented amplitude modulation cycles that the FLEX experiment normally requires were replaced by a single-shot spatiotemporal encoding. The ensuing UF 2D FLEX experiment was then used to monitor the spectral signatures of multiple moieties as they exchange with the solvent, by imprinting these onto the water resonance as in the original experiment –but now all within a single shot. Upon incorporating two-scan phase cycling and quadrature detection, the resulting method showed an experimental performance similar to t1-encoded FLEX, while providing significant time savings plus imaging information that could be of further use in in vivo studies. The main advantages, features and drawbacks observed for UF 2D FLEX are briefly discussed.

Sensitive, Efficient and Portable Analysis of Molecular Exchange Processes by Hyperpolarized Ultrafast NMR

AbstractMolecular exchange processes are ubiquitous in nature. Here, we introduce a method to analyze exchange processes by using low‐cost, portable, single‐sided NMR instruments. The inherent magnetic field inhomogeneity of the single‐sided instruments is exploited to achieve diffusion contrast of exchange sites and spatial encoding of 2D data. This so‐called ultrafast diffusion exchange spectroscopy method shortens the experiment time by two to four orders of magnitude. Furthermore, because full 2D data are measured in a single scan (in a fraction of a second), the sensitivity of the experiment can be improved by several orders of magnitude using so‐called nuclear spin hyperpolarization methods (in this case, dissolution dynamic nuclear polarization). As the first demonstration of the feasibility of the method in various applications, we show that the method enables quantification of intra‐ and extracellular exchange of water in a yeast cell suspension.

Sensitive, Efficient and Portable Analysis of Molecular Exchange Processes by Hyperpolarized Ultrafast NMR.

Molecular exchange processes are ubiquitous in nature. Here, we introduce a method to analyze exchange processes by using low‐cost, portable, single‐sided NMR instruments. The inherent magnetic field inhomogeneity of the single‐sided instruments is exploited to achieve diffusion contrast of exchange sites and spatial encoding of 2D data. This so‐called ultrafast diffusion exchange spectroscopy method shortens the experiment time by two to four orders of magnitude. Furthermore, because full 2D data are measured in a single scan (in a fraction of a second), the sensitivity of the experiment can be improved by several orders of magnitude using so‐called nuclear spin hyperpolarization methods (in this case, dissolution dynamic nuclear polarization). As the first demonstration of the feasibility of the method in various applications, we show that the method enables quantification of intra‐ and extracellular exchange of water in a yeast cell suspension.

ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation.

A new tool, ML-J-DP4, provides an efficient and accurate method for determining the most likely structure of complex molecules within minutes using standard computational resources. The workflow involves combining fast Karplus-type J calculations with NMR chemical shifts predictions at the cheapest HF/STO-3G level enhanced using machine learning (ML), all embedded in the J-DP4 formalism. Our ML provides accurate predictions, which compare favorably alongside with other ML methods.

Ultrafast transverse relaxation exchange NMR spectroscopy.

Molecular exchange between different physical or chemical environments occurs due to either diffusion or chemical transformation. Nuclear magnetic resonance (NMR) spectroscopy provides a means of understanding the molecular exchange in a noninvasive way and without tracers. Here, we introduce a novel two dimensional, single-scan ultrafast Laplace NMR (UF LNMR) method to monitor molecular exchange using transverse relaxation as a contrast. The UF T2-T2 relaxation exchange spectroscopy (REXSY) method shortens the experiment time by one to two orders of magnitude compared to its conventional counterpart. Contrary to the conventional EXSY, the exchanging sites are distinguished based on T2 relaxation times instead of chemical shifts, making the method especially useful for systems including physical exchange of molecules. Therefore, the UF REXSY method offers an efficient means for quantification of exchange processes in various fields such as cellular metabolism and ion transport in electrolytes. As a proof of principle, we studied a halogen-free orthoborate based ionic liquid system and followed molecular exchange between molecular aggregates and free molecules. The results are in good agreement with the conventional exchange studies. Due to the single-scan nature, the method potentially significantly facilitates the use of modern hyperpolarization techniques to boost the sensitivity by several orders of magnitude.

Unraveling the Surface Hydroxyl Network on In2O3 Nanoparticles with High-Field Ultrafast Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy.

Hydroxyl groups are among the major active surface sites over metal oxides. However, their spectroscopic characterizations have been challenging due to limited resolutions, especially on hydroxyl-rich surfaces where strong hydroxyl networks are present. Here, using nanostructured In2O3 as an example, we show significantly enhanced discrimination of the surface hydroxyl groups, owing to the high-resolution 1H NMR spectra performed at a high magnetic field (18.8 T) and a fast magic angle spinning (MAS) of up to 60 kHz. A total of nine kinds of hydroxyl groups were distinguished and their assignments (μ1, μ2, and μ3) were further identified with the assistance of 17O NMR. The spatial distribution of these hydroxyl groups was further explored via two-dimensional (2D) 1H-1H homonuclear correlation experiments with which the complex surface hydroxyl network was unraveled at the atomic level. Moreover, the quantitative analysis of these hydroxyl groups with such high resolution enables further investigations into the physicochemical property and catalytic performance characterizations (in CO2 reduction) of these hydroxyl groups. This work provides insightful understanding on the surface structure/property of the In2O3 nanoparticles and, importantly, may prompt general applications of high-field ultrafast MAS NMR techniques in the study of hydroxyl-rich surfaces on other metal oxide materials.

Quadratic spacing of the effective gradient area for spatially encoded diffusion NMR

Diffusion NMR experiments rely on the measurement of signal attenuation as a function of the area of diffusion-encoding pulsed magnetic-field gradients. In conventional experiments, arbitrary series of gradient values can be used, and different gradient spacing strategies have different advantages. Ultrafast diffusion NMR relies on the spatial parallelisation of effective gradient area values to collect full 2D diffusion data sets in a single scan. Until recently, only linear spacing was available. We have shown that quadratic spacing can be achieved using a tailored frequency swept pulse. Here we describe the design of the pulse and validate it with numerical spin simulations, that make it possible to check the effect of the quadratic spacing pulse at different stages of the pulse sequence. We also show that quadratic spacing makes it possible to use a recently reported analysis method for diffusion NMR, the Matrix Pencil Method. We describe the results obtained with the MPM and those obtained with the direct exponential curve resolution algorithm (DECRA), which also requires quadratic gradient spacing. Overall, these developments open new opportunities for applications of spatially encoded diffusion experiments, such as ultrafast DOSY NMR and ultrafast Laplace NMR.

Decoupling the effects of defects on efficiency and stability through phosphonates in stable halide perovskite solar cells

Summary Understanding defects is of paramount importance for the development of stable halide perovskite solar cells (PSCs). However, isolating their distinctive effects on device efficiency and stability is currently a challenge. We report that adding the organic molecule 3-phosphonopropionic acid (H3pp) to the halide perovskite results in unchanged overall optoelectronic performance while having a tremendous effect on device stability. We obtained PSCs with ∼21% efficiency that retain ∼100% of the initial efficiency after 1,000 h at the maximum power point under simulated AM1.5G illumination. The strong interaction between the perovskite and the H3pp molecule through two types of hydrogen bonds (H…I and O…H) leads to shallow point defect passivation that has a significant effect on device stability but not on the non-radiative recombination and device efficiency. We expect that our work will have important implications for the current understanding and advancement of operational PSCs.

Frequency-swept pulses for ultrafast spatially encoded NMR

Ultrafast NMR based on spatial encoding yields arbitrary multidimensional spectra in a single scan. The dramatic acceleration afforded by spatial parallelisation makes it possible to capture transient species and processes, and has notably been applied to the monitoring of reactions and the analysis of hyperpolarised species. At the heart of ultrafast NMR lies the spatially sequential manipulation of nuclear spins. This is virtually always achieved by combining a swept radio-frequency pulse with a magnetic field gradient pulse. The dynamics of nuclear spins during these pulse sequence elements is key to understand and design ultrafast NMR experiments, and can often be described by surprisingly simple models. This article describes the spatial encoding of relaxation, chemical shift and diffusion in a common framework and discusses directions for future developments.

Ultrafast diffusion exchange nuclear magnetic resonance

The exchange of molecules between different physical or chemical environments due to diffusion or chemical transformations has a crucial role in a plethora of fundamental processes such as breathing, protein folding, chemical reactions and catalysis. Here, we introduce a method for a single-scan, ultrafast NMR analysis of molecular exchange based on the diffusion coefficient contrast. The method shortens the experiment time by one to four orders of magnitude. Consequently, it opens the way for high sensitivity quantification of important transient physical and chemical exchange processes such as in cellular metabolism. As a proof of principle, we demonstrate that the method reveals the structure of aggregates formed by surfactants relevant to aerosol research.

Insights into real-time chemical processes in a calcium sensor protein-directed dynamic library

Dynamic combinatorial chemistry (DCC) has proven its potential in drug discovery speeding the identification of modulators of biological targets. However, the exchange chemistries typically take place under specific reaction conditions, with limited tools capable of operating under physiological parameters. Here we report a catalyzed protein-directed DCC working at low temperatures that allows the calcium sensor NCS-1 to find the best ligands in situ. Ultrafast NMR identifies the reaction intermediates of the acylhydrazone exchange, tracing the molecular assemblies and getting a real-time insight into the essence of DCC processes at physiological pH. Additionally, NMR, X-ray crystallography and computational methods are employed to elucidate structural and mechanistic aspects of the molecular recognition event. The DCC approach leads us to the identification of a compound stabilizing the NCS-1/Ric8a complex and whose therapeutic potential is proven in a Drosophila model of disease with synaptic alterations.

REGISTRIES AND CARE OF NEUROMUSCULAR DISORDERS: P.293A novel, ultrafast and robust NMR imaging approach to evaluate disease activity and chronic degenerative changes in skeletal muscle using an optimal fingerprinting radial sequence

REGISTRIES AND CARE OF NEUROMUSCULAR DISORDERS: P.293A novel, ultrafast and robust NMR imaging approach to evaluate disease activity and chronic degenerative changes in skeletal muscle using an optimal fingerprinting radial sequence

Studying intact bacterial peptidoglycan by proton-detected NMR spectroscopy at 100 kHz MAS frequency

The bacterial cell wall is composed of the peptidoglycan (PG), a large polymer that maintains the integrity of the bacterial cell. Due to its multi-gigadalton size, heterogeneity, and dynamics, atomic-resolution studies are inherently complex. Solid-state NMR is an important technique to gain insight into its structure, dynamics and interactions. Here, we explore the possibilities to study the PG with ultra-fast (100 kHz) magic-angle spinning NMR. We demonstrate that highly resolved spectra can be obtained, and show strategies to obtain site-specific resonance assignments and distance information. We also explore the use of proton-proton correlation experiments, thus opening the way for NMR studies of intact cell walls without the need for isotope labeling.

Probing molecular dynamics with hyperpolarized ultrafast Laplace NMR using a low-field, single-sided magnet.

Laplace NMR (LNMR) offers deep insights on diffusional and rotational motion of molecules. The so-called "ultrafast" approach, based on spatial data encoding, enables one to carry out a multidimensional LNMR experiment in a single scan, providing from 10 to 1000-fold acceleration of the experiment. Here, we demonstrate the feasibility of ultrafast diffusion-T2 relaxation correlation (D-T2) measurements with a mobile, low-field, relatively low-cost, single-sided NMR magnet. We show that the method can probe a broad range of diffusion coefficients (at least from 10-8 to 10-12 m2 s-1) and reveal multiple components of fluids in heterogeneous materials. The single-scan approach is demonstrably compatible with nuclear spin hyperpolarization techniques because the time-consuming hyperpolarization process does not need to be repeated. Using dynamic nuclear polarization (DNP), we improved the NMR sensitivity of water molecules by a factor of 105 relative to non-hyperpolarized NMR in the 0.3 T field of the single-sided magnet. This enabled us to acquire a D-T2 map in a single, 22 ms scan, despite the low field and relatively low mole fraction (0.003) of hyperpolarized water. Consequently, low-field, hyperpolarized ultrafast LNMR offers significant prospects for advanced, mobile, low-cost and high-sensitivity chemical and medical analysis.

Ultrafast Laplace NMR with hyperpolarized xenon gas

Laplace NMR, consisting of diffusion and relaxation experiments, provides detailed information about dynamics of fluids in porous materials. Recently, we showed that two-dimensional Laplace NMR experiments can be carried out with a single scan based on spatial encoding. The method shortens the experiment time by one to three orders of magnitude, and therefore it is called ultrafast Laplace NMR. Furthermore, the single-scan approach facilitates significantly the use of nuclear spin hyperpolarization for boosting the sensitivity of the experiment, because a laborious hyperpolarization procedure does not need to be repeated. Here, we push the limits of the ultrafast Laplace NMR method by applying it, for the first time, in the investigation of a gas phase substance, namely hyperpolarized xenon gas. We show that, regardless of the fast diffusion of gas, layer-like spatial encoding is feasible, and an ultrafast diffusion – T2 relaxation correlation experiment reveals significantly different signals of free gas and gas adsorbed in a mesoporous controlled pore glass (CPG). The observed diffusion coefficients are many orders of magnitude larger than those detected earlier from liquid phase substances, emphasizing the extended application range of the method. The challenges in the methodology, caused by the fast diffusion, are also discussed.