Dissect and Divide: Putting NMR Spectra of Mixtures under the Knife

Combining Fast Pure Shift NMR and GEMSTONE-Based Selective TOCSY for Efficient NMR Analysis of Complex Systems

As one of the commonly used intact detection techniques, liquid NMR spectroscopy offers unparalleled insights into the chemical environments, structures, and dynamics of molecules. However, it generally encounters the challenges of crowded or even overlapped spectra, especially when probing complex sample systems containing numerous components and complicated molecular structures. Herein, we exploit a general NMR protocol for efficient NMR analysis of complex systems by combining fast pure shift NMR and GEMSTONE-based selective TOCSY. First, this protocol enables ultrahigh-selective observation on the coupling networks that are totally correlated with targeted resonances or components, even where they are situated in severely overlapped spectral regions. Second, pure shift simplification is introduced to enhance the spectral resolution and further resolve the subspectra containing spectral congestion, thus facilitating the dissection of overlapped spectra. Additionally, sparse sampling accompanied by spectral reconstruction is adopted to significantly accelerate acquisition and improve spectral quality. The advantages of this protocol were demonstrated on different complex sample systems, including a challenging compound of estradiol, a mixture of sucrose and d-glucose, and natural grape juice, verifying its feasibility and power, and boosting the potential application landscapes in various chemical fields.

Review on NMR as a tool to analyse natural products extract directly: Molecular structure elucidation and biological activity analysis

INTRODUCTION

Natural products, the small organic molecules produced by plants, microbes and invertebrates, often present in the form of a mixture, this leads to the structural characterisation of natural extracts often requiring time-consuming multistep purification procedures. Nuclear magnetic resonance (NMR) technology is traditionally utilised as a tool for the structural elucidation of pure compounds. Contemporarily, an up-to-date trend in the application of NMR in natural product research is shifting to the direct NMR analysis of crude mixtures, to obtain molecular structure and biological activity information without performing cumbersome separation.

OBJECTIVE

To review works of literature on the evolution, principle and progress of NMR technologies for analysing mixtures, we focus on the successful application of NMR technologies in direct analysis of natural product extracts.

METHODOLOGY

Based on our research experience, academic tracking and extensive literature search, which involved, but not limited to, the use of various databases, like Web of Knowledge and PubMed. The keywords used, in various combinations, to retrieve recent literature on the successful application of NMR technologies to sheer natural product extracts, and excluded artificially natural product mixture and biofluid.

RESULTS

NMR technologies for direct natural extracts analysis, including two-dimensional J-resolved spectroscopy (2D-JRES), pure shift NMR, diffusion-ordered NMR spectroscopy (DOSY), statistical correlation spectroscopy (STOCSY), concentration-ordered NMR spectroscopy (CORDY), saturation transfer difference (STD) and water-ligand observed via gradient spectroscopy (WaterLOGSY) were illustrated.

CONCLUSIONS

By these methods, molecular structure and biological activity information will be directly obtained from NMR analysis of natural products extract, aiming to save experimental time and expenses.

Obtaining Pure 1H NMR Spectra of Individual Pyranose and Furanose Anomers of Reducing Deoxyfluorinated Sugars

Due to tautomeric equilibria, NMR spectra of reducing sugars can be complex with many overlapping resonances. This hampers coupling constant determination, which is required for conformational analysis and configurational assignment of substituents. Given that mixtures of interconverting species are physically inseparable, easy-to-use techniques that enable facile full 1H NMR characterization of sugars are of interest. Here, we show that individual spectra of both pyranoside and furanoside forms of reducing fluorosugars can be obtained using 1D FESTA. We discuss the unique opportunities offered by FESTA over standard sel-TOCSY and show how it allows a more complete characterization. We illustrate the power of FESTA by presenting the first full NMR characterization of many fluorosugars, including of the important fluorosugar 2-deoxy-2-fluoroglucose. We discuss in detail all practical considerations for setting up FESTA experiments for fluorosugars, which can be extended to any mixture of fluorine-containing species interconverting slowly on the NMR frequency-time scale.

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 methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

Surface potential modulation as a tool for mitigating challenges in SERS-based microneedle sensors

Raman spectroscopic-based biosensing strategies are often complicated by low signal and the presence of multiple chemical species. While surface-enhanced Raman spectroscopy (SERS) nanostructured platforms are able to deliver high quality signals by focusing the electromagnetic field into a tight plasmonic hot-spot, it is not a generally applicable strategy as it often depends on the specific adsorption of the analyte of interest onto the SERS platform. This paper describes a strategy to address this challenge by using surface potential as a physical binding agent in the context of microneedle sensors. We show that the potential-dependent adsorption of different chemical species allows scrutinization of the contributions of different chemical species to the final spectrum, and that the ability to cyclically adsorb and desorb molecules from the surface enables efficient application of multivariate analysis methods. We demonstrate how the strategy can be used to mitigate potentially confounding phenomena, such as surface reactions, competitive adsorption and the presence of molecules with similar structures. In addition, this decomposition helps evaluate criteria to maximize the signal of one molecule with respect to others, offering new opportunities to enhance the measurement of analytes in the presence of interferants.

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.

Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures

Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of small molecules. However, the compound identification in NMR spectra of mixtures is highly challenging because of chemical shift variations of the same compound in different mixtures and peak overlapping among molecules. Here, we present a pseudo-Siamese convolutional neural network method (pSCNN) to identify compounds in mixtures for NMR spectroscopy. A data augmentation method was implemented for the superposition of several NMR spectra sampled from a spectral database with random noises. The augmented dataset was split and used to train, validate and test the pSCNN model. Two experimental NMR datasets (flavor mixtures and additional flavor mixture) were acquired to benchmark its performance in real applications. The results show that the proposed method can achieve good performances in the augmented test set (ACC = 99.80%, TPR = 99.70% and FPR = 0.10%), the flavor mixtures dataset (ACC = 97.62%, TPR = 96.44% and FPR = 2.29%) and the additional flavor mixture dataset (ACC = 91.67%, TPR = 100.00% and FPR = 10.53%). We have demonstrated that the translational invariance of convolutional neural networks can solve the chemical shift variation problem in NMR spectra. In summary, pSCNN is an off-the-shelf method to identify compounds in mixtures for NMR spectroscopy because of its accuracy in compound identification and robustness to chemical shift variation.

NMR spectroscopy of wastewater: A review, case study, and future potential

NMR spectroscopy is arguably the most powerful tool for the study of molecular structures and interactions, and is increasingly being applied to environmental research, such as the study of wastewater. With over 97% of the planet's water being saltwater, and two thirds of freshwater being frozen in the ice caps and glaciers, there is a significant need to maintain and reuse the remaining 1%, which is a precious resource, critical to the sustainability of most life on Earth. Sanitation and reutilization of wastewater is an important method of water conservation, especially in arid regions, making the understanding of wastewater itself, and of its treatment processes, a highly relevant area of environmental research. Here, the benefits, challenges and subtleties of using NMR spectroscopy for the analysis of wastewater are considered. First, the techniques available to overcome the specific challenges arising from the nature of wastewater (which is a complex and dilute matrix), including an examination of sample preparation and NMR techniques (such as solvent suppression), in both the solid and solution states, are discussed. Then, the arsenal of available NMR techniques for both structure elucidation (e.g., heteronuclear, multidimensional NMR, homonuclear scalar coupling-based experiments) and the study of intermolecular interactions (e.g., diffusion, nuclear Overhauser and saturation transfer-based techniques) in wastewater are examined. Examples of wastewater NMR studies from the literature are reviewed and potential areas for future research are identified. Organized by nucleus, this review includes the common heteronuclei (¹³C, ¹⁵N, ¹⁹F, ³¹P, ²⁹Si) as well as other environmentally relevant nuclei and metals such as ²⁷Al, ⁵¹V, ²⁰⁷Pb and ¹¹³Cd, among others. Further, the potential of additional NMR methods such as comprehensive multiphase NMR, NMR microscopy and hyphenated techniques (for example, LC-SPE-NMR-MS) for advancing the current understanding of wastewater are discussed. In addition, a case study that combines natural abundance (i.e. non-concentrated), targeted and non-targeted NMR to characterize wastewater, along with in vivo based NMR to understand its toxicity, is included. The study demonstrates that, when applied comprehensively, NMR can provide unique insights into not just the structure, but also potential impacts, of wastewater and wastewater treatment processes. Finally, low-field NMR, which holds considerable future potential for on-site wastewater monitoring, is briefly discussed. In summary, NMR spectroscopy is one of the most versatile tools in modern science, with abilities to study all phases (gases, liquids, gels and solids), chemical structures, interactions, interfaces, toxicity and much more. The authors hope this review will inspire more scientists to embrace NMR, given its huge potential for both wastewater analysis in particular and environmental research in general.

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.

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).

Ultrafast diffusion-based unmixing of 1H NMR spectra

We show that the NMR spectra of components in a mixture can be separated using 2D data acquired in less than one second, and an algorithm that is executed in just a few seconds. This NMR unmixing method is based on spatial encoding of the translational diffusion coefficients of the mixture's components, with multivariate processing of the data. This requires a new frequency swept pulse, which is designed and implemented to obtain quadratic spacing of the spatially parallelised gradient dimension. Ultrafast NMR unmixing may help in the analysis of mixtures that evolve in time.

Incorporated diffusion ordered heteronuclear multiple bond correlation spectroscopy, 3D iDOSY-HMBC. Merging of diffusion delay with long polarization transfer delay of HMBC

3D iDOSY-HMBC pulse sequences allow the simplification of HMBC data of mixtures via separation in the diffusion domain. The presented methods utilize incorporated DOSY approach, iDOSY, where the existing delays of the basic pulse sequence are utilized for diffusion attenuation. In the simplest form of the proposed 3D iDOSY-HMBC sequences, no extra delays or RF-pulses were required, only two diffusion gradients were added within HMBC polarization transfer delay.

Signal Deconvolution and Generative Topographic Mapping Regression for Solid-State NMR of Multi-Component Materials

Solid-state nuclear magnetic resonance (ssNMR) spectroscopy provides information on native structures and the dynamics for predicting and designing the physical properties of multi-component solid materials. However, such an analysis is difficult because of the broad and overlapping spectra of these materials. Therefore, signal deconvolution and prediction are great challenges for their ssNMR analysis. We examined signal deconvolution methods using a short-time Fourier transform (STFT) and a non-negative tensor/matrix factorization (NTF, NMF), and methods for predicting NMR signals and physical properties using generative topographic mapping regression (GTMR). We demonstrated the applications for macromolecular samples involved in cellulose degradation, plastics, and microalgae such as Euglena gracilis. During cellulose degradation, ¹³C cross-polarization (CP)-magic angle spinning spectra were separated into signals of cellulose, proteins, and lipids by STFT and NTF. GTMR accurately predicted cellulose degradation for catabolic products such as acetate and CO₂. Using these methods, the ¹H anisotropic spectrum of poly-ε-caprolactone was separated into the signals of crystalline and amorphous solids. Forward prediction and inverse prediction of GTMR were used to compute STFT-processed NMR signals from the physical properties of polylactic acid. These signal deconvolution and prediction methods for ssNMR spectra of macromolecules can resolve the problem of overlapping spectra and support macromolecular characterization and material design.

Selective Nuclear Magnetic Resonance Experiments for Sign-Sensitive Determination of Heteronuclear Couplings: Expanding the Analysis of Crude Reaction Mixtures

State-of-the-art nuclear magnetic resonance (NMR) selective experiments are capable of directly analyzing crude reaction mixtures. A new experiment named HD-HAPPY-FESTA yields ultrahigh-resolution total correlation subspectra, which are suitable for sign-sensitive determination of heteronuclear couplings, as demonstrated here by measuring the sign and magnitude for proton-fluorine couplings (J_HF) from major and minor isomer products of a two-step reaction without any purification. Proton-fluorine couplings ranging from 51.5 to -2.6 Hz could be measured using HD-HAPPY-FESTA, with the smallest measured magnitude of 0.8 Hz. Experimental J_HF values were used to identify the two fluoroketone intermediates and the four fluoroalcohol products. Results were rationalized and compared with the density functional theory (DFT) calculations. Experimental data were further compared with the couplings reported in the literature, where pure samples were analyzed.

Band-selective NMR experiments for suppression of unwanted signals in complex mixtures

Band-selective NMR experiments are presented that allow selective suppression of unwanted signals (SUN) from the spectra of complex metabolite mixtures. As a result, spectral overlap and dynamic range problems are substantially reduced and low-intensity signals normally covered by dominant signals can be observed. The usefulness of the experiments is exemplified with selective suppression of sugar signals from the NMR spectra of fruit juice and a plant sample. Other possible applications include blood, milk, and wine samples.

Band-selective NMR experiments are presented that allow selective suppression of unwanted signals (SUN) from the spectra of complex metabolite mixtures.

Matrix-assisted DOSY

The analysis of mixtures by NMR spectroscopy is challenging. Diffusion-ordered NMR spectroscopy enables a pseudo-separation of species based on differences in their translational diffusion coefficients. Under the right circumstances, this is a powerful technique; however, when molecules diffuse at similar rates separation in the diffusion dimension can be poor. In addition, spectral overlap also limits resolution and can make interpretation challenging. Matrix-assisted diffusion NMR seeks to improve resolution in the diffusion dimension by utilising the differential interaction of components in the mixture with an additive to the solvent. Tuning these matrix-analyte interactions allows the diffusion resolution to be optimised. This review presents the background to matrix-assisted diffusion experiments, surveys the wide range of matrices employed, including chromatographic stationary phases, surfactants and polymers, and demonstrates the current state of the art.

Improving the Sensitivity of FESTA Methods for the Analysis of Fluorinated Mixtures

The analysis of complex mixtures is an important but often intractable problem. When species contain sparse fluorine atoms, NMR spectra of fluorine-containing spin systems can be efficiently extracted from an intact mixture using the recently proposed FESTA (Fluorine-Edited Selective TOCSY Acquisition) methodology. Here an alternative approach to the existing selective reverse INEPT FESTA (SRI-FESTA) experiment is described, based on the use of a modulated spin echo for the initial excitation. MODO-FESTA (modulated echo FESTA) is simpler and has a significant sensitivity advantage over SRI-FESTA. Comparisons are presented of the relative sensitivity and spectral purity of the two types of methods.