Solution-State 2D NMR Spectroscopy of Mixtures HyperpolarizedUsing Optically Polarized Crystals.

The HYPNOESYS method (Hyperpolarized NOE System), which relies on the dissolution of optically polarized crystals, has recently emerged as a promising approach to enhance the sensitivity of NMR spectroscopy in the solution state. However, HYPNOESYS is a single-shot method that is not generally compatible with multidimensional NMR. Here we show that 2D NMR spectra can be obtained from HYPNOESYS-polarized samples, using single-scan acquisition methods. The approach is illustrated with a mixture of terpene molecules and a benchtop NMR spectrometer, paving the way to a sensitive, information-rich and affordable analytical method.

A Modified 1H-NMR Quantification Method of Ephedrine Alkaloids in Ephedrae Herba Samples.

A previous 1H-NMR method allowed the quantification of ephedrine alkaloids; however, there were some disadvantages. The cyclized derivatives resulted from the impurities of diethyl ether were identified and benzene was selected as the better extraction solvent. The locations of ephedrine alkaloids were confirmed with 2D NMR. Therefore, a specific 1H-NMR method has been modified for the quantification of ephedrine alkaloids. Accordingly, twenty Ephedrae Herba samples could be classified into three classes: (I) E. sinica-like species; (II) E. intermedia-like species; (III) others (lower alkaloid contents). The results indicated that ephedrine and pseudoephedrine are the major alkaloids in Ephedra plants, but the concentrations vary greatly determined by the plant species and the collection locations.

Mahalanobis distance correlation: A novel approach for quantitating changes in multidimensional NMR spectra in biological applications.

We present here a novel protocol for quantitating changes in the NMR spectra, which is based on Mahalanobis statistics. In a two dimensional NMR spectrum, the various peaks are taken to represent a distribution, and the two chemical shifts along the orthogonal axes and the peak intensities constitute three observables. All these observables vary in a correlated manner. Taking account of these, the Mahalanobis distance (MD) reflects the distance of any chosen peak from the centre of the distribution. For quantitating changes in a particular spectrum (say A) with N peaks (altered protein NMR spectrum) with respect to a reference spectrum (say B) with M peaks (original protein NMR spectrum), a composite spectrum with N + M peaks is generated. A one-to-one correspondence between N MD values considering all the N peaks in A and the same N peaks in the composite spectrum (A + B) is calculated. The MD distance of corresponding peaks in two different distributions can be correlated to assess the changes in the spectra during the course of a biological phenomenon, or as a result of biomolecular interactions. We have demonstrated these ideas, first, using the 1H-15N HSQC spectrum of Ubiquitin, and then application of these has been demonstrated for monitoring progression of fibrillation of the protein α-Synuclein, in absence and presence of safranal, a known inhibitor of fibrillation of the protein. The method is in general applicable to multidimensional NMR spectra, does not require extensive data collection, and allows quantitative assessment of spectral changes via a single parameter. We believe that the method will have wide ranging applications to monitor many biological phenomena, and will also be useful in an industrial environment for mass comparison of molecules in a rapid manner.

Brownian motion, spin diffusion and protein structure determination in solution.

This paper presents my recollections on the development of protein structure determination by NMR in solution from 1968 to 1992. The key to success was to identify NMR-accessible parameters that unambiguously determine the spatial arrangement of polypeptide chains. Inspired by work with cyclopeptides, model considerations showed that enforcing short non-bonding interatomic distances imposes «ring closure conditions¼ on polypeptide chains. Given that distances are scalar parameters, this indicated an avenue for studies of proteins in solution, i.e., under the regime of stochastic rotational and translational motions at frequencies in the nanosecond range (Brownian motion), where sharp pictures could not be obtained by photography-related methods. Later-on, we used distance geometry calculations with sets of inter-atomic distances derived from protein crystal structures to confirm that measurements of short proton-proton distances could provide atomic-resolution structures of globular proteins. During the years 1976-1984 the following four lines of research then led to protein structure determination by NMR in solution. First, the development of NMR experiments enabling the use of the nuclear Overhauser effect (NOE) for measurements of interatomic distances between pairs of hydrogen atoms in proteins. Second, obtaining sequence-specific resonance assignment solved the "phase problem" for protein structure determination by NMR. Third, generating and programming novel distance geometry algorithms enabled the calculation of atomic-resolution protein structures from limited sets of distance constraints measured by NMR. Fourth, the introduction of two-dimensional NMR provided greatly improved spectral resolution of the complex spectra of proteins as well as efficient delineation of scalar and dipole-dipole 1H-1H connectivities, thus making protein structure determination in solution viable and attractive.

A general strategy for the structural determination of carbohydrates by multi-dimensional NMR spectroscopies.

Two-dimensional NMR spectroscopies are one of the most frequently used techniques for the structural determination of carbohydrates. However, the data analysis is challenging because of the signal overlap in the 1H homonuclear correlation spectra. We attempted to explore a general strategy for the structural determination of carbohydrates by combined multi-dimensional spectroscopies. The strategy was applied to a human milk oligosaccharide lacto-N-difucohexaose I, that has been previously studied by conventional two-dimensional NMR spectroscopy. Assignment of the intra-residue resonances of the hexasaccharide using the three-dimensional spectrum was straightforward. Consequently, data analysis of the multi-dimensional spectra was significantly simplified, leading to a quicker determination of the intra- and inter-residue connections in the hexasaccharide. Application of the NMR strategy to chondroitin sulfate from bovine cartilage revealed two repeating disaccharide regions of the A and C units of chondroitin sulfate, indicating the high potential of this technique for the structural determination of complex polysaccharides.

A method for increasing the solubility of industrial azo pigments for 13 C and 1 H NMR spectra and the assignments of their 13 C and 1 H NMR peaks.

A method for increasing the solubilities of industrial azo pigments in DMSO by adding DBU (1,8-diaza-7-bicyclo[5.4.0]undecene) has been developed. This facilitated the acquisition of solution 13 C NMR spectra of the pigments. This method was applied to four types of azo pigments: naphthol AS (3-hydroxy-2-naphthoic acid anilide) pigments, naphthol pigments, pyrazolone pigments and acetoacetanilide pigments. This represents the first solution 13 C NMR spectra for naphthol AS pigments. Altogether 18 industrial azo pigments were analysed using 1D and 2D NMR techniques. The proton and corresponding carbon NMR resonances of these pigments have all been assigned.

A novel high-dimensional NMR experiment for resolving protein backbone dihedral angle ambiguities.

Intrinsically disordered proteins (IDPs) are challenging established structural biology perception and urge a reassessment of the conventional understanding of the subtle interplay between protein structure and dynamics. Due to their importance in eukaryotic life and central role in protein interaction networks, IDP research is a fascinating and highly relevant research area in which NMR spectroscopy is destined to be a key player. The flexible nature of IDPs, as a result of the sampling of a vast conformational space, however, poses a tremendous scientific challenge, both technically and theoretically. Pronounced signal averaging results in narrow signal dispersion and requires higher dimensionality NMR techniques. Moreover, a fundamental problem in the structural characterization of IDPs is the definition of the conformational ensemble sampled by the polypeptide chain in solution, where often the interpretation relies on the concept of 'residual structure' or 'conformational preference'. An important source of structural information is information-rich NMR experiments that probe protein backbone dihedral angles in a unique manner. Cross-correlated relaxation experiments have proven to fulfil this task as they provide unique information about protein backbones, particularly in IDPs. Here we present a novel cross-correlation experiment that utilizes non-uniform sampling detection schemes to resolve protein backbone dihedral ambiguities in IDPs. The sensitivity of this novel technique is illustrated with an application to the prototypical IDP [Formula: see text]-Synculein for which unexpected deviations from random-coil-like behaviour could be observed.

Two-dimensional NMR lineshape analysis of single, multiple, zero and double quantum correlation experiments.

NMR spectroscopy provides a powerful approach for the characterisation of chemical exchange and molecular interactions by analysis of series of experiments acquired over the course of a titration measurement. The appearance of NMR resonances undergoing chemical exchange depends on the frequency difference relative to the rate of exchange, and in the case of one-dimensional experiments chemical exchange regimes are well established and well known. However, two-dimensional experiments present additional complexity, as at least one additional frequency difference must be considered. Here we provide a systematic classification of chemical exchange regimes in two-dimensional NMR spectra. We highlight important differences between exchange in HSQC and HMQC experiments, that on a practical level result in more severe exchange broadening in HMQC spectra, but show that complementary alternatives to the HMQC are available in the form of HZQC and HDQC experiments. We present the longitudinal relaxation optimised SOFAST-H(Z/D)QC experiment for the simultaneous acquisition of sensitivity-enhanced HZQC and HDQC spectra, and the longitudinal and transverse relaxation optimised BEST-ZQ-TROSY for analysis of large molecular weight systems. We describe the application of these experiments to the characterisation of the interaction between the Hsp90 N-terminal domain and a small molecule ligand, and show that the independent analysis of HSQC, HMQC, HZQC and HDQC experiments provides improved confidence in the fitted dissociation constant and dissociation rate. Joint analysis of such data may provide improved sensitivity to detect and analyse more complex multi-state interaction mechanisms such as induced fit or conformational selection.

NMR application in unconventional shale reservoirs - A new porous media research frontier.

Unconventional shale reservoirs have greatly contributed to the recent surge in petroleum production in the United States and are expected to lead the US oil production to a historical high in 2018. The complexity of the rocks and fluids in these reservoirs presents a significant challenge to the traditional approaches to the evaluation of geological formations due to the low porosity, permeability, complex lithology and fluid composition. NMR has emerged as the key measurement for evaluating these reservoirs, for quantifying their petrophysical parameters, fluid properties, and determining productivity. Measurement of the T1/T2 ratio by 2D NMR has been found to be critical for identifying the fluid composition of kerogen, bitumen, light/heavy oils, gases and brine in these formations. This paper will first provide a brief review of the theories of relaxation, measurement methods, and data inversion techniques and then will discuss several examples of applications of these NMR methods for understanding various aspects of the unconventional reservoirs. At the end, we will briefly discuss a few other topics, which are still in their developmental stages, such as solid state NMR, and their potential applications for shale rock evaluation.

Two-dimensional NMR analysis of Angiopteris evecta rhizome and improved extraction method for angiopteroside.

INTRODUCTION: The rhizome of Angiopteris evecta is of academic interest in Kalimantan, Indonesia, from an ethnobotanical perspective. Angiopteroside is a substance of pharmaceutical importance that is found in the rhizome of A. evecta. OBJECTIVE: The aims of this research are to improve the extraction method for angiopteroside from the rhizome, compared to that in a previous report, and to determine the yield of angiopteroside from the rhizome of A. evecta, as well as to obtain precise data for extractives from the rhizome of A. evecta by using two-dimensional NMR spectroscopy and liquid chromatography-mass spectrometry (LC-MS). METHODOLOGY: We investigated the chemical constituents of the whole rhizome by means of two-dimensional NMR (heteronuclear single quantum coherence or HSQC) spectroscopy, neutral sugar analysis using the alditol acetate method, and lignin analysis using alkaline nitrobenzene oxidation and Klason lignin methods. LC-MS revealed the purity of the angiopteroside. Antimicrobial assays were also performed for the purified angiopteroside by using a broth microdilution method. RESULTS: Angiopteroside was isolated by Soxhlet extraction with aqueous acetone followed by preparative thin-layer chromatography (eluent: 20% methanol/dichloromethane). LC-MS revealed that angiopteroside can be found in the rhizome of A. evecta in 9.9% yield, which is an extremely high yield for a plant extractive. CONCLUSION: HSQC analysis is a powerful tool for surveying compounds in plant materials, such as the whole rhizome of A. evecta. Soxhlet extraction with aqueous acetone is an effective method for extracting glycosides from plant materials.

Solid-State NMR Structural Characterization of Self-Assembled Peptides with Selective 13C and 15N Isotopic Labels.

For the structural characterization methods discussed here, information on molecular conformation and intermolecular organization within nanostructured peptide assemblies is discerned through analysis of solid-state NMR spectral features. This chapter reviews general NMR methodologies, requirements for sample preparation, and specific descriptions of key experiments. An attempt is made to explain choices of solid-state NMR experiments and interpretation of results in a way that is approachable to a nonspecialist. Measurements are designed to determine precise NMR peak positions and line widths, which are correlated with secondary structures, and probe nuclear spin-spin interactions that report on three-dimensional organization of atoms. The formulation of molecular structural models requires rationalization of data sets obtained from multiple NMR experiments on samples with carefully chosen 13C and 15N isotopic labels. The information content of solid-state NMR data has been illustrated mostly through the use of simulated data sets and references to recent structural work on amyloid fibril-forming peptides and designer self-assembling peptides.

High-dimensional NMR methods for intrinsically disordered proteins studies.

Intrinsically disordered proteins (IDPs) are getting more and more interest of the scientific community. Nuclear magnetic resonance (NMR) is often a technique of choice for these studies, as it provides atomic-resolution information on structure, dynamics and interactions of IDPs. Nonetheless, NMR spectra of IDPs are typically extraordinary crowded, comparing to those of structured proteins. To overcome this problem, high-dimensional NMR experiments can be used, which allow for a better peak separation. In the present review different aspects of such experiments are discussed, from data acquisition and processing to analysis, focusing on experiments for resonance assignment.

Detection of 2-aminoethylphosphonic acid in suspended particles in an ultraoligotrophic lake: a two-dimensional nuclear magnetic resonance (2D-NMR) study.

Particulate organic phosphorus (P) compounds were examined in ultraoligotrophic Lake Saiko, Japan. A cartridge filter was used to collect sufficient amount of suspended particles for analysis by a two-dimensional NMR (1H-31P heteronuclear multiple bond correlation). 2-Aminoethylphosphonic acid (2-AEP), a phosphonate, was detected in suspended particles in Lake Saiko. The identity of the phosphonate was confirmed by comparison with a commercially available compound. Because 2-AEP is bioavailable, microorganisms can store and use this compound under extremely P-limited conditions. This is the first study to detect 2-AEP in an ultra-oligotrophic environment.

Synthesis, structure elucidation, and determination of polyhalogenated N-methylpyrroles (PMPs) in blue mussels.

Polyhalogenated N-methylpyrroles (PMPs) are halogenated natural products (HNPs) recently detected in seagrass, blue mussels, and other marine organisms. In this study, we synthesized 2,3,4,5-tetrachloro-N-methylpyrrole (Cl4-MP), 2,3,4,5-tetrabrominated-N-methylpyrrole (Br4-MP, aka TBMP), and mixed tetrahalogenated (Cl and Br) N-methylpyrrole congeners. Use of one- and two-dimensional 1H and 13C NMR verified the structures of isolated/enriched 3,4-dibromo-2,5-dichloro-N-methylpyrrole (3,4-Br2-2,5-Cl2-MP), 2,3,4-tribromo-5-chloro-N-methylpyrrole (2,3,4-Br3-5-Cl-MP), and 3-bromo-2,4,5-trichloro-N-methylpyrrole (3-Br-2,4,5-Cl3-MP). GC/EI-MS and GC/ECNI-MS mass spectra of the five PMPs were studied with regard to fragmentation pattern and individual responses which were strongly affected by the presence (or absence) of Br in α-position(s). Quantitative solutions of the synthesized standards were used to determine the elution order of isomers and to quantify PMPs in selected blue mussel samples (Mytilus sp.) from the European Atlantic coast (Spain, France), the North Sea (the Netherlands, Germany) and Baltic Sea (Germany). PMPs were detected in all samples and the concentrations ranged between 0.6 and 52 µg/kg lipids with Br4-MP being the most abundant representative of this substance class.

Persistence of urban organic aerosols composition: Decoding their structural complexity and seasonal variability.

Organic Aerosols (OAs) are typically defined as highly complex matrices whose composition changes in time and space. Focusing on time vector, this work uses two-dimensional nuclear magnetic resonance (2D NMR) techniques to examine the structural features of water-soluble (WSOM) and alkaline-soluble organic matter (ASOM) sequentially extracted from fine atmospheric aerosols collected in an urban setting during cold and warm seasons. This study reveals molecular signatures not previously decoded in NMR-related studies of OAs as meaningful source markers. Although the ASOM is less hydrophilic and structurally diverse than its WSOM counterpart, both fractions feature a core with heteroatom-rich branched aliphatics from both primary (natural and anthropogenic) and secondary origin, aromatic secondary organics originated from anthropogenic aromatic precursors, as well as primary saccharides and amino sugar derivatives from biogenic emissions. These common structures represent those 2D NMR spectral signatures that are present in both seasons and can thus be seen as an "annual background" profile of the structural composition of OAs at the urban location. Lignin-derived structures, nitroaromatics, disaccharides, and anhydrosaccharides signatures were also identified in the WSOM samples only from periods identified as smoke impacted, which reflects the influence of biomass-burning sources. The NMR dataset on the H-C molecules backbone was also used to propose a semi-quantitative structural model of urban WSOM, which will aid efforts for more realistic studies relating the chemical properties of OAs with their atmospheric behavior.

Novel 2D-NMR Approach for the Classification of Balsamic Vinegars of Modena.

The aim of this work is to evaluate the possibility of using 2D-NMR for the construction of classification models for balsamic vinegars of Modena. The goal was to obtain an indirect indicator of authenticity and a quality control tool. The spectral data were analyzed by chemometric methods, aiming to discriminate the samples in relation to their origin. Application of general discriminant analysis (GDA) revealed a good discrimination; the two obtained models explained 83.9% and 97.3% of the total variance with a predictive capacity of 98.6% and 98.4%, respectively. The signals of 5-HMF, ß-glucose, 2,3-butanediol, 6-acetyl glucose, and different aliphatic signals of sugars were the most significant variables. These results are very promising for giving an important contribution in quality control and characterization of such very valuable foods.

Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm.

A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH.

INFOS: spectrum fitting software for NMR analysis.

Software for fitting of NMR spectra in MATLAB is presented. Spectra are fitted in the frequency domain, using Fourier transformed lineshapes, which are derived using the experimental acquisition and processing parameters. This yields more accurate fits compared to common fitting methods that use Lorentzian or Gaussian functions. Furthermore, a very time-efficient algorithm for calculating and fitting spectra has been developed. The software also performs initial peak picking, followed by subsequent fitting and refinement of the peak list, by iteratively adding and removing peaks to improve the overall fit. Estimation of error on fitting parameters is performed using a Monte-Carlo approach. Many fitting options allow the software to be flexible enough for a wide array of applications, while still being straightforward to set up with minimal user input.

Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data.

Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.

Multidimensional NMR inversion without Kronecker products: Multilinear inversion.

Multidimensional NMR inversion using Kronecker products poses several challenges. First, kernel compression is only possible when the kernel matrices are separable, and in recent years, there has been an increasing interest in NMR sequences with non-separable kernels. Second, in three or more dimensions, the singular value decomposition is not unique; therefore kernel compression is not well-defined for higher dimensions. Without kernel compression, the Kronecker product yields matrices that require large amounts of memory, making the inversion intractable for personal computers. Finally, incorporating arbitrary regularization terms is not possible using the Lawson-Hanson (LH) or the Butler-Reeds-Dawson (BRD) algorithms. We develop a minimization-based inversion method that circumvents the above problems by using multilinear forms to perform multidimensional NMR inversion without using kernel compression or Kronecker products. The new method is memory efficient, requiring less than 0.1% of the memory required by the LH or BRD methods. It can also be extended to arbitrary dimensions and adapted to include non-separable kernels, linear constraints, and arbitrary regularization terms. Additionally, it is easy to implement because only a cost function and its first derivative are required to perform the inversion.