NMR and parity nonconservation. Experimental requirements to observe a difference between enantiomer signals.

The possibility of observing a difference in the high-resolution NMR spectra of two enantiomers as due to parity nonconservation is discussed. Proposals to minimize the NMR linewidths are presented. It is concluded that, using the ultra- high-resolution technique, a difference could be observed with high Z value spin one- half nuclei such as Pt, T1, Xe. Other nuclei can also be considered.     

Phosphorus-31 NMR as a probe for phosphoproteins

Nuclear magnetic resonance methodology continues to advance such that phosphorus-31 NMR experiments can be profitably applied to elucidate some aspects of proteins which are covalently phosphorylated. This review introduces NMR spectral parameters pertinent to using phosphorus-31 NMR for investigation of structure and dynamics. The techniques of two-dimensional NMR, solid state NMR, and isotopic substitution are also introduced. Characteristics of phosphorylated amino acids and peptides, as revealed by phosphorus-31 NMR, are described. Studies of phosphorylated containing phosphomonoesters, phosphoramidates, acyl phosphates, and disubstituted phosphorus bridges are discussed. Among these phosphoproteins are several examples where phosphorus residues evidently play a role as polyelectrolytes, in enzyme catalysis, and in regulation of protein function.     

Studies on cryoprotectant equilibration in the intact rat liver using nuclear magnetic resonance spectroscopy: a noninvasive method to assess distribution of dimethyl sulfoxide in tissues

Nuclear magnetic resonance (NMR) spectroscopy was used in the study of rat livers following flushing with a clinically used preservation solution containing either 12 or 30% (v/v) Me2SO. The extent of equilibration of Me2SO in the tissue after 10-15 min of perfusion with Me2SO and again after subsequent washout with Me2SO-free medium was assessed by 1H NMR spectroscopy. 31P NMR spectroscopy was used to follow the changes in ATP, ADP, inorganic phosphate, and tissue pH. The data show that 1H NMR spectroscopy can be used as a sensitive and rapid method of assessing the equilibration and concentration of compounds such as Me2SO, since these compounds are likely to be present at concentrations greatly in excess of other constituents of the medium and will therefore give rise to strong, easily detected signals. At the same time, 31P NMR spectroscopy can be used to monitor the metabolic status of the tissue reflected in the levels of ATP, ADP, and inorganic phosphate, as well as being a noninvasive monitor of intracellular pH. The possibility of determining the tissue pH in the presence of solutes such as Me2SO is discussed.     

A MILP-based flux alternative generation and NMR experimental design strategy for metabolic engineering

A mixed-integer linear program (MILP) is described that can enumerate all the ways fluxes can distribute in a metabolic network while still satisfying the same constraints and objective function. The multiple solutions can be used to (1) generate alternative flux scenarios that can account for limited experimental observations, (2) forecast the potential responses to mutation (e.g., new reaction pathways may be used), and (3) (as illustrated) design (13)C NMR experiments such that different potential flux patterns in a mutant can be distinguished. The experimental design is enabled by using the MILP results as an input to an isotopomer mapping matrices (IMM)-based program, which accounts for the network circulation of (13)C from a precursor such as glucose. The IMM-based program can interface to common plotting programs with the result that the user is provided with predicted NMR spectra that are complete with splittings and Lorentzian line-shape features. The example considered is the trafficking of carbon in an Escherichia coli mutant, which has pyruvate kinase activity deleted for the purpose of eliminating acetate production. Similar yields and extracellular measurements would be manifested by the flux alternatives. The MILP-IMM results suggest how NMR experiments can be designed such that the spectra of glutamate for two flux distribution scenarios differ significantly.     

The use of solid-state NMR and X-ray crystallography as complementary tools for studying molecular recognition

Solid-state NMR is rapidly becoming available as a routine technique for studying the structure of crystalline or noncrystalline solids. This technique has an advantage over crystallography in that single crystals are not necessary, but it has the disadvantage that the information obtained does not produce a direct picture of the molecule and its environment. On the other hand, solid-state NMR can be done on mixtures, and it gives information about phase distribution in a manner similar to that of X-ray powder pattern analysis.Crystallographic effects such as polymorphism, multiple molecules per asymmetric unit, disorder and salvation can frequently be detected using NMR. Sometimes molecular point group symmetry can also be deduced based on the number of independent nuclei that are detected. The NMR method is sensitive to changes in the electronic structure of a molecule as sensed by the nuclei, and the effects are measured as changes in the isotropic chemical shift of individual nuclei.In this paper, we will give examples of the combined use of X-ray crystallography and ¹³CP/MAS (cross polarization/magic angle spinning) NMR for studying hostguest materials and cocrystals. We have learned how to use NMR to tell us about keto/enol composition in the solid state, to detect the presence of trapped solvent molecules, to detect hydrogen-bond formation and to evaluate molecular conformation and unusual packing pattern effects. We will also present a brief background of the ¹³CP/MAS NMR technique and three case studies in which solid-state NMR and X-ray crystallography are used together to understand materials' structures and properties     

Nmrglue: an open source Python package for the analysis of multidimensional NMR data

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.     

COCO: a simple tool to enrich the representation of conformational variability in NMR structures

NMR structures are typically deposited in databases such as the PDB in the form of an ensemble of structures. Generally, each of the models in such an ensemble satisfies the experimental data and is equally valid. No unique solution can be calculated because the experimental NMR data is insufficient, in part because it reflects the conformational variability and dynamical behavior of the molecule in solution. Even for relatively rigid molecules, the limited number of structures that are typically deposited cannot completely encompass the structural diversity allowed by the observed NMR data, but they can be chosen to try and maximize its representation. We describe here the adaptation and application of techniques more commonly used to examine large ensembles from molecular dynamics simulations, to the analysis of NMR ensembles. The approach, which is based on principal component analysis, we call COCO ("Complementary Coordinates"). The COCO approach analyses the distribution of an NMR ensemble in conformational space, and generates a new ensemble that fills "gaps" in the distribution. The method is very rapid, and analysis of a 25-member ensemble and generation of a new 25 member ensemble typically takes 1-2 min on a conventional workstation. Applied to the 545 structures in the RECOORD database, we find that COCO generates new ensembles that are as structurally diverse-both from each other and from the original ensemble-as are the structures within the original ensemble. The COCO approach does not explicitly take into account the NMR restraint data, yet in tests on selected structures from the RECOORD database, the COCO ensembles are frequently good matches to this data, and certainly are structures that can be rapidly refined against the restraints to yield high-quality, novel solutions. COCO should therefore be a useful aid in NMR structure refinement and in other situations where a richer representation of conformational variability is desired-for example in docking studies. COCO is freely accessible via the website www.ccpb.ac.uk/COCO.     

Residual dipolar couplings: Synergy between NMR and structural genomics

Structural genomics is on a quest for the structure and function of a significant fraction of gene products. Current efforts are focusing on structure determination of single-domain proteins, which can readily be targeted by X-ray crystallography, NMR spectroscopy and computational homology modeling. However, comprehensive association of gene products with functions also requires systematic determination of more complex protein structures and other biomolecules participating in cellular processes such as nucleic acids, and characterization of biomolecular interactions and dynamics relevant to function. Such NMR investigations are becoming more feasible, not only due to recent advances in NMR methodology, but also because structural genomics is providing valuable structural information and new experimental and computational tools. The measurement of residual dipolar couplings in partially oriented systems and other new NMR methods will play an important role in this synergistic relationship between NMR and structural genomics. Both an expansion in the domain of NMR application, and important contributions to future structural genomics efforts can be anticipated.     

Nuclear magnetic resonance micro-imaging in the investigation of plant cell metabolism

Micro-imaging based on nuclear magnetic resonance offers the possibility to map metabolites in plant tissues non-invasively. Major metabolites such as sucrose and amino acids can be observed with high spatial resolution. Stable isotope tracers, such as (13)C-labelled metabolites can be used to measure the in vivo conversion rates in a metabolic network. This review summarizes the different nuclear magnetic resonance micro-imaging techniques that are available to obtain spatially resolved information on metabolites in plants. A short general introduction into NMR imaging techniques is provided. Particular emphasis is given to the difficulties encountered when NMR micro-imaging is applied to plant systems.     

NMR structures of paramagnetic metalloproteins

Metalloproteins represent a large share of the proteome and many of them contain paramagnetic metal ions. The knowledge, at atomic resolution, of their structure in solution is important to understand processes in which they are involved, such as electron transfer mechanisms, enzymatic reactions, metal homeostasis and metal trafficking, as well as interactions with their partners. Formerly considered as unfeasible, the first structure in solution by nuclear magnetic resonance (NMR) of a paramagnetic protein was obtained in 1994. Methodological and instrumental advancements pursued over the last decade are such that NMR structure of paramagnetic proteins may be now routinely obtained. We focus here on approaches and problems related to the structure determination of paramagnetic proteins in solution through NMR spectroscopy. After a survey of the background theory, we show how the effects produced by the presence of a paramagnetic metal ion on the NMR parameters, which are in many cases deleterious for the detection of NMR spectra, can be overcome and turned into an additional source of structural restraints. We also briefly address features and perspectives given by the use of 13C-detected protonless NMR spectroscopy for proteins in solution. The structural information obtained through the exploitation of a paramagnetic center are discussed for some Cu2+ -binding proteins and for Ca2+ -binding proteins, where the replacement of a diamagnetic metal ion with suitable paramagnetic metal ions suggests novel approaches to the structural characterization of proteins containing diamagnetic and NMR-silent metal ions.     

Probing protein dynamics by nuclear magnetic resonance

Proteins are dynamic molecules that often undergo conformational changes while performing their specific functions, such as target recognition, ligand binding and catalysis. NMR spectroscopy is uniquely suited to study protein dynamics, because site-specific information can be obtained for motions that span a broad range of time scales. The information obtained from NMR dynamics experiments has provided insights into specific structural changes or conformational energetics associated with molecular function. In the last decade, a number of new advancements in NMR methodologies have further extended our ability to characterize protein dynamics. Here, we present an overview of current NMR technology that is used to monitor the dynamic properties of proteins.     

核磁共振技术在土壤-植物-大气连续体研究中的应用

植物体内的水分状态与传输过程是土壤-植物-大气连续体(SPAC)水分传输理论的核心内容,也是研究植物水分利用与调控的基础.植物体内水分的传输过程受外界环境影响较大,植物需要通过对体内水分状态的适当调整来适应环境变化和维持自身的生长发育.由于蒸发通量、压力室、高压流速仪、热脉冲等传统检测方法往往会对植株造成破坏和损伤,因此难以准确反映和定量描述植物体内水分传输的真实过程.核磁共振技术(NMR)由于其无损、非侵入的特点,在植物水分分布和传输相关研究中日益得到关注.本文概述了NMR在检测植物体内水分分布、传输以及含量测定等方面的研究进展,还分析了目前NMR技术在SPAC系统研究中存在的问题及可能的解决方法,并指出NMR技术将来可能在植物水分生理、植物与环境互作以及水分代谢等相关研究领域的应用.NMR技术在SPAC系统研究中的应用在我国仍处于初级阶段,开发户外便携式、开放式检测仪器是NMR技术在SPAC研究领域进一步应用和推广的关键所在.     

Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts

The biochemical mode-of-action (MOA) for herbicides and other bioactive compounds can be rapidly and simultaneously classified by automated pattern recognition of the metabonome that is embodied in the 1H NMR spectrum of a crude plant extract. The ca. 300 herbicides that are used in agriculture today affect less than 30 different biochemical pathways. In this report, 19 of the most interesting MOAs were automatically classified. Corn (Zea mays) plants were treated with various herbicides such as imazethapyr, glyphosate, sethoxydim, and diuron, which represent various biochemical modes-of-action such as inhibition of specific enzymes (acetohydroxy acid synthase [AHAS], protoporphyrin IX oxidase [PROTOX], 5-enolpyruvylshikimate-3-phosphate synthase [EPSPS], acetyl CoA carboxylase [ACC-ase], etc.), or protein complexes (photosystems I and II), or major biological process such as oxidative phosphorylation, auxin transport, microtubule growth, and mitosis. Crude isolates from the treated plants were subjected to 1H NMR spectroscopy, and the spectra were classified by artificial neural network analysis to discriminate the herbicide modes-of-action. We demonstrate the use and refinement of the method, and present cross-validated assignments for the metabolite NMR profiles of over 400 plant isolates. The MOA screen also recognizes when a new mode-of-action is present, which is considered extremely important for the herbicide discovery process, and can be used to study deviations in the metabolism of compounds from a chemical synthesis program. The combination of NMR metabolite profiling and neural network classification is expected to be similarly relevant to other metabonomic profiling applications, such as in drug discovery.     

Refined solution structure of the 82-kDa enzyme malate synthase G from joint NMR and synchrotron SAXS restraints

Determination of the accurate three-dimensional structure of large proteins by NMR remains challenging due to a loss in the density of experimental restraints resulting from the often prerequisite perdeuteration. Solution small-angle scattering, which carries long-range translational information, presents an opportunity to enhance the structural accuracy of derived models when used in combination with global orientational NMR restraints such as residual dipolar couplings (RDCs) and residual chemical shift anisotropies (RCSAs). We have quantified the improvements in accuracy that can be obtained using this strategy for the 82 kDa enzyme Malate Synthase G (MSG), currently the largest single chain protein solved by solution NMR. Joint refinement against NMR and scattering data leads to an improvement in structural accuracy as evidenced by a decrease from approximately 4.5 to approximately 3.3 A of the backbone rmsd between the derived model and the high-resolution X-ray structure, PDB code 1D8C. This improvement results primarily from medium-angle scattering data, which encode the overall molecular shape, rather than the lowest angle data that principally determine the radius of gyration and the maximum particle dimension. The effect of the higher angle data, which are dominated by internal density fluctuations, while beneficial, is also found to be relatively small. Our results demonstrate that joint NMR/SAXS refinement can yield significantly improved accuracy in solution structure determination and will be especially well suited for the study of systems with limited NMR restraints such as large proteins, oligonucleotides, or their complexes.     

Diffusion-ordered NMR spectroscopy: a versatile tool for the molecular weight determination of uncharged polysaccharides

Diffusion-ordered NMR spectroscopy (DOSY) experiments have been carried out on dilute aqueous solutions of uncharged saccharide systems and, in particular, on six well characterized pullulan fractions of different molecular weights. The values of diffusion coefficients and hydrodynamic radii determined for the pullulan fractions are in good agreement with the results obtained with other methodologies such as light scattering. Fitting the diffusion coefficients data as a function of the molecular weight allows for the determination of a calibration curve that can be applied to a wide range of mono-, oligo-, and polysaccharides. Therefore, DOSY is proposed as a versatile tool for achieving a simple estimation of the molecular weight of uncharged polysaccharides. Mixtures of homopolymers of different molecular weight can be nicely separated. An advantage of the method is that the same sample used for the NMR characterization can be used for the molecular weight determination without any further manipulation. Other water soluble polymers, such as poly(ethylene oxide) and poly(vinylpyrrolidone), can be roughly characterized using the same calibration curve.     

Choosing membrane mimetics for NMR structural studies of transmembrane proteins

The native environment of membrane proteins is complex and scientists have felt the need to simplify it to reduce the number of varying parameters. However, experimental problems can also arise from oversimplification which contributes to why membrane proteins are under-represented in the protein structure databank and why they were difficult to study by nuclear magnetic resonance (NMR) spectroscopy. Technological progress now allows dealing with more complex models and, in the context of NMR studies, an incredibly large number of membrane mimetics options are available. This review provides a guide to the selection of the appropriate model membrane system for membrane protein study by NMR, depending on the protein and on the type of information that is looked for. Beside bilayers (of various shapes, sizes and lamellarity), bicelles (aligned or isotropic) and detergent micelles, this review will also describe the most recent membrane mimetics such as amphipols, nanodiscs and reverse micelles. Solution and solid-state NMR will be covered as well as more exotic techniques such as DNP and MAOSS.     

Review: model peptides and the physicochemical approach to beta-amyloids

beta-Amyloid peptides are the main protein components of neuritic plaques and may be important in the pathogenesis of Alzheimer's Disease. The determination of the structure of beta-amyloid fibrils poses a challenge because of the limited solubility of beta-amyloid peptides and the noncrystalline nature of fibrils formed from these peptides. In this paper, we describe several physicochemical approaches which have been used to examine fibrils and the fibrillogenesis of peptide models of beta-amyloid. Recent advances in solid state NMR, such as the DRAWS pulse sequence, have made this approach a particularly attractive one for peptides such as beta-amyloid, which are not yet amenable to high-resolution solution phase NMR and crystallography. The application of solid state NMR techniques has yielded information on a model peptide comprising residues 10-35 of human beta-amyloid and indicates that in fibrils, this peptide assumes a parallel beta-strand conformation, with all residues in exact register. In addition, we discuss the use of block copolymers of Abeta peptides and polyethylene glycol as probes for the pathways of fibrillogenesis. These methods can be combined with other new methods, such as high-resolution synchrotron X-ray diffraction and small angle neutron and X-ray scattering, to yield structural data of relevance not only to disease, but to the broader question of protein folding and self-assembly.     

Recommended strategies for spectral processing and post-processing of 1D <Superscript>1</Superscript>H-NMR data of biofluids with a particular focus on urine

¹H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.     

Multiple loop conformations of peptides predicted by molecular dynamics simulations are compatible with nuclear magnetic resonance

The affinity and selectivity of protein-protein interactions can be fine-tuned by varying the size, flexibility, and amino acid composition of involved surface loops. As a model for such surface loops, we study the conformational landscape of an octapeptide, whose flexibility is chemically steered by a covalent ring closure integrating an azobenzene dye into and by a disulfide bridge additionally constraining the peptide backbone. Because the covalently integrated azobenzene dyes can be switched by light between a bent cis state and an elongated trans state, six cyclic peptide models of strongly different flexibilities are obtained. The conformational states of these peptide models are sampled by NMR and by unconstrained molecular dynamics (MD) simulations. Prototypical conformations and the free-energy landscapes in the high-dimensional space spanned by the phi/psi angles at the peptide backbone are obtained by clustering techniques from the MD trajectories. Multiple open-loop conformations are shown to be predicted by MD particularly in the very flexible cases and are shown to comply with the NMR data despite the fact that such open-loop conformations are missing in the refined NMR structures.