Sensitivity gains,linearity, and spectral reproducibility in nonuniformly sampled multidimensional MAS NMR spectra of high dynamic range

Recently, we have demonstrated that considerable inherent sensitivity gains are attained in MAS NMR spectra acquired by nonuniform sampling (NUS) and introduced maximum entropy interpolation (MINT) processing that assures the linearity of transformation between the time and frequency domains. In this report, we examine the utility of the NUS/MINT approach in multidimensional datasets possessing high dynamic range, such as homonuclear ¹³C–¹³C correlation spectra. We demonstrate on model compounds and on 1–73-(U-¹³C,¹⁵N)/74–108-(U-¹⁵N) E. coli thioredoxin reassembly, that with appropriately constructed 50 % NUS schedules inherent sensitivity gains of 1.7–2.1-fold are readily reached in such datasets. We show that both linearity and line width are retained under these experimental conditions throughout the entire dynamic range of the signals. Furthermore, we demonstrate that the reproducibility of the peak intensities is excellent in the NUS/MINT approach when experiments are repeated multiple times and identical experimental and processing conditions are employed. Finally, we discuss the principles for design and implementation of random exponentially biased NUS sampling schedules for homonuclear ¹³C–¹³C MAS correlation experiments that yield high-quality artifact-free datasets.     

SPARTA+: a modest improvement in empirical NMR chemical shift prediction by means of an artificial neural network

NMR chemical shifts provide important local structural information for proteins and are key in recently described protein structure generation protocols. We describe a new chemical shift prediction program, SPARTA+, which is based on artificial neural networking. The neural network is trained on a large carefully pruned database, containing 580 proteins for which high-resolution X-ray structures and nearly complete backbone and ¹³C^β chemical shifts are available. The neural network is trained to establish quantitative relations between chemical shifts and protein structures, including backbone and side-chain conformation, H-bonding, electric fields and ring-current effects. The trained neural network yields rapid chemical shift prediction for backbone and ¹³C^β atoms, with standard deviations of 2.45, 1.09, 0.94, 1.14, 0.25 and 0.49 ppm for δ¹⁵N, δ¹³C’, δ¹³C^α, δ¹³C^β, δ¹H^α and δ¹H^N, respectively, between the SPARTA+ predicted and experimental shifts for a set of eleven validation proteins. These results represent a modest but consistent improvement (2–10%) over the best programs available to date, and appear to be approaching the limit at which empirical approaches can predict chemical shifts.     

Performance tuning non-uniform sampling for sensitivity enhancement of signal-limited biological NMR

Non-uniform sampling (NUS) has been established as a route to obtaining true sensitivity enhancements when recording indirect dimensions of decaying signals in the same total experimental time as traditional uniform incrementation of the indirect evolution period. Theory and experiments have shown that NUS can yield up to two-fold improvements in the intrinsic signal-to-noise ratio (SNR) of each dimension, while even conservative protocols can yield 20–40 % improvements in the intrinsic SNR of NMR data. Applications of biological NMR that can benefit from these improvements are emerging, and in this work we develop some practical aspects of applying NUS nD-NMR to studies that approach the traditional detection limit of nD-NMR spectroscopy. Conditions for obtaining high NUS sensitivity enhancements are considered here in the context of enabling ¹H,¹⁵N-HSQC experiments on natural abundance protein samples and ¹H,¹³C-HMBC experiments on a challenging natural product. Through systematic studies we arrive at more precise guidelines to contrast sensitivity enhancements with reduced line shape constraints, and report an alternative sampling density based on a quarter-wave sinusoidal distribution that returns the highest fidelity we have seen to date in line shapes obtained by maximum entropy processing of non-uniformly sampled data.     

Performance of a neural-network-based determination of amino acid class and secondary structure from 1H-15N NMR data

A neural network which can determine both amino acid class andsecondary structure using NMR data from ¹⁵N-labeled proteinsis described. We have included nitrogen chemical shifts,³J_HN_H coupling constants, -protonchemical shifts, and side-chain proton chemical shifts as input to athree-layer feed-forward network. The network was trained with 456 spinsystems from several proteins containing various types of secondarystructure, and tested on human ubiquitin, which has no sequence homologywith any of the proteins in the training set. A very limited set of data,representative of those from a TOCSY-HSQC and HNHA experiment, was used.Nevertheless, in 60% of the spin systems the correct amino acid classwas among the top two choices given by the network, while in 96% ofthe spin systems the secondary structure was correctly identified. Theperformance of this network clearly shows the potential of the neuralnetwork algorithm in the automation of NMR spectral analysis.     

Application of neural networks to automated assignment of NMR spectra of proteins

Summary Simulated neural networks are described which aid the assignment of protein NMR spectra. A network trained to recognize amino acid type from TOCSY data was trained on 148 assigned spin systems from E. coli acyl carrier proteins (ACPs) and tested on spin systems from spinach ACP, which has a 37% sequence homology with E. coli ACP and a similar secondary structure. The output unit corresponding to the correct amino acid is one of the four most activated units in 83% of the spin systems tested. The utility of this information is illustrated by a second network which uses a constraint satisfaction algorithm to find the best fit of the spin systems to the amino acid sequence. Application to a stretch of 20 amino acids in spinach ACP results in 75% correct sequential assignment. Since the output of the amino acid type identification network can be coupled with a variety of sequential assignment strategies, the approach offers substantial potential for expediting assignment of protein NMR spectra.     

Phase Separation in Binary Mixtures of Bipolar and Monopolar Lipid Dispersions Revealed by H NMR Spectroscopy, Small Angle X-Ray Scattering, and Molecular Theory

Binary mixtures of C₂₀BAS and POPC membranes were studied by solid-state ²H NMR spectroscopy and small angle x-ray scattering (SAXS) over a wide range of concentrations and at different temperatures. Three specifically deuterated C₂₀BAS derivatives—[1′,1′,20′,20′-²H₄]C₂₀BAS, [2′,2′,19′,19′-²H₄]C₂₀BAS, and [10′,11′-²H₂]C₂₀BAS—combined with protiated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), as well as membranes containing POPC-d₃₁ and fully protiated bolalipid, were used in NMR experiments to obtain structural information for the mixtures. The ²H NMR spectra of [10′,11′-²H₂]C₂₀BAS/POPC membrane dispersions reveal that the bolalipid is predominantly in the transmembrane conformation at high bolalipid concentrations (100, 90, and 70 mol %). At ≤50 mol % C₂₀BAS, smaller quadrupolar couplings appear in the spectra, indicating the presence of U-shaped conformers. The proportion of U-shaped bolalipids increases as the amount of POPC in the membrane increases; however, the transmembrane component remains the dominant bolalipid conformation in the membrane even at 45°C and 10 mol % C₂₀BAS, where it accounts for ∼50% of the bolalipid population. The large fraction of C₂₀BAS transmembrane conformers, regardless of the C₂₀BAS/POPC ratio, together with the findings from molecular mean-field theory calculations, suggests the coexistence of phase-separated bolalipid-rich domains and POPC-rich domains. A single lamellar repeat distance was observed in SAXS experiments corresponding to the average repeat spacing expected for C₂₀BAS- and POPC-rich domains. These observations are consistent with the presence of microphase-separated domains in the mixed membrane samples that arise from POPC-C₂₀BAS hydrophobic mismatch.     

1H and 13C nuclear magnetic resonance spectra of the lipids in normal and SV 40 virus-transformed hamster embryo fibroblast membranes

Well resolved ¹H and ¹³C NMR spectra were obtained with normal and SV 40-transformed cell membranes. Estimation of the ratio of ¹³CT₂ values of the normal to transformed cell membranes showed an increased intermolecular motion in the transformed cell membranes. The temperature dependence of the (CH₂)_n line in the ¹H spectra in the temperature range 298–343 °K shows an activation energy for the lateral diffusion of the fluid phospholipid regions in the normal cell membranes while the transformed ones show practically no temperature dependence in this temperature range. The fluidity of the phospholipid region in the transformed cell membrane seems to be significantly higher than that observed in the normal cell material. These data support and extend the findings concerning the mobility of the concanavalin A binding/agglutinating sites on the surface of normal and virus-transformed cells and suggest further approaches to the study of the membrane alterations in tumor cells.     

Global fold of human cannabinoid type 2 receptor probed by solid‐state 13C‐, 15N‐MAS NMR and molecular dynamics simulations

The global fold of human cannabinoid type 2 (CB₂) receptor in the agonist‐bound active state in lipid bilayers was investigated by solid‐state ¹³C‐ and ¹⁵N magic‐angle spinning (MAS) NMR, in combination with chemical‐shift prediction from a structural model of the receptor obtained by microsecond‐long molecular dynamics (MD) simulations. Uniformly ¹³C‐ and ¹⁵N‐labeled CB₂ receptor was expressed in milligram quantities by bacterial fermentation, purified, and functionally reconstituted into liposomes. ¹³C MAS NMR spectra were recorded without sensitivity enhancement for direct comparison of C_α, C_β, and C?O bands of superimposed resonances with predictions from protein structures generated by MD. The experimental NMR spectra matched the calculated spectra reasonably well indicating agreement of the global fold of the protein between experiment and simulations. In particular, the ¹³C chemical shift distribution of C_α resonances was shown to be very sensitive to both the primary amino acid sequence and the secondary structure of CB₂. Thus the shape of the C_α band can be used as an indicator of CB₂ global fold. The prediction from MD simulations indicated that upon receptor activation a rather limited number of amino acid residues, mainly located in the extracellular Loop 2 and the second half of intracellular Loop 3, change their chemical shifts significantly (≥1.5 ppm for carbons and ≥5.0 ppm for nitrogens). Simulated two‐dimensional ¹³C_α(i)? ¹³C?O(i) and ¹³C?O(i)? ¹⁵NH(i + 1) dipolar‐interaction correlation spectra provide guidance for selective amino acid labeling and signal assignment schemes to study the molecular mechanism of activation of CB₂ by solid‐state MAS NMR. Proteins 2014; 82:452–465. © 2013 Wiley Periodicals, Inc.     

Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms

Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but using multimodal data to estimate maize LAI, and the effect of tassels and soil background, remain understudied. Our research aims to (1) determine how multimodal data contribute to LAI and propose a framework for estimating LAI based on remote-sensing data, (2) evaluate the robustness and adaptability of an LAI estimation model that uses multimodal data fusion and deep neural networks (DNNs) in single- and whole growth stages, and (3) explore how soil background and maize tasseling affect LAI estimation. To construct multimodal datasets, our UAV collected red–green–blue, multispectral, and thermal infrared images. We then developed partial least square regression (PLSR), support vector regression, and random forest regression models to estimate LAI. We also developed a deep learning model with three hidden layers. This multimodal data structure accurately estimated maize LAI. The DNN model provided the best estimate (coefficient of determination [R²] = 0.89, relative root mean square error [rRMSE] = 12.92%) for a single growth period, and the PLSR model provided the best estimate (R² = 0.70, rRMSE = 12.78%) for a whole growth period. Tassels reduced the accuracy of LAI estimation, but the soil background provided additional image feature information, improving accuracy. These results indicate that multimodal data fusion using low-cost UAVs and DNNs can accurately and reliably estimate LAI for crops, which is valuable for high-throughput phenotyping and high-spatial precision farmland management.

Multimodal data fusion (red–green–blue, multispectral, and thermal infrared) using low-cost unmanned aerial vehicles in a deep neural network and machine learning framework estimates maize leaf area index     

A NMR experiment for simultaneous correlations of valine and leucine/isoleucine methyls with carbonyl chemical shifts in proteins

A methyl-detected ‘out-and-back’ NMR experiment for obtaining simultaneous correlations of methyl resonances of valine and isoleucine/leucine residues with backbone carbonyl chemical shifts, SIM-HMCM(CGCBCA)CO, is described. The developed pulse-scheme serves the purpose of convenience in recording a single data set for all Ile^δ1, Leu^δ and Val^γ (ILV) methyl positions instead of acquiring two separate spectra selective for valine or leucine/isoleucine residues. The SIM-HMCM(CGCBCA)CO experiment can be used for ILV methyl assignments in moderately sized protein systems (up to ~100 kDa) where the backbone chemical shifts of ¹³C^α, ¹³C_β and ¹³CO are known from prior NMR studies and where some losses in sensitivity can be tolerated for the sake of an overall reduction in NMR acquisition time.     

13C NMR spectra of 1, 3, 6 -trihydroxy-7-methoxy-8-(3, 7 -dimethyl-2,6-octadienyl) xanthone and its dimethyl derivative

The ¹³C NMR spectra of 1, 3, 6-trihydroxy-7-methoxy-8-(3, 7-dimethyl-2, 6-octadienyl)xanthone and its dimethyl derivative are discussed. The data obtained confirmed the assigned structures. The geometrical configuration of the C₁₀ dienyl side-chain has been deduced as trans.     

NMR spectroscopy reveals unexpected structural variation at the protein–protein interface in MHC class I molecules

It is well established that non-uniform sampling (NUS) allows acquisition of multi-dimensional NMR spectra at a resolution that cannot be obtained with traditional uniform acquisition through the indirect dimensions. However, the impact of NUS on the signal-to-noise ratio (SNR) and sensitivity are less well documented. SNR and sensitivity are essential aspects of NMR experiments as they define the quality and extent of data that can be obtained. This is particularly important for spectroscopy with low concentration samples of biological macromolecules. There are different ways of defining the SNR depending on how to measure the noise, and the distinction between SNR and sensitivity is often not clear. While there are defined procedures for measuring sensitivity with high concentration NMR standards, such as sucrose, there is no clear or generally accepted definition of sensitivity when comparing different acquisition and processing methods for spectra of biological macromolecules with many weak signals close to the level of noise. Here we propose tools for estimating the SNR and sensitivity of NUS spectra with respect to sampling schedule and reconstruction method. We compare uniformly acquired spectra with NUS spectra obtained in the same total measuring time. The time saving obtained when only 1/k of the Nyquist grid points are sampled is used to measure k-fold more scans per increment. We show that judiciously chosen NUS schedules together with suitable reconstruction methods can yield a significant increase of the SNR within the same total measurement time. Furthermore, we propose to define the sensitivity as the probability to detect weak peaks and show that time-equivalent NUS can considerably increase this detection sensitivity. The sensitivity gain increases with the number of NUS indirect dimensions. Thus, well-chosen NUS schedules and reconstruction methods can significantly increase the information content of multidimensional NMR spectra of challenging biological macromolecules.     

Synthesis and conformational analysis of carbasugar bioisosteres of α-l-iduronic acid and its methyl glycoside

The synthesis of two novel carbasugar analogues of α-l-iduronic acid is described in which the ring-oxygen is replaced by a methylene group. In analogy with the conformational equilibrium described for α-l-IdopA, the conformation of the carbasugars was investigated by ¹H and ¹³C NMR spectroscopy. Hadamard transform NMR experiments were utilised for rapid acquisition of ¹H,¹³C-HSQC spectra and efficient measurements of heteronuclear long-range coupling constants. Analysis of ¹H NMR chemical shifts and J_H,H coupling constants extracted by a total-lineshape fitting procedure in conjunction with J_H,C coupling constants obtained by three different 2D NMR experiments, viz., ¹H,¹³C-HSQC-HECADE, J-HMBC and IPAP-HSQC-TOCSY-HT, as well as effective proton-proton distances from 1D ¹H,¹H T-ROE and NOE experiments showed that the conformational equilibrium ⁴C₁?²S_5a?¹C₄ is shifted towards ⁴C₁ as the predominant or exclusive conformation. These carbasugar bioisosteres of α-l-iduronic acid do not as monomers show the inherent flexibility that is anticipated to be necessary for biological activity.     

Dimeric Switch of Hakai-truncated Monomers during Substrate Recognition: INSIGHTS FROM SOLUTION STUDIES AND NMR STRUCTURE*

Hakai, an E3 ubiquitin ligase, disrupts cell-cell contacts in epithelial cells and is up-regulated in human colon and gastric adenocarcinomas. Hakai acts through its phosphotyrosine-binding (HYB) domain, which bears a dimeric fold that recognizes the phosphotyrosine motifs of E-cadherin, cortactin, DOK1, and other Src substrates. Unlike the monomeric nature of the SH2 and phosphotyrosine-binding domains, the architecture of the HYB domain consists of an atypical, zinc-coordinated tight homodimer. Here, we report a C-terminal truncation mutant of the HYB domain (HYB^ΔC), comprising amino acids 106–194, which exists as a monomer in solution. The NMR structure revealed that this deletion mutant undergoes a dramatic structural change caused by a rearrangement of the atypical zinc-coordinated unit in the C terminus of the HYB domain to a C₂H₂-like zinc finger in HYB^ΔC. Moreover, using isothermal titration calorimetry, we show that dimerization of HYB^ΔC can be induced using a phosphotyrosine substrate peptide. This ligand-induced dimerization of HYB^ΔC is further validated using analytical ultracentrifugation, size-exclusion chromatography, NMR relaxation studies, dynamic light scattering, and circular dichroism experiments. Overall, these observations suggest that the dimeric architecture of the HYB domain is essential for the phosphotyrosine-binding property of Hakai.     

Carbon-13 NMR studies of C2H5N13C binding to various hemoproteins

The addition of an excess of C₂H₅N¹³C to myoglobin and human adult and fetal hemoglobins, gives three characteristic NMR spectra with new ¹³C resonances respectively at δ = ?10,56 ppm, δ = ?7,03 and ?7,95 ppm and δ = ?6,28 and ?7,95 ppm (CH₃CO₂Na as external standard). These signals correspond to the C₂H₅N¹³C bound to the Fe(II) of the different heme units, according to CO exchange experiments. Characteristic resonances can be assigned to C₂H₅N¹³C bound to α, β and γ subunits. C₂H₅N¹³C appears as a more sensitive probe than ¹³CO for hemoprotein NMR studies.     

Tetraplex Formation of d(GGGGGTTTTT): 1H NMR Study in Solution

Abstract

The oligonucleotide d(G₅T₅) can in principle form a fully matched duplex with G · T pairing and/or a tetraplex. Non-denaturing gel electrophoresis, circular dichroism and NMR experiments show that the tetraplex is exclusively formed by this oligomer in solution. In the presence of its complementary strand d(A₅C₅) at low temperature, d(G₅T₅) forms the tetraplex over the normally expected Watson-Crick duplex. However, when d(G₅T₅) and d(A₅C₅) are mixed together in equimolar amounts and heated for several minutes at 85°C, and then allowed to cool, the product was essentially the Watson-Crick duplex. The lack of resolution in the 500 MHz ¹H NMR spectra and the presence of extensive spin diffusion do not allow us to derive a quantitative structure for the tetraplex from the NMR data. However, we find good qualitative agreement between the NOESY and MINSY data and a theoretically derived stereochemically sound structure in which the G's and T's are part of a parallel tetraplex.     

Identification of helix capping and β-turn motifs from NMR chemical shifts

We present an empirical method for identification of distinct structural motifs in proteins on the basis of experimentally determined backbone and ¹³C^β chemical shifts. Elements identified include the N-terminal and C-terminal helix capping motifs and five types of β-turns: I, II, I′, II′ and VIII. Using a database of proteins of known structure, the NMR chemical shifts, together with the PDB-extracted amino acid preference of the helix capping and β-turn motifs are used as input data for training an artificial neural network algorithm, which outputs the statistical probability of finding each motif at any given position in the protein. The trained neural networks, contained in the MICS (motif identification from chemical shifts) program, also provide a confidence level for each of their predictions, and values ranging from ca 0.7–0.9 for the Matthews correlation coefficient of its predictions far exceed those attainable by sequence analysis. MICS is anticipated to be useful both in the conventional NMR structure determination process and for enhancing on-going efforts to determine protein structures solely on the basis of chemical shift information, where it can aid in identifying protein database fragments suitable for use in building such structures.     

Structure, dynamics and topology of membrane polypeptides by oriented 2H solid-state NMR spectroscopy

Knowledge of the structure, dynamics and interactions of polypeptides when associated with phospholipid bilayers is key to understanding the functional mechanisms of channels, antibiotics, signal- or translocation peptides. Solid-state NMR spectroscopy on samples uniaxially aligned relative to the magnetic field direction offers means to determine the alignment of polypeptide bonds and domains relative to the bilayer normal. Using this approach the ¹⁵N chemical shift of amide bonds provides a direct indicator of the approximate helical tilt, whereas the ²H solid-state NMR spectra acquired from peptides labelled with 3,3,3-²H₃-alanines contain valuable complimentary information for a more accurate analysis of tilt and rotation pitch angles. The deuterium NMR line shapes are highly sensitive to small variations in the alignment of the C_α–C_β bond relative to the magnetic field direction and, therefore, also the orientational distribution of helices relative to the membrane normal. When the oriented membrane samples are investigated with their normal perpendicular to the magnetic field direction, the rate of rotational diffusion can be determined in a semi-quantitative manner and thereby the aggregation state of the peptides can be analysed. Here the deuterium NMR approach is first introduced showing results from model amphipathic helices. Thereafter investigations of the viral channel peptides Vpu_1–27 and Influenza A M2_22–46 are shown. Whereas the ¹⁵N chemical shift data confirm the transmembrane helix alignments of these hydrophobic sequences, the deuterium spectra indicate considerable mosaic spread in the helix orientations. At least two peptide populations with differing rotational correlation times are apparent in the deuterium spectra of the viral channels suggesting an equilibrium between monomeric peptides and oligomeric channel configurations under conditions where solid-state NMR structural studies of these peptides have previously been performed. Dedicated to Prof. K. Arnold on the occasion of his 65th birthday.     

Characterization of Cimetidine–Piroxicam Coprecipitate Interaction Using Experimental Studies and Molecular Dynamic Simulations

The crystalline states of cimetidine and piroxicam, when coprecipitated from solvents containing 1:1 mole ratio, were transformed to amorphous states as observed using powder X-ray diffraction (PXRD). Amorphous forms of drugs generally exhibit higher water solubility than crystalline forms. It is therefore interesting to investigate the interactions that cause the transformation of both the crystalline drugs. Intermolecular interactions between the drugs were determined using Fourier-transform infrared spectroscopy (FTIR) and solid-state ¹³C CP/MAS NMR. Molecular dynamic (MD) simulation was performed for the first time for this type of study to indicate the specific groups involved in the interactions based on radial distribution function (RDF) analyses. RDF is a useful tool to describe the average density of atoms at a distance from a specified atom. FTIR spectra revealed a shift of the C≡N stretching band of cimetidine. The ¹³C CP/MAS NMR spectra indicated downfield shifts of C₁₁, C₁₅ and C₇ of piroxicam. RDF analyses indicated that intermolecular interactions occurred between the amide oxygen atom as well as the pyridyl nitrogen of piroxicam and H-N₃ of cimetidine. The hydrogen atom (O–H) at C₇ interacts with the N₁ of cimetidine. Since the MD simulation results are consistent with, and complementary to the experimental analyses, such simulations could provide a novel strategy for investigating specific interacting groups of drugs in coprecipitates, or in amorphous mixtures.