Resonance assignment strategies for the analysis of nmr spectra of proteins

Determination of the high resolution solution structure of a protein using nuclear magnetic resonance (NMR) spectroscopy requires that resonances observed in the NMR spectra be unequivocally assigned to individual nuclei of the protein. With the advent of modern, two-dimensional NMR techniques arose methodologies for assigning the¹H resonances based on 2D, homonuclear¹H NMR experiments. These include the sequential assignment strategy and the main chain directed strategy. These basic strategies have been extended to include newer 3D homonuclear experiments and 2D and 3D heteronuclear resolved and edited methods. Most recently a novel, conceptually new approach to the problem has been introduced that relies on heteronuclear, multidimensional so-called triple resonance experiments for both backbone and sidechain resonance assignments in proteins. This article reviews the evolution of strategies for the assignment of resonances of proteins.     

Spectral processing methods for the removal of t1 noise and solvent artifacts from NMR spectra

Summary A data processing method is described which reduces the effects of t₁ noise artifacts and improves the presentation of 2D NMR spectral data. A t₁ noise profile is produced by measuring the average noise in each column. This profile is then used to determine weighting coefficients for a sliding weighted smoothing filter that is applied to each row, such that the amount of smoothing each point receives is proportional to both its estimated t₁ noise level and the level of t₁ noise of neighbouring points. Thus, points in the worst t₁ noise bands receive the greatest smoothing, whereas points in low-noise regions remain relatively unaffected. In addition, weighted smoothing allows points in low-noise regions to influence neighbouring points in noisy regions. This method is also effective in reducing the noise artifacts associated with the solvent resonance in spectra of biopolymers in aqueous solution. Although developed primarily to improve the quality of 2D NMR spectra of biopolymers prior to automated analysis, this approach should enhance processing of spectra of a wide range of compounds and can be used whenever noise occurs in discrete bands in one dimension of a multi-dimensional spectrum.     

Automation of peak-tracking analysis of stepwise perturbed NMR spectra

We describe a new algorithmic approach able to automatically pick and track the NMR resonances of a large number of 2D NMR spectra acquired during a stepwise variation of a physical parameter. The method has been named Trace in Track (TinT), referring to the idea that a gaussian decomposition traces peaks within the tracks recognised through 3D mathematical morphology. It is capable of determining the evolution of the chemical shifts, intensity and linewidths of each tracked peak.The performances obtained in term of track reconstruction and correct assignment on realistic synthetic spectra were high above 90% when a noise level similar to that of experimental data were considered. TinT was applied successfully to several protein systems during a temperature ramp in isotope exchange experiments. A comparison with a state-of-the-art algorithm showed promising results for great numbers of spectra and low signal to noise ratios, when the graduality of the perturbation is appropriate. TinT can be applied to different kinds of high throughput chemical shift mapping experiments, with quasi-continuous variations, in which a quantitative automated recognition is crucial.     

A novel approach for sequential assignment of 1H, 13C, and 15N spectra of proteins: heteronuclear triple-resonance three-dimensional NMR spectroscopy. Application to calmodulin

A novel approach is described for obtaining sequential assignment of the backbone 1H, 13C, and 15N resonances of larger proteins. The approach is demonstrated for the protein calmodulin (16.7 kDa), uniformly (approximately 95%) labeled with 15N and 13C. Sequential assignment of the backbone residues by standard methods was not possible because of the very narrow chemical shift distribution range of both NH and C alpha H protons in this largely alpha-helical protein. We demonstrate that the combined use of four new types of heteronuclear 3D NMR spectra together with the previously described HOHAHA-HMQC 3D experiment [Marion, D., et al. (1989) Biochemistry 28, 6150-6156] can provide unambiguous sequential assignment of protein backbone resonances. Sequential connectivity is derived from one-bond J couplings and the procedure is therefore independent of the backbone conformation. All the new 3D NMR experiments use 1H detection and rely on multiple-step magnetization transfers via well-resolved one-bond J couplings, offering high sensitivity and requiring a total of only 9 days for the recording of all five 3D spectra. Because the combination of 3D spectra offers at least two and often three independent pathways for determining sequential connectivity, the new assignment procedure is easily automated. Complete assignments are reported for the proton, carbon, and nitrogen backbone resonances of calmodulin, complexed with calcium.     

An improved ultrafast 2D NMR experiment: Towards atom-resolved real-time studies of protein kinetics at multi-Hz rates

Multidimensional NMR spectroscopy is a well-established technique for the characterization of structure and fast-time-scale dynamics of highly populated ground states of biological macromolecules. The investigation of short-lived excited states that are important for molecular folding, misfolding and function, however, remains a challenge for modern biomolecular NMR techniques. Off-equilibrium real-time kinetic NMR methods allow direct observation of conformational or chemical changes by following peak positions and intensities in a series of spectra recorded during a kinetic event. Because standard multidimensional NMR methods required to yield sufficient atom-resolution are intrinsically time-consuming, many interesting phenomena are excluded from real-time NMR analysis. Recently, spatially encoded ultrafast 2D NMR techniques have been proposed that allow one to acquire a 2D NMR experiment within a single transient. In addition, when combined with the SOFAST technique, such ultrafast experiments can be repeated at high rates. One of the problems detected for such ultrafast protein NMR experiments is related to the heteronuclear decoupling during detection with interferences between the pulses and the oscillatory magnetic field gradients arising in this scheme. Here we present a method for improved ultrafast data acquisition yielding higher signal to noise and sharper lines in single-scan 2D NMR spectra. In combination with a fast-mixing device, the recording of ¹H–¹⁵N correlation spectra with repetition rates of up to a few Hertz becomes feasible, enabling real-time studies of protein kinetics occurring on time scales down to a few seconds.     

Use of multiple 13C-labeling strategies and 13C NMR to detect low levels of exogenous metabolites in the presence of large endogenous pools: measurement of glucose turnover in a human subject

A significant problem which may be encountered in 13C NMR studies of metabolism is the contribution that background levels of 13C may make to the observed spectra when low or tracer levels of the 13C label are used. We propose that the introduction of two or more labeled sites in the same tracer molecule is an effective strategy for eliminating or reducing this difficulty and demonstrate its feasibility in an isotope dilution study of glucose turnover in a human volunteer. This approach has two significant advantages over the more common use of a singly enriched labeling strategy: (i) as a consequence of the scalar coupling interactions, multiple-labeled metabolites will yield spectra distinct from those containing natural abundance 13C, and (ii) at a 99% level of enrichment for the precursor, concentration levels which are approximately 1% of the endogenous pools can be detected with approximately equal sensitivity. As a demonstration of this strategy, glucose production in a human subject was determined by continuous infusion of tracer levels of [U-13C6]glucose over a 4-h period and subsequent analysis of plasma levels of the tracer in vitro by NMR. Mass spectroscopy was used on the same samples to provide a basis for comparison of the precision and accuracy of the NMR technique. The results demonstrate the feasibility of the multiply labeled approach for detection by NMR of tracer amounts of label in the presence of a much larger endogenous pool of glucose. The NMR and mass spectrometric data gave quantitatively identical results for the glucose production rate demonstrating that equivalent data may be obtained by both methods.(ABSTRACT TRUNCATED AT 250 WORDS)     

Rapid isolation and identification of minor natural products by LC–MS,LC–SPE–NMR and ECD: Isoflavanones,biflavanones and bisdihydrocoumarins from Ormocarpum kirkii

The combination of the hyphenated techniques LC–MS and LC–SPE–NMR constitutes a powerful platform for the rapid isolation and identification of minor components from natural sources. Electronic circular dichroism (ECD) is a useful tool to determine the absolute configuration of small quantities of chiral molecules. In order to search for minor constituents present in an Ormocarpum kirkii extract, these techniques were applied for the separation and structure elucidation of a series of isoflavanones, biflavanones and biscoumarins. After optimization of chromatographic conditions and subsequent isolation, MS and 1D and 2D NMR data were collected. Experimental and calculated ECD spectra were used in conjunction with NMR data to confirm the absolute configuration of these compounds. Eight compounds were identified for the first time and six have been previously reported. The present approach offers a strategy for accelerating research on natural products.     

Clean absorption mode NMR data acquisition based on time-proportional phase incrementation

Clean absorption mode NMR data acquisition is presented based on mirrored time domain sampling and widely used time-proportional phase incrementation (TPPI) for quadrature detection. The resulting NMR spectra are devoid of dispersive frequency domain peak components. Those peak components exacerbate peak identification and shift peak maxima, and thus impede automated spectral analysis. The new approach is also of unique value for obtaining clean absorption mode reduced-dimensionality projection NMR spectra, which can rapidly provide high-dimensional spectral information for high-throughput NMR structure determination.     

2D NMR metabonomic analysis: a novel method for automated peak alignment

MOTIVATION: Comparative metabolic profiling by nuclear magnetic resonance (NMR) is showing increasing promise for identifying inter-individual differences to drug response. Two dimensional (2D) (1)H (13)C NMR can reduce spectral overlap, a common problem of 1D (1)H NMR. However, the peak alignment tools for 1D NMR spectra are not well suited for 2D NMR. An automated and statistically robust method for aligning 2D NMR peaks is required to enable comparative metabonomic analysis using 2D NMR. RESULTS: A novel statistical method was developed to align NMR peaks that represent the same chemical groups across multiple 2D NMR spectra. The degree of local pattern match among peaks in different spectra is assessed using a similarity measure, and a heuristic algorithm maximizes the similarity measure for peaks across the whole spectrum. This peak alignment method was used to align peaks in 2D NMR spectra of endogenous metabolites in liver extracts obtained from four inbred mouse strains in the study of acetaminophen-induced liver toxicity. This automated alignment method was validated by manual examination of the top 50 peaks as ranked by signal intensity. Manual inspection of 1872 peaks in 39 different spectra demonstrated that the automated algorithm correctly aligned 1810 (96.7%) peaks. AVAILABILITY: Algorithm is available upon request.     

Use of relaxation-edited one-dimensional and two dimensional nuclear magnetic resonance spectroscopy to improve detection of small metabolites in blood plasma

The 1H nuclear magnetic resonance (NMR) spectra of biological samples, such as blood plasma and tissues, are information rich but data complex owing to superposition of the resonances from a multitude of different chemical entities in multiple-phase compartments, hampering detection and subsequent resonance assignments. To overcome these problems, several spectral-editing NMR experiments are described here, combining spin-relaxation filters (based on T(1), T(rho), and T(2)) with both one-dimensional and two-dimensional (2D) NMR spectroscopy. These techniques enable the separation of NMR resonances based on their relaxation times and allow simplification of the complex spectra. In this paper, the approach is exemplified using a control human blood plasma, which is a complex mixture of proteins, lipoproteins, and small-molecule metabolites. In the case of T(1rho)- and T(2)-edited 2D NMR experiments, a "flip-back" pulse was introduced after the relaxation editing to make the phase cycling of the "relaxation filter" and the 2D NMR part independent, thus enabling easy implementation of the phase-sensitive 2D NMR experiments. These methods also permit much higher receiver gains to be used to reduce digitization error, in particular, for the small resonances, which are sometimes vitally important for metabonomics studies. Both pulse sequences and experimental results are discussed for T(1)-, T(1rho)-, and T(2)-filtered COSY, T(2)-filtered phase-sensitive DQF-COSY, and T(1), T(1rho)-, and T(2)-filtered TOCSY NMR.     

Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson Gap scheduling

The fast Fourier transformation has been the gold standard for transforming data from time to frequency domain in many spectroscopic methods, including NMR. While reliable, it has as a drawback that it requires a grid of uniformly sampled data points. This needs very long measuring times for sampling in multidimensional experiments in all indirect dimensions uniformly and even does not allow reaching optimal evolution times that would match the resolution power of modern high-field instruments. Thus, many alternative sampling and transformation schemes have been proposed. Their common challenges are the suppression of the artifacts due to the non-uniformity of the sampling schedules, the preservation of the relative signal amplitudes, and the computing time needed for spectra reconstruction. Here we present a fast implementation of the Iterative Soft Thresholding approach (istHMS) that can reconstruct high-resolution non-uniformly sampled NMR data up to four dimensions within a few hours and make routine reconstruction of high-resolution NUS 3D and 4D spectra convenient. We include a graphical user interface for generating sampling schedules with the Poisson-Gap method and an estimation of optimal evolution times based on molecular properties. The performance of the approach is demonstrated with the reconstruction of non-uniformly sampled medium and high-resolution 3D and 4D protein spectra acquired with sampling densities as low as 0.8%. The method presented here facilitates acquisition, reconstruction and use of multidimensional NMR spectra at otherwise unreachable spectral resolution in indirect dimensions.     

Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching

MOTIVATION: A major problem for current peak detection algorithms is that noise in mass spectrometry (MS) spectra gives rise to a high rate of false positives. The false positive rate is especially problematic in detecting peaks with low amplitudes. Usually, various baseline correction algorithms and smoothing methods are applied before attempting peak detection. This approach is very sensitive to the amount of smoothing and aggressiveness of the baseline correction, which contribute to making peak detection results inconsistent between runs, instrumentation and analysis methods. RESULTS: Most peak detection algorithms simply identify peaks based on amplitude, ignoring the additional information present in the shape of the peaks in a spectrum. In our experience, 'true' peaks have characteristic shapes, and providing a shape-matching function that provides a 'goodness of fit' coefficient should provide a more robust peak identification method. Based on these observations, a continuous wavelet transform (CWT)-based peak detection algorithm has been devised that identifies peaks with different scales and amplitudes. By transforming the spectrum into wavelet space, the pattern-matching problem is simplified and in addition provides a powerful technique for identifying and separating the signal from the spike noise and colored noise. This transformation, with the additional information provided by the 2D CWT coefficients can greatly enhance the effective signal-to-noise ratio. Furthermore, with this technique no baseline removal or peak smoothing preprocessing steps are required before peak detection, and this improves the robustness of peak detection under a variety of conditions. The algorithm was evaluated with SELDI-TOF spectra with known polypeptide positions. Comparisons with two other popular algorithms were performed. The results show the CWT-based algorithm can identify both strong and weak peaks while keeping false positive rate low. AVAILABILITY: The algorithm is implemented in R and will be included as an open source module in the Bioconductor project.     

A simple protocol to study blue copper proteins by NMR.

In the case of oxidized plastocyanin from Synechocystis sp. PCC6803, an NMR approach based on classical two and three dimensional experiments for sequential assignment leaves unobserved 14 out of 98 amino acids. A protocol which simply makes use of tailored versions of 2D HSQC and 3D CBCA(CO)NH and CBCANH leads to the identification of nine of the above 14 residues. The proposed protocol differs from previous approaches in that it does not involve the use of unconventional experiments designed specifically for paramagnetic systems, and does not exploit the occurrence of a corresponding diamagnetic species in chemical exchange with the blue copper form. This protocol is expected to extend the popularity of NMR in the structural studies of copper (II) proteins, allowing researchers to increase the amount of information available via NMR on the neighborhood of a paramagnetic center without requiring a specific expertise in the field. The resulting 3D spectra are standard spectra that can be handled by any standard software for protein NMR data analysis.     

Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids

One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.     

Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS

Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [¹H,¹H]-NOESY spectra during de novoprotein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated de novoprotein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novoprotein structure determination by NMR.     

VirtualSpectrum,a tool for simulating peak list for multi-dimensional NMR spectra

NMR spectroscopy is a widely used technique for characterizing the structure and dynamics of macromolecules. Often large amounts of NMR data are required to characterize the structure of proteins. To save valuable time and resources on data acquisition, simulated data is useful in the developmental phase, for data analysis, and for comparison with experimental data. However, existing tools for this purpose can be difficult to use, are sometimes specialized for certain types of molecules or spectra, or produce too idealized data. Here we present a fast, flexible and robust tool, VirtualSpectrum, for generating peak lists for most multi-dimensional NMR experiments for both liquid and solid state NMR. It is possible to tune the quality of the generated peak lists to include sources of artifacts from peak overlap, noise and missing signals. VirtualSpectrum uses an analytic expression to represent the spectrum and derive the peak positions, seamlessly handling overlap between signals. We demonstrate our tool by comparing simulated and experimental spectra for different multi-dimensional NMR spectra and analyzing systematically three cases where overlap between peaks is particularly relevant; solid state NMR data, liquid state NMR homonuclear ¹H and ¹⁵N-edited spectra, and 2D/3D heteronuclear correlation spectra of unstructured proteins. We analyze the impact of protein size and secondary structure on peak overlap and on the accuracy of structure determination based on data of different qualities simulated by VirtualSpectrum.     

Visualizing the principal component of 1H,15N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C

Laboratories often repeatedly determine the structure of a given protein under a variety of conditions, mutations, modifications, or in a number of states. This approach can be cumbersome and tedious. Given then a database of structures, identifiers, and corresponding (1)H,(15)N-HSQC NMR spectra for homologous proteins, we investigated whether structural information could be ascertained for a new homolog solely from its (1)H,(15)N-HSQC NMR spectrum. We addressed this question with two different approaches. First, we used a semi-automated approach with the program, ORBplus. ORBplus looks for patterns in the chemical shifts and correlates these commonalities to the explicit property of interest. ORBplus ranks resonances based on consistency of the magnitude and direction of the chemical shifts within the database, and the chemical shift correlation of the unknown protein with the database. ORBplus visualizes the results by a histogram and a vector diagram, and provides residue specific predictions on structural similarities with the database. The second method we used was partial least squares (PLS), which is a multivariate statistical technique used to correlate response and predictor variables. We investigated the ability of these methods to predict the tertiary structure of the contractile regulatory protein troponin C. Troponin C undergoes a closed-to-open conformational change, which is coupled to its function in muscle. We found that both ORBplus and PLS were able to identify patterns in the (1)H,(15)N-HSQC NMR data from different states of troponin C that correlated to its conformation.     

Computer aided evaluation of two-dimensional NMR spectra of proteins

A computer program for the automatic evaluation of two-dimensional NMR spectra of peptides and proteins has been developed. The used strategy is described, the advantages and limits of this approach are discussed. The program was successfully tested on a COSY-spectrum of the neuropeptide Glp-Pro-Pro-Gly-Gly-Ser-Lys-Val-Ile-Leu-Phe from hydra, resulting in a drastic reduction of the time needed for the evaluation of two-dimensional NMR data.     

Covariance NMR in higher dimensions: application to 4D NOESY spectroscopy of proteins

Elucidation of high-resolution protein structures by NMR spectroscopy requires a large number of distance constraints that are derived from nuclear Overhauser effects between protons (NOEs). Due to the high level of spectral overlap encountered in 2D NMR spectra of proteins, the measurement of high quality distance constraints requires higher dimensional NMR experiments. Although four-dimensional Fourier transform (FT) NMR experiments can provide the necessary kind of spectral information, the associated measurement times are often prohibitively long. Covariance NMR spectroscopy yields 2D spectra that exhibit along the indirect frequency dimension the same high resolution as along the direct dimension using minimal measurement time. The generalization of covariance NMR to 4D NMR spectroscopy presented here exploits the inherent symmetry of certain 4D NMR experiments and utilizes the trace metric between donor planes for the construction of a high-resolution spectral covariance matrix. The approach is demonstrated for a 4D (13)C-edited NOESY experiment of ubiquitin. The 4D covariance spectrum narrows the line-widths of peaks strongly broadened in the FT spectrum due to the necessarily short number of increments collected, and it resolves otherwise overlapped cross peaks allowing for an increase in the number of NOE assignments to be made from a given dataset. At the same time there is no significant decrease in the positive predictive value of observing a peak as compared to the corresponding 4D Fourier transform spectrum. These properties make the 4D covariance method a potentially valuable tool for the structure determination of larger proteins and for high-throughput applications in structural biology.     

Structure analyses of DNA oligomers by use of heteronuclear 2D NMR.

DNA oligomer d(CGGAAGACTCTCCTCCG):d(CGGAGGAGAGTCTTCCG) named UASG (17mer M.W. = 11 kDa) was studied by 1H NMR and heteronuclear two dimensional (2D) NMR. All the labile protons and half of the non-exchangeable protons were assigned by use of conventional 1H 2D experiments including NOESY using 1-1 echo excitation for water suppression. Signal degeneracy in the sugar proton region made it difficult to make assignments of the remaining half of the non-exchangeable protons of the oligomer in 1H 2D spectra. Here we report a new strategy using 1H/13C and 1H/31P heteronuclear single-quantum correlation spectroscopy combined with homonuclear three dimensional NOESY-TOCSY. By this strategy, most of the proton resonances of the oligomer have been assigned, and it turned out that the whole conformation of the oligomer is B-form like.