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.     

Reducing the overlap problem in the proton NMR spectra of oligosaccharides by application of pseudo-four-dimensional homonuclear HOHAHA-HOHAHA-COSY.

A new homonuclear NMR experiment is described for the assignment of the proton NMR spectra of oligosaccharides, namely HOHAHA-HOHAHA-COSY (where HOHAHA is homonuclear Hartmann-Hahn spectroscopy and COSY is correlated spectroscopy). While this technique may formally be thought of as a four-dimensional NMR experiment, by use of selective pulses it is demonstrated that the analogous pseudo-four-dimensional experiment is a valuable improvement over conventional three-dimensional HOHAHA-COSY, in that the degree of resonance overlap is markedly reduced by the dispersion of resonances into a fourth effective dimension. The technique is demonstrated by application to the biantennary nonasaccharide Gal beta 1-4-GlcNAc beta 1-2Man alpha 1-6(Gal beta 1-4GlcNAc beta 1-2Man alpha 1-3)Man-beta 1-4GlcNAc beta 1-4GlcNAc.     

StePSIM – a method for stepwise peak selection and identification of metabolites in 1 H NMR spectra

A method for stepwise selection of peaks in NMR spectra from multiple groups is described. This method is based on initial peak-finding among the spectra and uses jacknife classification performance as the basis for selection of peaks. The selection process is followed by the construction of correlation maps to identify sets of multiplets that are related to each of the selected peaks, aiding in the identification of metabolites that are responsible for differences among the groups. For illustrative purposes, this methodology is applied to a data set that contains 52 spectra from renal cell carcinoma and normal renal tissue samples. The new method is denoted as StePSIM, Stepwise Peak Selection and Identification of Metabolites. Research partially supported by NCI 1 R21 CA89671-01A1 and NIH NCRR 02584     

NMR spectra of some cyanosteroids

The MMR Spectra of thirty-four cyanosteroids and of thirty-four model steroids are discussed. The chemical shifts of the protons at C-18, C-19 and C-21 are used to study the cyanosteroid structures and the specific corrections Δδ^∗ are calculated.     

NMR spectra of fluorinated carbohydrates

Recent advances in structural and conformational analysis of fluorinated carbohydrates by NMR spectroscopy are reviewed. Characteristic 1H, 13C, and 19F NMR chemical shifts and coupling constants for selected examples are given and the spectral data of a series of fluorinated carbohydrates were collected in continuation of the review of Csuk and Gl?nzer [Adv. Carbohydr. Chem. Biochem., 46 (1988) 73-177].     

Parallel acquisition of multi-dimensional spectra in protein NMR

We introduce the use of multiple receivers applied in parallel for simultaneously recording multi-dimensional data sets of proteins in a single experiment. The utility of the approach is established through the introduction of the 2D (15)N,(1)H(N)||(13)CO HSQC experiment in which a pair of two-dimensional (15)N,(1)H(N) and (15)N,(13)CO spectra are recorded. The methodology is further extended to higher dimensionality via the 3D (1)H(N)||(13)CO HNCA in which a pair of data sets recording (13)C(α),(15)N,(1)H(N) and (13)C(α),(15)N,(13)CO chemical shifts are acquired. With the anticipated increases in probe sensitivity it is expected that multiple receiver experiments will become an important approach for efficient recording of NMR data.     

Phase-shift presaturation for water peak suppression in biomolecular NMR experiments

The phase-shift presaturation technique for water suppression is further improved with effective phase cycling. In the two-dimensional NMR COSY, NOESY and HMQC experiments of biosamples, the water sup-pression factor reaches the order of 10 , making it possible to detect 13C NMR signals in extremely diluted (2 mmol/L) aqueous solutions.     

Automated structure determination from NMR spectra

Automated methods for protein structure determination by NMR have increasingly gained acceptance and are now widely used for the automated assignment of distance restraints and the calculation of three-dimensional structures. This review gives an overview of the techniques for automated protein structure analysis by NMR, including both NOE-based approaches and methods relying on other experimental data such as residual dipolar couplings and chemical shifts, and presents the FLYA algorithm for the fully automated NMR structure determination of proteins that is suitable to substitute all manual spectra analysis and thus overcomes a major efficiency limitation of the NMR method for protein structure determination.     

NMR spectra of C-24 isomeric sterols

Cholesterol and four pairs of C-24 isomeric sterols, campesterol-22,23-dihydrobrassicasterol, α-spinasterol-chondrillasterol, stigmasterol-poriferasterol, and sitosterol-22,23-dihydroporiferasterol were studied by NMR spectroscopy and their spectra are presented. The NMR spectra of three of the pairs of isomeric sterols recorded at 100 MHz could be differentiated from each other, although at 60 MHz only the spectra of campesterol (24α-methylcholesterol) and 22,23-dihydrobrassicasterol (24β-methylcholesterol) showed differences. Sitosterol and 22,23-dihydroporiferasterol, the pair of sterols that showed no differences in their NMR spectra are readily differentiated by the physical properties of their acetates. The practical application of NMR spectroscopy to several problems concerning the C-24 isomeric sterols is demonstrated.     

The 220 MHz NMR spectra of phytosterols

The 220MHz NMR spectra of forty two steroids are reported. Eight pairs of C-24 epimers (24α- and 24β) and two pairs of double bond isomers (cis and trans) can be distinguished by this technique. The influence of substituents, solvents and stereochemistry on methyl group chemical shifts is discussed.     

Sequential resonance assignments in 1H NMR spectra of oligonucleotides by two-dimensional NMR spectroscopy

A sequential assignment procedure is outlined, based on two-dimensional NOE ( NOESY ) and two-dimensional J-correlated spectroscopy ( COSY ), for assigning the nonexchangeable proton resonances in NMR spectra of oligonucleotides. As presented here the method is generally applicable to right-handed helical oligonucleotides of intermediate size. We applied it to a lac operator DNA fragment consisting of d( TGAGCGG ) and d( CCGCTCA ) and obtained complete assignments for the adenine H8, guanine H8, cytosine H6 and H5, thymine H6 and 5-methyl, and the deoxyribose H1', H2', H2", H3', and H4' resonances, as well as some H5', H5" (pairwise) assignments. These assignments are required for the analysis of two-dimensional NOE and J-coupling data in terms of the solution structure of oligonucleotides.     

Chemical shift optimization in multidimensional NMR spectra by AUREMOL-SHIFTOPT

A problem often encountered in multidimensional NMR-spectroscopy is that an existing chemical shift list of a protein has to be used to assign an experimental spectrum but does not fit sufficiently well for a safe assignment. A similar problem occurs when temperature or pressure series of n-dimensional spectra are to be evaluated automatically. We have developed two different algorithms, AUREMOL-SHIFTOPT1 and AUREMOL-SHIFTOPT2 that fulfill this task. In the present contribution their performance is analyzed employing a set of simulated and experimental two-dimensional and three-dimensional spectra obtained from three different proteins. A new z-score based on atom and amino acid specific chemical shift distributions is introduced to weight the chemical shift contributions in different dimensions properly.     

Tellurium-125 NMR and mass spectra of dithiotellurides

The preparation, ¹²⁵Te NMR and mass spectra of some dithiotellurides, Te(RS)₂ (R = Ph, 2-PhCOOH, CPh₃, CH₂Ph, 3-PrCOOH, n-Bu, i-Pr, t-Bu) are discussed. The ¹²⁵Te chemical shifts have been found to lie within a range spanning ca. 690 ppm and correlate with the pK_a values of the parent thiols. The mass spectra of the alkyl derivatives (R = n-Bu, i-Pr, t-Bu) indicate an initial step-wise loss of alkenyl groups followed by the elimination of hydrogen sulfide from the resultant bis(hydrosulfido)-tellurium ion.     

Editing and diagonal peak suppression in three-dimensional HCCH protein NMR correlation experiments

A novel three-dimensional (3D) HCCH NMR experiment is introduced. It involves ¹³C-¹³C COSY or TOCSY coherence transfer plus two independent editing steps according to the number of protons attached to the individual carbons before and after the ¹³C-¹³C homonuclear mixing. This double editing leads to simplification of HCCH protein side chain spectra that otherwise are prone to spectral overlap. Another interesting feature is amino acid selectivity, i.e. that the presence of certain correlations in a doubly edited HCCH subspectrum gives a clue as to assignment to a particular subgroup of amino acids or segments thereof. Finally, the selection of two different multiplicities in the two editing steps leads to diagonal peak suppression in the ¹H-¹H (3D spectrum recorded with two ¹H and one ¹³C dimension) or the ¹³C-¹³C (3D spectrum recorded with one ¹H and two ¹³C dimensions) two-dimensional projection. The new experiment is demonstrated using a ¹³C,¹⁵N-labeled protein sample, chymotrypsin inhibitor 2, at 500 MHz.     

NMR spectra of exchangeable protons of pyridoxal phosphate-dependent enzymes

We have recorded 1H NMR spectra in H2O for exchangeable protons of four pyridoxal phosphate-dependent enzymes: D-serine dehydratase, aspartate aminotransferase, tryptophan: indole-lyase and glutamate decarboxylase. The molecular masses range from 48-250 kDa. In every case there are downfield peaks which are lost when the apoenzyme is formed. In most cases some peaks shift in response to interactions with substrates and inhibitors and with changes in pH. We associate one downfield resonance with the proton on the ring nitrogen of the coenzyme and others with imidazole groups that interact with coenzyme or substrates. The chemical shift for the coenzyme-bound proton differs for free enzyme, substrate Schiff base or quinonoid forms.     

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.     

Addressing the overlap problem in the quantitative analysis of two dimensional NMR spectra: Application to <Superscript>15</Superscript>N relaxation measurements

A quantitative analysis of 2D ¹H-¹⁵N spectra is often complicated by resonance overlap. Here a simple method is presented for resolving overlapped correlations by recording 2D projection planes from HNCO data sets. Applications are presented involving the measurement of ¹⁵N T₁ relaxation rates in a high molecular weight protein, malate synthase G, and in a system that exchanges between folded and unfolded states, the drkN SH3 domain. By supplementing relaxation data recorded in the conventional way as a series of 2D ¹H-¹⁵N data sets with a series of a pair of projection planes the number of dynamics probes is increased significantly for both systems studied.     

Bayesian signal extraction from noisy FT NMR spectra

Summary The statistical interpretation of the histogram representation of NMR spectra is described, leading to an estimation of the probability density function of the noise. The white-noise and Gaussian hypotheses are discussed, and a new estimator of the noise standard deviation is derived from the histogram strategy. The Bayesian approach to NMR signal detection is presented. This approach homogeneously combines prior knowledge, obtained from the histogram strategy, together with the posterior information resulting from the test of presence of a set of reference shapes in the neighbourhood of each data point. This scheme leads to a new strategy in the local detection of NMR signals in 2D and 3D spectra, which is illustrated by a complete peak-picking algorithm.     

Peptide mass fingerprinting peak intensity prediction: extracting knowledge from spectra

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry has become a valuable tool in proteomics. With the increasing acquisition rate of mass spectrometers, one of the major issues is the development of accurate, efficient and automatic peptide mass fingerprinting (PMF) identification tools. Current tools are mostly based on counting the number of experimental peptide masses matching with theoretical masses. Almost all of them use additional criteria such as isoelectric point, molecular weight, PTMs, taxonomy or enzymatic cleavage rules to enhance prediction performance. However, these identification tools seldom use peak intensities as parameter as there is currently no model predicting the intensities based on the physicochemical properties of peptides. In this work, we used standard datamining methods such as classification and regression methods to find correlations between peak intensities and the properties of the peptides composing a PMF spectrum. These methods were applied on a dataset comprising a series of PMF experiments involving 157 proteins. We found that the C4.5 method gave the more informative results for the classification task (prediction of the presence or absence of a peptide in a spectra) and M5' for the regression methods (prediction of the normalized intensity of a peptide peak). The C4.5 result correctly classified 88% of the theoretical peaks; whereas the M5' peak intensities had a correlation coefficient of 0.6743 with the experimental peak intensities. These methods enabled us to obtain decision and model trees that can be directly used for prediction and identification of PMF results. The work performed permitted to lay the foundations of a method to analyze factors influencing the peak intensity of PMF spectra. A simple extension of this analysis could lead to improve the accuracy of the results by using a larger dataset. Additional peptide characteristics or even PMF experimental parameters can also be taken into account in the datamining process to analyze their influence on the peak intensity. Furthermore, this datamining approach can certainly be extended to the tandem mass spectrometry domain or other mass spectrometry derived methods.