Complete H and C NMR chemical shift assignments of mono-, di-, and trisaccharides as basis for NMR chemical shift predictions of polysaccharides using the computer program casper

The computer program casper uses ¹H and ¹³C NMR chemical shift data of mono- to trisaccharides for the prediction of chemical shifts of oligo- and polysaccharides. In order to improve the quality of these predictions the ¹H and ¹³C, as well as ³¹P when applicable, NMR chemical shifts of 30 mono-, di-, and trisaccharides were assigned. The reducing sugars gave two distinct sets of NMR resonances due to the α- and β-anomeric forms. In total 35 ¹H and ¹³C NMR chemical shift data sets were obtained from the oligosaccharides. One- and two-dimensional NMR experiments were used for the chemical shift assignments and special techniques were employed in some cases such as 2D ¹H,¹³C-HSQC Hadamard Transform methodology which was acquired approximately 45 times faster than a regular t₁ incremented ¹H,¹³C-HSQC experiment and a 1D ¹H,¹H-CSSF-TOCSY experiment which was able to distinguish spin-systems in which the target protons were only 3.3 Hz apart. The ¹H NMR chemical shifts were subsequently refined using total line-shape analysis with the PERCH NMR software. The acquired NMR data were then utilized in the casper program (http://www.casper.organ.su.se/casper/) for NMR chemical shift predictions of the O-antigen polysaccharides from Klebsiella O5, Shigella flexneri serotype X, and Salmonella arizonae O62. The data were compared to experimental data of the polysaccharides from the two former strains and the lipopolysaccharide of the latter strain showing excellent agreement between predicted and experimental ¹H and ¹³C NMR chemical shifts.     

Expression of doubly labeled Saccharomyces cerevisiae iso-1 ferricytochrome c and (1)H, (13)C and (15)N chemical shift assignments by multidimensional NMR

We have expressed [U-(13)C,(15)N]-labeled Saccharomyces cerevisiae iso-1 cytochrome c C102T;K72A in Escherichia coli with a yield of 11 mg/l of growth medium. Nuclear magnetic resonance (NMR) studies were conducted on the Fe(3+) form of the protein. We report herein chemical shift assignments for amide (1)H and (15)N, (13)C(omicron), (13)C(alpha), (13)C(beta), (1)H(alpha) and (1)H(beta) resonances based upon a series of three-dimensional NMR experiments: HNCA, HN(CO)CA, HNCO, HN(CA)CO, HNCACB, HCA(CO)N, HCCH-TOCSY and HBHA(CBCA)NH. An investigation of the chemical shifts of the threonine residues was also made by using density functional theory in order to help solve discrepancies between (15)N chemical shift assignments reported in this study and those reported previously.     

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.     

Prediction of the anomeric configuration, type of linkage, and residues in disaccharides from 1D (13)C NMR data

A machine learning approach was explored for the prediction of the anomeric configuration, residues, and type of linkages of disaccharides using (13)C NMR chemical shifts. For this study, 154 pyranosyl disaccharides were used that are dimers of the α or β anomers of d-glucose, d-galactose or d-mannose residues bonded through α or β glycosidic linkages of types 1→2, 1→3, 1→4, or 1→6, as well as methoxylated disaccharides. The (13)C NMR chemical shifts of the training set were calculated using the casper (Computer Assisted SPectrum Evaluation of Regular polysaccharides) program, and chemical shifts of the test set were experimental values obtained from the literature. Experiments were performed for (1) classification of the anomeric configuration, (2) classification of the type of linkage, and (3) classification of the residues. Classification trees could correctly classify 67%, 74%, and 38% of the test set for the three tasks, respectively, on the basis of unassigned chemical shifts. The results for the same experiments using Random Forests were 93%, 90%, and 68%, respectively.     

Structural analysis of silk with 13C NMR chemical shift contour plots.

The polymorphic structures of silk fibroins in the solid state were examined on the basis of a quantitative relationship between the 13C chemical shift and local structure in proteins. To determine this relationship, 13C chemical shift contour plots for C alpha and C beta carbons of Ala and Ser residues, and the C alpha chemical shift plot for Gly residues were prepared using atomic co-ordinates from the Protein Data Bank and 13C NMR chemical shift data in aqueous solution reported for 40 proteins. The 13C CP/MAS NMR chemical shifts of Ala, Ser and Gly residues of Bombyx mori silk fibroin in silk I and silk II forms were used along with 13C CP/MAS NMR chemical shifts of Ala residues of Samia cynthia ricini silk fibroin in beta-sheet and alpha-helix forms for the structure analyses of silk fibroins. The allowed regions in the 13C chemical shift contour plots for C alpha and C beta carbons of Ala and Ser residues for the structures in silk fibroins, i.e. Silk II, Silk I and alpha-helix, were determined using their 13C isotropic NMR chemical shifts in the solid state. There are two area of the phi,psi map which satisfy the observed Silk I chemical shift data for both the C alpha and C beta carbons of Ala and Ser residues in the 13C chemical shift contour plots.     

Sequence determination of oligosaccharides and regular polysaccharides using NMR spectroscopy and a novel Web-based version of the computer program CASPER

A WWW-interface to a program for structure elucidation of oligo- and polysaccharides using NMR data, CASPER, is presented. The interface and the underlying program have been extensively tested using published data and it was able to simulate 13C NMR spectra of >200 structures with an average error of about 0.3 ppm/resonance. When applied to the repeating units of Escherichia coli O-antigens the published structures were found among the five highest ranked structures in 75% of the cases. The average deviation between calculated and experimental 13C chemical shifts was 0.45 ppm. Oligosaccharide spectra were calculated with even better accuracy (0.23 ppm/resonance) and the correct structure was ranked 1st or 2nd in all the cases examined. Additional NMR experiments that may be required to distinguish between candidate structures are aided by the assignments provided by the program. This computational approach is also suitable for use in structural confirmation of chemically or enzymatically synthesized oligosaccharides. The program is found at http://www.casper.organ.su.se/casper.     

Automated and assisted RNA resonance assignment using NMR chemical shift statistics

The three-dimensional structure determination of RNAs by NMR spectroscopy relies on chemical shift assignment, which still constitutes a bottleneck. In order to develop more efficient assignment strategies, we analysed relationships between sequence and ¹H and ¹³C chemical shifts. Statistics of resonances from regularly Watson–Crick base-paired RNA revealed highly characteristic chemical shift clusters. We developed two approaches using these statistics for chemical shift assignment of double-stranded RNA (dsRNA): a manual approach that yields starting points for resonance assignment and simplifies decision trees and an automated approach based on the recently introduced automated resonance assignment algorithm FLYA. Both strategies require only unlabeled RNAs and three 2D spectra for assigning the H2/C2, H5/C5, H6/C6, H8/C8 and H1′/C1′ chemical shifts. The manual approach proved to be efficient and robust when applied to the experimental data of RNAs with a size between 20 nt and 42 nt. The more advanced automated assignment approach was successfully applied to four stem-loop RNAs and a 42 nt siRNA, assigning 92–100% of the resonances from dsRNA regions correctly. This is the first automated approach for chemical shift assignment of non-exchangeable protons of RNA and their corresponding ¹³C resonances, which provides an important step toward automated structure determination of RNAs.     

The revised NMR chemical shift data of carrageenans

A new set of (13)C and (1)H NMR chemical shifts of most common carrageenan types is given relative to DSS as the internal standard according to the IUPAC recommendations. Moreover, the chemical shifts of characteristic signals for pyruvate acetal and floridean starch are reported. Additionally, chemical shifts of common internal standards, such as methanol, DMSO and acetone, were measured at different temperatures and pH values.     

Prediction of the anomeric configuration, type of linkage, and residues in disaccharides from 1D C NMR data

A machine learning approach was explored for the prediction of the anomeric configuration, residues, and type of linkages of disaccharides using ¹³C NMR chemical shifts. For this study, 154 pyranosyl disaccharides were used that are dimers of the α or β anomers of d-glucose, d-galactose or d-mannose residues bonded through α or β glycosidic linkages of types 1→2, 1→3, 1→4, or 1→6, as well as methoxylated disaccharides. The ¹³C NMR chemical shifts of the training set were calculated using the casper (Computer Assisted SPectrum Evaluation of Regular polysaccharides) program, and chemical shifts of the test set were experimental values obtained from the literature. Experiments were performed for (1) classification of the anomeric configuration, (2) classification of the type of linkage, and (3) classification of the residues. Classification trees could correctly classify 67%, 74%, and 38% of the test set for the three tasks, respectively, on the basis of unassigned chemical shifts. The results for the same experiments using Random Forests were 93%, 90%, and 68%, respectively.     

An automated system designed for large scale NMR data deposition and annotation: application to over 600 assigned chemical shift data entries to the BioMagResBank from the Riken Structural Genomics/Proteomics Initiative internal database

Biomolecular NMR chemical shift data are key information for the functional analysis of biomolecules and the development of new techniques for NMR studies utilizing chemical shift statistical information. Structural genomics projects are major contributors to the accumulation of protein chemical shift information. The management of the large quantities of NMR data generated by each project in a local database and the transfer of the data to the public databases are still formidable tasks because of the complicated nature of NMR data. Here we report an automated and efficient system developed for the deposition and annotation of a large number of data sets including (1)H, (13)C and (15)N resonance assignments used for the structure determination of proteins. We have demonstrated the feasibility of our system by applying it to over 600 entries from the internal database generated by the RIKEN Structural Genomics/Proteomics Initiative (RSGI) to the public database, BioMagResBank (BMRB). We have assessed the quality of the deposited chemical shifts by comparing them with those predicted from the PDB coordinate entry for the corresponding protein. The same comparison for other matched BMRB/PDB entries deposited from 2001-2011 has been carried out and the results suggest that the RSGI entries greatly improved the quality of the BMRB database. Since the entries include chemical shifts acquired under strikingly similar experimental conditions, these NMR data can be expected to be a promising resource to improve current technologies as well as to develop new NMR methods for protein studies.     

1H, 13C and 15N chemical shift referencing in biomolecular NMR

Summary A considerable degree of variability exists in the way that ¹H, ¹³C and ¹⁵N chemical shifts are reported and referenced for biomolecules. In this article we explore some of the reasons for this situation and propose guidelines for future chemical shift referencing and for conversion from many common ¹H, ¹³C and ¹⁵N chemical shift standards, now used in biomolecular NMR, to those proposed here.Abbreviations TMS tetramethylsilane - TSP 3-(trimethylsilyl)-propionate, sodium salt - DSS 2,2-dimethyl-2-silapentane-5-sulfonate, sodium salt - TFE 2,2,2-trifluoroethanol - DMSO dimethyl sulfoxide     

NMR chemical shift mapping of the binding site of a protein proteinase inhibitor: changes in the (1)H, (13)C and (15)N NMR chemical shifts of turkey ovomucoid third domain upon binding to bovine chymotrypsin A(alpha)

The substrate-like inhibition of serine proteinases by avian ovomucoid domains has provided an excellent model for protein inhibitor-proteinase interactions of the standard type. 1H,15N and 13C NMR studies have been undertaken on complexes formed between turkey ovomucoid third domain (OMTKY3)2 and chymotrypsin A(alpha) (Ctr) in order to characterize structural changes occurring in the Ctr binding site of OMTKY3. 15N and 13C were incorporated uniformly into OMTKY3, allowing backbone resonances to be assigned for OMTKY3 in both its free and complex states. Chemical shift perturbation mapping indicates that the two regions, K13-P22 and N33-A40, are the primary sites in OMTKY3 involved in Ctr binding, in full agreement with the 12 consensus proteinase-contact residues of OMTKY3 defined previously on the basis of X-ray crystallographic and mutational analysis. Smaller chemical shift perturbations in selected other regions may result from minor structural changes on binding. Through-bond 15N-13C correlations between P1-13C' and P1'-15N in two-dimensional H(N)CO and HN(CO) NMR spectra of selectively labeled OMTKY3 complexed with Ctr indicate that the scissile peptide bond between L18 and E19 of the inhibitor is intact in the complex. The chemical shifts of the reactive site peptide bond indicate that it is predominantly trigonal, although the data are not inconsistent with a slight perturbation of the hybridization of the peptide bond toward the first tetrahedral state along the reaction coordinate.     

Assigning stereodiversity of the 27-Me group of furostane-type steroidal saponins via NMR chemical shifts

Applicability of (13)C and (1)H NMR chemical shifts for the assignment of the 25R/25S configuration of the 27-methyl group in the case of furostane-type steroidal saponins has been investigated. A comparative study of (13)C NMR data suggest that chemical shift values for C-20, C-21, C-22, C-23, C-24, C-25, C-26 and C-27 resonances were not much influenced by R/S configuration of the 27-Me group, thus reflecting limited application of (13)C NMR chemical shifts for such stereochemical determinations. In contrast, (1)H NMR chemical shifts (delta(a), delta(b)) for geminal protons of glycosyloxy methylene (H(2)-26) exhibit pronounced dependence and the difference (Delta(ab)=delta(a)-delta(b)) among their chemical shifts [Delta(ab)= or <0.48 for 25R; Delta(ab)= or >0.57 for 25S] seems to be of general applicability for ascertaining 25R/25S orientation of the 27-methyl group of furostane-type steroidal saponins.     

Effect of substitution pattern on 1H, 13C NMR chemical shifts and 1J(CH) coupling constants in heparin derivatives

1H, 13C NMR chemical shifts and 1J(CH) coupling constants were measured for derivatives of heparin containing various sulfation patterns. 1H and 13C chemical shifts varied considerably after introducing electronegative sulfate groups. Chemical shifts of protons linked to carbons changed by up to 1 ppm on substitution with O- and N-sulfate or acetyl groups. Differences up to 10 ppm were detected for 13C chemical shifts in substituted glucosamine, but a less clear dependence was found in iduronate. 1J(CH) values formed two groups, corresponding to either sulfation or non-sulfation at positions 2 and 3 of glucosamine. O-sulfation caused increases up to 6 Hz in 1J(CH) and N-sulfation decreases up to 4 Hz. N-acetylation gave similar 1J(CH) values to N-sulfation. At positions 2 and 3 of iduronate the trend was less marked; 1J(CH) for O-sulfated positions usually increasing. Introduction of sulfate groups influences chemical shift and 1J(CH) values at the position of substitution, but also at more remote positions. 1J(CH) at the glycosidic linkage positions varied between free-amino and N-sulfated compounds, by up to 9 Hz. These results and changes in chemical shift values suggest that iduronate residues and the glycosidic linkages are affected, indicating overall conformational change. This may have important implications for biological activities.     

From NMR chemical shifts to amino acid types: Investigation of the predictive power carried by nuclei

An approach to automatic prediction of the amino acid type from NMR chemical shift values of its nuclei is presented here, in the frame of a model to calculate the probability of an amino acid type given the set of chemical shifts. The method relies on systematic use of all chemical shift values contained in the BioMagResBank (BMRB). Two programs were designed, one (BMRB stats) for extracting statistical chemical shift parameters from the BMRB and another one (RESCUE2) for computing the probabilities of each amino acid type, given a set of chemical shifts. The Bayesian prediction scheme presented here is compared to other methods already proposed: PROTYP RESCUE and PLATON and is found to be more sensitive and more specific. Using this scheme, we tested various sets of nuclei. The two nuclei carrying the most information are C(beta) and H(beta), in agreement with observations made in Grzesiek and Bax, 1993. Based on four nuclei: H(beta), C(beta), C(alpha) and C', it is possible to increase correct predictions to a rate of more than 75%. Taking into account the correlations between the nuclei chemical shifts has only a slight impact on the percentage of correct predictions: indeed, the largest correlation coefficients display similar features on all amino acids.     

Carbon-13 NMR in conformational analysis of nucleic acid fragments. Heteronuclear chemical shift correlation spectroscopy of RNA constituents.

The assignment of the non-quaternary 13C resonances by means of two-dimensional heteronuclear chemical shift correlation spectroscopy is presented for several oligoribonucleotides: The dimers m6(2)AU, m6(2)Am6(2)A and mpUm6(2)A and the trimers m6(2)AUm6(2)A and m4(2)Cm4(2)Cm6(2)A. The temperature and concentration dependency of the 13C chemical shifts are studied with emphasis on the behaviour of the dimer m6(2)AU. The present study shows that in the 5-50 mM range the concentration-dependent chemical shift changes of the ribose carbons are negligible compared to chemical shift changes due to intramolecular events. All compounds studied show a surprising correlation between the chemical shifts of the carbon atoms of the ribose ring and the sugar conformational equilibrium as expressed by the percentage N or S conformer. Thus the chemical shift data can be used to obtain the thermodynamical parameters of the two-state N/S equilibrium. Parameters deduced for m6(2)AU are Tm = 306 K and delta S = -25 cal mol-1 K-1, which values are in satisfactory agreement with results obtained earlier from 1H NMR and from Circular Dichroism.     

An NMR method for the determination of protein binding interfaces using TEMPOL-induced chemical shift perturbations

Background

The determination of protein–protein interfaces is of crucial importance to understand protein function and to guide the design of compounds. To identify protein–protein interface by NMR spectroscopy, ¹³C NMR paramagnetic shifts induced by freely diffusing 4-hydroxy-2, 2, 6, 6-tetramethyl-piperidine-1-oxyl (TEMPOL) are promising, because TEMPOL affects distinct ¹³C NMR chemical shifts of the solvent accessible nuclei belonging to proteins of interest, while ¹³C nuclei within the interior of the proteins may be distinguished by a lack of such shifts.

Method

We measured the ¹³C NMR paramagnetic shifts induced by TEMPOL by recording ¹³C–¹³C TOCSY spectra for ubiquitin in the free state and the complex state with yeast ubiquitin hydrolase1 (YUH1).

Results

Upon complexation of ubiquitin with YUH1, ¹³C NMR paramagnetic shifts associated with the protein binding interface were reduced by 0.05 ppm or more. The identified interfacial atoms agreed with the prior X-ray crystallographic data.

Conclusions

The TEMPOL-induced ¹³C chemical shift perturbation is useful to determine precise protein–protein interfaces.

General significance

The present method is a useful method to determine protein–protein interface by NMR, because it has advantages in easy sample preparations, simple data analyses, and wide applicabilities.     

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.     

Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

We introduce a Python-based program that utilizes the large database of ¹³C and ¹⁵N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D ¹³C–¹³C, ¹⁵N–¹³C, or 3D ¹⁵N–¹³C–¹³C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D ¹³C–¹³C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40–60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO–Cα–Cβ or N–Cα–Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.     

Backbone structure confirmation and side chain conformation refinement of a bradykinin mimic BKM-824 by comparing calculated (1)H, (13)C and (19)F chemical shifts with experiment

Calculated and experimental (1)H, (13)C and (19)F chemical shifts were compared in BKM-824, a cyclic bradykinin antagonist mimic, c[Ava(1)-Igl(2)-Ser(3)-DF5F(4)-Oic(5)-Arg(6)] (Ava=5-aminovaleric acid, Igl=alpha-(2-indanyl)glycine, DF5F=pentafluorophenylalanine, Oic=(2S,3aS,7aS)-octahydroindole-2-carboxylic acid). The conformation of BKM-824 has been studied earlier by NMR spectroscopy (M. Miskolzie et al., J. Biomolec. Struct. Dyn. 17, 947-955 (2000)). All NMR structures have qualitatively the same backbone structure but there is considerable variation in the side chain conformations. We have carried out quantum mechanical optimization for three representative NMR structures at the B3LYP/6-31G* level, constraining the backbone dihedral angles at their NMR structure values, followed by NMR chemical shift calculations at the optimized structures with the 6-311G** basis set. There is an intramolecular hydrogen bond at Ser(3) in the optimized structures. The experimental (13)C chemical shifts at five C(alpha) positions as well as at the Cbeta, Cgamma and Cdelta position of Ava(1), which forms part of the backbone, are well reproduced by the calculations, confirming the NMR backbone structure. A comparison between the calculated and experimental H(beta) chemical shifts in Igl(2) shows that the dominant conformation at this residue is gauche. Changes of proton chemical shifts with the scan of the chi(1) angle in DF5F(4) suggest that chi(1)180 degrees. The calculated (1)H and (13)C chemical shifts are in good agreement with experiment at the rigid residue Oic(5). None of the models gives accurate results for Arg(6), presumably because of its positive charge. Our study indicates that calculated NMR shifts can be used as additional constraints in conjunction with NMR data to determine protein conformations. However, to be computationally effective, a database of chemical shifts in small peptide fragments should be precalculated.