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.     

Accurate ab initio prediction of NMR chemical shifts of nucleic acids and nucleic acids/protein complexes

NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r²) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization.     

Exploring the conformational space of amorphous cellulose using NMR chemical shifts

(13)C-labeled amorphous cellulose and (13)C NMR chemical shifts by 2D (13)C-(13)C correlation spectroscopy were obtained in the regenerated solid-state from ionic liquids. On the basis of the assigned chemical shifts, combined with information from molecular dynamics and quantum chemistry computer simulations a twisted structure for amorphous cellulose is proposed exposing more hydrophilic surface than that of extended crystalline cellulose.     

The application of 1H NMR chemical shift calculations to diastereotopic groups in proteins.

We have calculated chemical shifts for a range of diastereotopic protons in proteins (i.e. methylene protons, and the methyl groups of valine and leucine residues), using a recently optimised method for chemical shift calculation. The calculations are based on crystal structure coordinates, and have been compared with experimental stereospecific assignments. The results indicate that chemical shifts can be used to suggest stereospecific assignments with about 80% probability of being correct, in cases where both the experimental and the calculated chemical shift differences between a pair of diastereotopic protons are greater than 0.3 ppm. Inaccurate calculations are shown to be caused in most cases by differences between crystal and solution structures. Furthermore, chemical shift calculations based on NMR structures are shown to be capable of acting as a further constraint on structure, by limiting the range of side-chain conformations adopted in structures calculated from NMR data.     

De novo protein structure generation from incomplete chemical shift assignments

NMR chemical shifts provide important local structural information for proteins. Consistent structure generation from NMR chemical shift data has recently become feasible for proteins with sizes of up to 130 residues, and such structures are of a quality comparable to those obtained with the standard NMR protocol. This study investigates the influence of the completeness of chemical shift assignments on structures generated from chemical shifts. The Chemical-Shift-Rosetta (CS-Rosetta) protocol was used for de novo protein structure generation with various degrees of completeness of the chemical shift assignment, simulated by omission of entries in the experimental chemical shift data previously used for the initial demonstration of the CS-Rosetta approach. In addition, a new CS-Rosetta protocol is described that improves robustness of the method for proteins with missing or erroneous NMR chemical shift input data. This strategy, which uses traditional Rosetta for pre-filtering of the fragment selection process, is demonstrated for two paramagnetic proteins and also for two proteins with solid-state NMR chemical shift assignments. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A strong 13C chemical shift signature provides the coordination mode of histidines in zinc-binding proteins

Zinc is the second most abundant metal ion incorporated in proteins, and is in many cases a crucial component of protein three-dimensional structures. Zinc ions are frequently coordinated by cysteine and histidine residues. Whereas cysteines bind to zinc via their unique S(γ) atom, histidines can coordinate zinc with two different coordination modes, either N(δ1) or N(ε2) is coordinating the zinc ion. The determination of this coordination mode is crucial for the accurate structure determination of a histidine-containing zinc-binding site by NMR. NMR chemical shifts contain a vast amount of information on local electronic and structural environments and surprisingly their utilization for the determination of the coordination mode of zinc-ligated histidines has been limited so far to (15)N nuclei. In the present report, we observed that the (13)C chemical shifts of aromatic carbons in zinc-ligated histidines represent a reliable signature of their coordination mode. Using a statistical analysis of (13)C chemical shifts, we show that (13)C(δ2) chemical shift is sensitive to the histidine coordination mode and that the chemical shift difference δ{(13)C(ε1)} - δ{(13)C(δ2)} provides a reference-independent marker of this coordination mode. The present approach allows the direct determination of the coordination mode of zinc-ligated histidines even with non-isotopically enriched protein samples and without any prior structural information.     

Quantitative use of chemical shifts for the modeling of protein complexes

Despite recent advances in the modeling of protein-protein complexes by docking, additional information is often required to identify the best solutions. For this purpose, NMR data deliver valuable restraints that can be used in the sampling and/or the scoring stage, like in the data-driven docking approach HADDOCK that can make use of NMR chemical shift perturbation (CSP) data to define the binding site on each protein and drive the docking. We show here that a quantitative use of chemical shifts (CS) in the scoring stage can help to resolve ambiguities. A quantitative CS-RMSD score based on (1) H(α) ,(13) C(α) , and (15) N chemical shifts ranks the best solutions always at the top, as demonstrated on a small benchmark of four complexes. It is implemented in a new docking protocol, CS-HADDOCK, which combines CSP data as ambiguous interaction restraints in the sampling stage with the CS-RMSD score in the final scoring stage. This combination of qualitative and quantitative use of chemical shifts increases the reliability of data-driven docking for the structure determination of complexes from limited NMR data.     

Structural determination of complex natural products by quantum mechanical calculations of <Superscript>13</Superscript>C NMR chemical shifts: development of a parameterized protocol for terpenes

Nuclear magnetic resonance (NMR) spectroscopy is one of the most important tools for determining the structures of organic molecules. Despite the advances made in this technique, revisions of erroneously established structures for natural products are still commonly published in the literature. In this context, the prediction of chemical shifts through ab initio and density functional theory (DFT) calculations has become a very powerful tool for assisting with the structural determination of complex organic molecules. In this work, we present the development of a protocol for ¹³C chemical shift calculations of terpenes, a class of natural products that are widely distributed among plant species and are very important due to their biological and pharmacological activities. This protocol consists of GIAO-DFT calculations of chemical shifts and the application of a parameterized scaling factor in order to ensure accurate structural determination of this class of natural products. The application of this protocol to a set of five terpenes yielded accurate calculated chemical shifts, showing that this is a very attractive tool for the calculation of complex organic structures such as terpenes.     

Building native protein conformation from NMR backbone chemical shifts using Monte Carlo fragment assembly

We have been analyzing the extent to which protein secondary structure determines protein tertiary structure in simple protein folds. An earlier paper demonstrated that three-dimensional structure can be obtained successfully using only highly approximate backbone torsion angles for every residue. Here, the initial information is further diluted by introducing a realistic degree of experimental uncertainty into this process. In particular, we tackle the practical problem of determining three-dimensional structure solely from backbone chemical shifts, which can be measured directly by NMR and are known to be correlated with a protein's backbone torsion angles. Extending our previous algorithm to incorporate these experimentally determined data, clusters of structures compatible with the experimentally determined chemical shifts were generated by fragment assembly Monte Carlo. The cluster that corresponds to the native conformation was then identified based on four energy terms: steric clash, solvent-squeezing, hydrogen-bonding, and hydrophobic contact. Currently, the method has been applied successfully to five small proteins with simple topology. Although still under development, this approach offers promise for high-throughput NMR structure determination.     

31P NMR chemical shifts of phosphate covalently bound to proteins

31P nuclear magnetic resonance (NMR) spectroscopy for characterizing the nature of covalently bound phosphate in proteins is relatively unexploited by the biochemist. 31P NMR chemical shifts of phosphate covalently bound to naturally occurring phosphoproteins, phosphorylated enzyme intermediates and chemically phosphorylated proteins have been compiled in this review. The chemical shifts (31P NMR) of selected reference compounds are reported to assist in the assignment of 31P resonances of phosphate covalently attached to proteins. 31P NMR chemical shifts of phosphate and phospho compounds non-covalently bound to selected proteins as well as the pH dependence of 31P NMR resonance have also been compiled.     

RefDB: a database of uniformly referenced protein chemical shifts

RefDB is a secondary database of reference-corrected protein chemical shifts derived from the BioMagResBank (BMRB). The database was assembled by using a recently developed program (SHIFTX) to predict protein ¹H, ¹³C and ¹⁵N chemical shifts from X-ray or NMR coordinate data of previously assigned proteins. The predicted shifts were then compared with the corresponding observed shifts and a variety of statistical evaluations performed. In this way, potential mis-assignments, typographical errors and chemical referencing errors could be identified and, in many cases, corrected. This approach allows for an unbiased, instrument-independent solution to the problem of retrospectively re-referencing published protein chemical shifts. Results from this study indicate that nearly 25% of BMRB entries with ¹³C protein assignments and 27% of BMRB entries with ¹⁵N protein assignments required significant chemical shift reference readjustments. Additionally, nearly 40% of protein entries deposited in the BioMagResBank appear to have at least one assignment error. From this study it evident that protein NMR spectroscopists are increasingly adhering to recommended IUPAC ¹³C and ¹⁵N chemical shift referencing conventions, however, approximately 20% of newly deposited protein entries in the BMRB are still being incorrectly referenced. This is cause for some concern. However, the utilization of RefDB and its companion programs may help mitigate this ongoing problem. RefDB is updated weekly and the database, along with its associated software, is freely available at http://redpoll.pharmacy.ualberta.ca and the BMRB website.     

Influence of the completeness of chemical shift assignments on NMR structures obtained with automated NOE assignment

Reliable automated NOE assignment and structure calculation on the basis of a largely complete, assigned input chemical shift list and a list of unassigned NOESY cross peaks has recently become feasible for routine NMR protein structure calculation and has been shown to yield results that are equivalent to those of the conventional, manual approach. However, these algorithms rely on the availability of a virtually complete list of the chemical shifts. This paper investigates the influence of incomplete chemical shift assignments on the reliability of NMR structures obtained with automated NOESY cross peak assignment. The program CYANA was used for combined automated NOESY assignment with the CANDID algorithm and structure calculations with torsion angle dynamics at various degrees of completeness of the chemical shift assignment which was simulated by random omission of entries in the experimental ¹H chemical shift lists that had been used for the earlier, conventional structure determinations of two proteins. Sets of structure calculations were performed choosing the omitted chemical shifts randomly among all assigned hydrogen atoms, or among aromatic hydrogen atoms. For comparison, automated NOESY assignment and structure calculations were performed with the complete experimental chemical shift but under random omission of NOESY cross peaks. When heteronuclear-resolved three-dimensional NOESY spectra are available the current CANDID algorithm yields in the absence of up to about 10% of the experimental ¹H chemical shifts reliable NOE assignments and three-dimensional structures that deviate by less than 2 Å from the reference structure obtained using all experimental chemical shift assignments. In contrast, the algorithm can accommodate the omission of up to 50% of the cross peaks in heteronuclear- resolved NOESY spectra without producing structures with a RMSD of more than 2 Å to the reference structure. When only homonuclear NOESY spectra are available, the algorithm is slightly more susceptible to missing data and can tolerate the absence of up to about 7% of the experimental ¹H chemical shifts or of up to 30% of the NOESY peaks.Abbreviations: BmPBP^A – Bombyx mori pheromone binding protein form A; CYANA – combined assignment and dynamics algorithm for NMR applications; NMR – nuclear magnetic resonance; NOE – nuclear Overhauser effect; NOESY – NOE spectroscopy; RMSD – root-mean-square deviation; WmKT – Williopsis mrakii killer toxin     

The PROSECCO server for chemical shift predictions in ordered and disordered proteins

The chemical shifts measured in solution-state and solid-state nuclear magnetic resonance (NMR) are powerful probes of the structure and dynamics of protein molecules. The exploitation of chemical shifts requires methods to correlate these data with the protein structures and sequences. We present here an approach to calculate accurate chemical shifts in both ordered and disordered proteins using exclusively the information contained in their sequences. Our sequence-based approach, protein sequences and chemical shift correlations (PROSECCO), achieves the accuracy of the most advanced structure-based methods in the characterization of chemical shifts of folded proteins and improves the state of the art in the study of disordered proteins. Our analyses revealed fundamental insights on the structural information carried by NMR chemical shifts of structured and unstructured protein states.     

Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction

While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein ¹H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6–17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for ¹Hα, ¹HN, ¹³Cα, ¹³Cβ, ¹³CO and backbone ¹⁵N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at .     

Backbone Structure Confirmation and Side Chain Conformation Refinement of a Bradykinin Mimic BKM-824 by Comparing Calculated 1H, 13C and 19F Chemical Shifts with Experiment

Abstract

Calculated and experimental ¹H, ¹³C and ¹⁹F chemical shifts were compared in BKM-824, a cyclic bradykinin antagonist mimic, c[Ava¹-Igl²-Ser³-DF5F⁴-Oic⁵-Arg⁶] (Ava=5-amino- valeric acid, Igl=α-(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 Ser³ in the optimized structures.

The experimental ¹³C chemical shifts at five C^α positions as well as at the C^β, C^γ and Cδ position of Ava¹, 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^β chemical shifts in Igl² shows that the dominant conformation at this residue is gauche. Changes of proton chemical shifts with the scan of the χ1 angle in DF5F⁴ suggest that χ1 ≈180°. The calculated ¹H and ¹³C chemical shifts are in good agreement with experiment at the rigid residue Oic⁵. None of the models gives accurate results for Arg⁶, 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.     

4D prediction of protein <Superscript>1</Superscript>H chemical shifts

A 4D approach for protein ¹H chemical shift prediction was explored. The 4th dimension is the molecular flexibility, mapped using molecular dynamics simulations. The chemical shifts were predicted with a principal component model based on atom coordinates from a database of 40 protein structures. When compared to the corresponding non-dynamic (3D) model, the 4th dimension improved prediction by 6–7%. The prediction method achieved RMS errors of 0.29 and 0.50 ppm for Hα and HN shifts, respectively. However, for individual proteins the RMS errors were 0.17–0.34 and 0.34–0.65 ppm for the Hα and HN shifts, respectively. X-ray structures gave better predictions than the corresponding NMR structures, indicating that chemical shifts contain invaluable information about local structures. The ¹H chemical shift prediction tool 4DSPOT is available from .     

Rapid and reliable protein structure determination via chemical shift threading

Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often?<?10 min/structure) and to significantly outperform other shift-based or threading-based structure determination methods (in terms of top template model accuracy)—with an average TM-score performance of 0.68 (vs. 0.50–0.62 for other methods). Coupled with recent developments in chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca.     

Nucleic acid helix structure determination from NMR proton chemical shifts

We present a method for de novo derivation of the three-dimensional helix structure of nucleic acids using non-exchangeable proton chemical shifts as sole source of experimental restraints. The method is called chemical shift de novo structure derivation protocol employing singular value decomposition (CHEOPS) and uses iterative singular value decomposition to optimize the structure in helix parameter space. The correct performance of CHEOPS and its range of application are established via an extensive set of structure derivations using either simulated or experimental chemical shifts as input. The simulated input data are used to assess in a defined manner the effect of errors or limitations in the input data on the derived structures. We find that the RNA helix parameters can be determined with high accuracy. We finally demonstrate via three deposited RNA structures that experimental proton chemical shifts suffice to derive RNA helix structures with high precision and accuracy. CHEOPS provides, subject to further development, new directions for high-resolution NMR structure determination of nucleic acids.