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 .

Unraveling the meaning of chemical shifts in protein NMR.

Chemical shifts are among the most informative parameters in protein NMR. They provide wealth of information about protein secondary and tertiary structure, protein flexibility, and protein-ligand binding. In this report, we review the progress in interpreting and utilizing protein chemical shifts that has occurred over the past 25years, with a particular focus on the large body of work arising from our group and other Canadian NMR laboratories. More specifically, this review focuses on describing, assessing, and providing some historical context for various chemical shift-based methods to: (1) determine protein secondary and super-secondary structure; (2) derive protein torsion angles; (3) assess protein flexibility; (4) predict residue accessible surface area; (5) refine 3D protein structures; (6) determine 3D protein structures and (7) characterize intrinsically disordered proteins. This review also briefly covers some of the methods that we previously developed to predict chemical shifts from 3D protein structures and/or protein sequence data. It is hoped that this review will help to increase awareness of the considerable utility of NMR chemical shifts in structural biology and facilitate more widespread adoption of chemical-shift based methods by the NMR spectroscopists, structural biologists, protein biophysicists, and biochemists worldwide. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

A simple method to measure protein side-chain mobility using NMR chemical shifts.

Protein side-chain motions are involved in many important biological processes including enzymatic catalysis, allosteric regulation, and the mediation of protein-protein, protein-DNA, protein-RNA, and protein-cofactor interactions. NMR spectroscopy has long been used to provide insights into the motions of side-chain groups. Currently, the method of choice for studying side-chain dynamics by NMR is the measurement of methyl (2)H autorelaxation. Methyl (2)H autorelaxation exhibits simple relaxation mechanisms and can be straightforwardly converted to meaningful dynamic parameters. However, methyl groups can only be found in 6 of 19 side-chain bearing amino acids. Consequently, only a sparse assessment of protein side-chain dynamics is possible. Therefore, there is a significant interest in developing novel methods of studying side-chain motions that can be applied to all types of side-chains. Here, we show how side-chain chemical shifts can be used to determine the magnitude of fast side-chain motions in proteins. The chemical shift method is applicable to all side-chain bearing residues and does not require any additional measurements beyond standard NMR experiments for backbone and side-chain assignments.

Solution NMR of a 463-residue phosphohexomutase: domain 4 mobility, substates, and phosphoryl transfer defect.

Phosphomannomutase/phosphoglucomutase contributes to the infectivity of Pseudomonas aeruginosa, retains and reorients its intermediate by 180°, and rotates domain 4 to close the deep catalytic cleft. Nuclear magnetic resonance (NMR) spectra of the backbone of wild-type and S108C-inactivated enzymes were assigned to at least 90%. (13)C secondary chemical shifts report excellent agreement of solution and crystallographic structure over the 14 α-helices, C-capping motifs, and 20 of the 22 ß-strands. Major and minor NMR peaks implicate substates affecting 28% of assigned residues. These can be attributed to the phosphorylation state and possibly to conformational interconversions. The S108C substitution of the phosphoryl donor and acceptor slowed transformation of the glucose 1-phosphate substrate by impairing k(cat). Addition of the glucose 1,6-bisphosphate intermediate accelerated this reaction by 2-3 orders of magnitude, somewhat bypassing the defect and apparently relieving substrate inhibition. The S108C mutation perturbs the NMR spectra and electron density map around the catalytic cleft while preserving the secondary structure in solution. Diminished peak heights and faster (15)N relaxation suggest line broadening and millisecond fluctuations within four loops that can contact phosphosugars. (15)N NMR relaxation and peak heights suggest that domain 4 reorients slightly faster in solution than domains 1-3, and with a different principal axis of diffusion. This adds to the crystallographic evidence of domain 4 rotations in the enzyme, which were previously suggested to couple to reorientation of the intermediate, substrate binding, and product release.

Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls.

Residual feed intake (RFI) is a feed efficiency measure commonly used in the livestock industry to identify animals that efficiently/inefficiently convert feed into meat or body mass. Selection for low-residual feed intake (LRFI), or feed efficient animals, is gaining popularity among beef producers due to the fact that LRFI cattle eat less and produce less methane per unit weight gain. RFI is a difficult and time-consuming measure to perform, and therefore a simple blood test that could distinguish high-RFI (HRFI) from LRFI animals (early on) would potentially benefit beef farmers in terms of optimizing production or selecting which animals to cull or breed. Using three different metabolomics platforms (nuclear magnetic resonance (NMR) spectrometry, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and inductively coupled plasma mass spectrometry (ICP-MS)) we successfully identified serum biomarkers for RFI that could potentially be translated to an RFI blood test. One set of predictive RFI biomarkers included formate and leucine (best for NMR), and another set included C4 (butyrylcarnitine) and LysoPC(28:0) (best for LC-MS/MS). These serum biomarkers have high sensitivity and specificity (AUROC > 0.85), for distinguishing HRFI from LRFI animals. These results suggest that serum metabolites could be used to inexpensively predict and categorize bovine RFI values. Further validation using a larger, more diverse cohort of cattle is required to confirm these findings.

The RCI server: rapid and accurate calculation of protein flexibility using chemical shifts.

Protein motions play important roles in numerous biological processes such as enzyme catalysis, muscle contractions, antigen-antibody interactions, gene regulation and virus assembly. Knowledge of protein flexibility is also important in rational drug design, protein docking and protein engineering. However, the experimental measurement of protein motions is often difficult, requiring sophisticated experiments, complex data analysis and detailed information about the protein's tertiary structure. As a result, there is a considerable interest in developing simpler, more effective ways of quantifying protein flexibility. Recently, we described a method, called the random coil index (RCI), which is able to quantitatively estimate backbone root mean square fluctuations (RMSFs) of structural ensembles and order parameters using only chemical shifts. The RCI method is very fast (<5 s) and exceedingly robust. It also offers an excellent alternative to traditional methods of measuring protein flexibility. We have recently extended the RCI concept and implemented it as a web server. This server allows facile, accurate and fully automated predictions of MD RMSF values, NMR RMSF values and model-free order parameters (S2) directly from chemical shift assignments. It also performs automatic chemical shift re-referencing to ensure consistency and reproducibility. On average, the correlation between RCI predictions and experimentally obtained motional amplitudes is within the range from 0.77 to 0.82. The server is available at http://wishart.biology.ualberta.ca/rci.

PREDITOR: a web server for predicting protein torsion angle restraints.

Every year between 500 and 1000 peptide and protein structures are determined by NMR and deposited into the Protein Data Bank. However, the process of NMR structure determination continues to be a manually intensive and time-consuming task. One of the most tedious and error-prone aspects of this process involves the determination of torsion angle restraints including phi, psi, omega and chi angles. Most methods require many days of additional experiments, painstaking measurements or complex calculations. Here we wish to describe a web server, called PREDITOR, which greatly accelerates and simplifies this task. PREDITOR accepts sequence and/or chemical shift data as input and generates torsion angle predictions (with predicted errors) for phi, psi, omega and chi-1 angles. PREDITOR combines sequence alignment methods with advanced chemical shift analysis techniques to generate its torsion angle predictions. The method is fast (<40 s per protein) and accurate, with 88% of phi/psi predictions being within 30 degrees of the correct values, 84% of chi-1 predictions being correct and 99.97% of omega angles being correct. PREDITOR is 35 times faster and up to 20% more accurate than any existing method. PREDITOR also provides accurate assessments of the torsion angle errors so that the torsion angle constraints can be readily fed into standard structure refinement programs, such as CNS, XPLOR, AMBER and CYANA. Other unique features to PREDITOR include dihedral angle prediction via PDB structure mapping, automated chemical shift re-referencing (to improve accuracy), prediction of proline cis/trans states and a simple user interface. The PREDITOR website is located at: http://wishart.biology.ualberta.ca/preditor.

The prion protein binds thiamine.

Although highly conserved throughout evolution, the exact biological function of the prion protein is still unclear. In an effort to identify the potential biological functions of the prion protein we conducted a small-molecule screening assay using the Syrian hamster prion protein [shPrP(90-232)]. The screen was performed using a library of 149 water-soluble metabolites that are known to pass through the blood-brain barrier. Using a combination of 1D NMR, fluorescence quenching and surface plasmon resonance we identified thiamine (vitamin B1) as a specific prion ligand with a binding constant of ~60 µM. Subsequent studies showed that this interaction is evolutionarily conserved, with similar binding constants being seen for mouse, hamster and human prions. Various protein construct lengths, both with and without the unstructured N-terminal region in the presence and absence of copper, were examined. This indicates that the N-terminus has no influence on the protein's ability to interact with thiamine. In addition to thiamine, the more biologically abundant forms of vitamin B1 (thiamine monophosphate and thiamine diphosphate) were also found to bind the prion protein with similar affinity. Heteronuclear NMR experiments were used to determine thiamine's interaction site, which is located between helix 1 and the preceding loop. These data, in conjunction with computer-aided docking and molecular dynamics, were used to model the thiamine-binding pharmacophore and a comparison with other thiamine binding proteins was performed to reveal the common features of interaction.

Application of the random coil index to studying protein flexibility.

Protein flexibility lies at the heart of many protein-ligand binding events and enzymatic activities. However, the experimental measurement of protein motions is often difficult, tedious and error-prone. As a result, there is a considerable interest in developing simpler and faster ways of quantifying protein flexibility. Recently, we described a method, called Random Coil Index (RCI), which appears to be able to quantitatively estimate model-free order parameters and flexibility in protein structural ensembles using only backbone chemical shifts. Because of its potential utility, we have undertaken a more detailed investigation of the RCI method in an attempt to ascertain its underlying principles, its general utility, its sensitivity to chemical shift errors, its sensitivity to data completeness, its applicability to other proteins, and its general strengths and weaknesses. Overall, we find that the RCI method is very robust and that it represents a useful addition to traditional methods of studying protein flexibility. We have implemented many of the findings and refinements reported here into a web server that allows facile, automated predictions of model-free order parameters, MD RMSF and NMR RMSD values directly from backbone 1H, 13C and 15N chemical shift assignments. The server is available at http://wishart.biology.ualberta.ca/rci.

A simple method to predict protein flexibility using secondary chemical shifts.

Protein motions play a critical role in many biological processes, such as enzyme catalysis, allosteric regulation, antigen-antibody interactions, and protein-DNA binding. NMR spectroscopy occupies a unique place among methods for investigating protein dynamics due to its ability to provide site-specific information about protein motions over a large range of time scales. However, most NMR methods require a detailed knowledge of the 3D structure and/or the collection of additional experimental data (NOEs, T1, T2, etc.) to accurately measure protein dynamics. Here we present a simple method based on chemical shift data that allows accurate, quantitative, site-specific mapping of protein backbone mobility without the need of a three-dimensional structure or the collection and analysis of NMR relaxation data. Further, we show that this chemical shift method is able to quantitatively predict per-residue RMSD values (from both MD simulations and NMR structural ensembles) as well as model-free backbone order parameters.