Accurate prediction of protein torsion angles using chemical shifts and sequence homology

Peptide bond conformation in peptides and proteins probed by dipolar coupling-chemical shift tensor correlation solid-state NMR

Multidimensional magic-angle spinning solid-state NMR experiments are described that permit cis and trans peptide bonds in uniformly 13C,15N-labeled peptides and proteins to be unambiguously distinguished in residue-specific manner by determining the relative orientations of the amide 13C' CSA and 1H-15N dipolar coupling tensors. The experiments are demonstrated for model peptides glycylglycine and 2,5-diketopiperazine containing trans and cis peptide bonds, respectively. Subsequently, the measurements are extended to two representative proteins that contain exclusively trans peptide bonds, microcrystalline B3 immunoglobulin domain of protein G and Y145Stop human prion protein amyloid fibrils, to illustrate their applicability to a wide range of protein systems.

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.

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.

Application of data mining tools for classification of protein structural class from residue based averaged NMR chemical shifts

The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for protein structural information that is directly related to function. Nuclear magnetic resonance (NMR) provides powerful means to determine three-dimensional structures of proteins in the solution state. However, translation of the NMR spectral parameters to even low-resolution structural information such as protein class requires multiple time consuming steps. In this paper, we present an unorthodox method to predict the protein structural class directly by using the residue's averaged chemical shifts (ACS) based on machine learning algorithms. Experimental chemical shift information from 1491 proteins obtained from Biological Magnetic Resonance Bank (BMRB) and their respective protein structural classes derived from structural classification of proteins (SCOP) were used to construct a data set with 119 attributes and 5 different classes. Twenty four different classification schemes were evaluated using several performance measures. Overall the residue based ACS values can predict the protein structural classes with 80% accuracy measured by Matthew correlation coefficient. Specifically protein classes defined by mixed αβ or small proteins are classified with >90% correlation. Our results indicate that this NMR-based method can be utilized as a low-resolution tool for protein structural class identification without any prior chemical shift assignments.

Deuterium isotope shifts for backbone ¹H, ¹⁵N and ¹³C nuclei in intrinsically disordered protein α-synuclein

Intrinsically disordered proteins (IDPs) are abundant in nature and characterization of their potential structural propensities remains a widely pursued but challenging task. Analysis of NMR secondary chemical shifts plays an important role in such studies, but the output of such analyses depends on the accuracy of reference random coil chemical shifts. Although uniform perdeuteration of IDPs can dramatically increase spectral resolution, a feature particularly important for the poorly dispersed IDP spectra, the impact of deuterium isotope shifts on random coil values has not yet been fully characterized. Very precise (2)H isotope shift measurements for (13)C(α), (13)C(β), (13)C', (15)N, and (1)H(N) have been obtained by using a mixed sample of protonated and uniformly perdeuterated α-synuclein, a protein with chemical shifts exceptionally close to random coil values. Decomposition of these isotope shifts into one-bond, two-bond and three-bond effects as well as intra- and sequential residue contributions shows that such an analysis, which ignores conformational dependence, is meaningful but does not fully describe the total isotope shift to within the precision of the measurements. Random coil (2)H isotope shifts provide an important starting point for analysis of such shifts in structural terms in folded proteins, where they are known to depend strongly on local geometry.

Solid-state NMR applied to photosynthetic light-harvesting complexes

This short review describes how solid-state NMR has provided a mechanistic and electronic picture of pigment-protein and pigment-pigment interactions in photosynthetic antenna complexes. NMR results on purple bacterial antenna complexes show how the packing of the protein and the pigments inside the light-harvesting oligomers induces mutual conformational stress. The protein scaffold produces deformation and electrostatic polarization of the BChl macrocycles and leads to a partial electronic charge transfer between the BChls and their coordinating histidines, which can tune the light-harvesting function. In chlorosome antennae assemblies, the NMR template structure reveals how the chromophores can direct their self-assembly into higher macrostructures which, in turn, tune the light-harvesting properties of the individual molecules by controlling their disorder, structural deformation, and electronic polarization without the need for a protein scaffold. These results pave the way for addressing the next challenge, which is to resolve the functional conformational dynamics of the lhc antennae of oxygenic species that allows them to switch between light-emitting and light-energy dissipating states.

J-coupling constants for a trialanine peptide as a function of dihedral angles calculated by density functional theory over the full Ramachandran space

We present 13 (3)J, seven (2)J and four (1)J coupling constants (24 in all) calculated using B3LYP/D95** as a function of the φ and ψ Ramachandran dihedral angles of the acetyl(Ala)(3)NH(2) capped trialanine peptide over the entire Ramachandran space. With the exception of three of these J couplings, all show significant dependence upon both dihedral angles. For each J coupling considered, a two dimensional grid with respect to φ and ψ angles can be used to interpolate the values for any pair of φ and ψ values. Such simple interpolation is shown to be very accurate. Most of these calculated J couplings should prove useful for improving the accuracy of the determination of peptide and protein structures from NMR measurements in solution over that provided by the common procedure of treating the J couplings as functions of a single dihedral angle by means of Karplus-type fittings.

Validation of archived chemical shifts through atomic coordinates

The public archives containing protein information in the form of NMR chemical shift data at the BioMagResBank (BMRB) and of 3D structure coordinates at the Protein Data Bank are continuously expanding. The quality of the data contained in these archives, however, varies. The main issue for chemical shift values is that they are determined relative to a reference frequency. When this reference frequency is set incorrectly, all related chemical shift values are systematically offset. Such wrongly referenced chemical shift values, as well as other problems such as chemical shift values that are assigned to the wrong atom, are not easily distinguished from correct values and effectively reduce the usefulness of the archive. We describe a new method to correct and validate protein chemical shift values in relation to their 3D structure coordinates. This method classifies atoms using two parameters: the per-atom solvent accessible surface area (as calculated from the coordinates) and the secondary structure of the parent amino acid. Through the use of Gaussian statistics based on a large database of 3220 BMRB entries, we obtain per-entry chemical shift corrections as well as Z scores for the individual chemical shift values. In addition, information on the error of the correction value itself is available, and the method can retain only dependable correction values. We provide an online resource with chemical shift, atom exposure, and secondary structure information for all relevant BMRB entries (http://www.ebi.ac.uk/pdbe/nmr/vasco) and hope this data will aid the development of new chemical shift-based methods in NMR. Proteins 2010. © 2010 Wiley-Liss, Inc.

DANGLE: A Bayesian inferential method for predicting protein backbone dihedral angles and secondary structure

This paper introduces DANGLE, a new algorithm that employs Bayesian inference to estimate the likelihood of all possible values of the backbone dihedral angles phi and psi for each residue in a query protein, based on observed chemical shifts and the conformational preferences of each amino acid type. The method provides robust estimates of phi and psi within realistic boundary ranges, an indication of the degeneracy in the relationship between shift measurements and conformation at each site, and faithful secondary structure state assignments. When a simple degeneracy-based filtering procedure is applied, DANGLE offers an ideal compromise between accuracy and coverage when compared with other shift-based dihedral angle prediction methods. In addition, per residue analysis of shift/structure degeneracy has potential to be a useful new approach for studying the properties of unfolded proteins, with sufficient sensitivity to identify regions of residual structure in the acid denatured state of apomyoglobin.

Calmodulin wraps around its binding domain in the plasma membrane Ca2+ pump anchored by a novel 18-1 motif

Using solution NMR spectroscopy, we obtained the structure of Ca(2+)-calmodulin (holoCaM) in complex with peptide C28 from the binding domain of the plasma membrane Ca(2+)-ATPase (PMCA) pump isoform 4b. This provides the first atomic resolution insight into the binding mode of holoCaM to the full-length binding domain of PMCA. Structural comparison of the previously determined holoCaM.C20 complex with this holoCaM.C28 complex supports the idea that the initial binding step is represented by (holoCaM.C20) and the final bound complex by (holoCaM.C28). This affirms the existing multi-step kinetic model of PMCA4b activation by CaM. The complex exhibits a new binding motif in which holoCaM is wrapped around helical C28 peptide using two anchoring residues from the peptide at relative positions 18 and 1. The anchors correspond to Phe-1110 and Trp-1093, respectively, in full-length PMCA4b, and the peptide and CaM are oriented in an anti-parallel manner. This is a greater sequence distance between anchors than in any of the known holoCaM complexes with a helical peptide. Analysis of the geometry of holoCaM-peptide binding for the cases where the target peptide adopts an alpha(D)-helix with its anchors buried in the main hydrophobic pockets of the two CaM lobes establishes that only relative sequential positions of 10, 14, 17, and 18 are allowed for the second anchor.

TALOS+: a hybrid method for predicting protein backbone torsion angles from NMR chemical shifts

NMR chemical shifts in proteins depend strongly on local structure. The program TALOS establishes an empirical relation between 13C, 15N and 1H chemical shifts and backbone torsion angles phi and psi (Cornilescu et al. J Biomol NMR 13 289-302, 1999). Extension of the original 20-protein database to 200 proteins increased the fraction of residues for which backbone angles could be predicted from 65 to 74%, while reducing the error rate from 3 to 2.5%. Addition of a two-layer neural network filter to the database fragment selection process forms the basis for a new program, TALOS+, which further enhances the prediction rate to 88.5%, without increasing the error rate. Excluding the 2.5% of residues for which TALOS+ makes predictions that strongly differ from those observed in the crystalline state, the accuracy of predicted phi and psi angles, equals +/-13 degrees . Large discrepancies between predictions and crystal structures are primarily limited to loop regions, and for the few cases where multiple X-ray structures are available such residues are often found in different states in the different structures. The TALOS+ output includes predictions for individual residues with missing chemical shifts, and the neural network component of the program also predicts secondary structure with good accuracy.

CheckShift improved: fast chemical shift reference correction with high accuracy

The construction of a consistent protein chemical shift database is an important step toward making more extensive use of this data in structural studies. Unfortunately, progress in this direction has been hampered by the quality of the available data, particularly with respect to chemical shift referencing, which is often either inaccurate or inconsistently annotated. Preprocessing of the data is therefore required to detect and correct referencing errors. In an earlier study we developed CheckShift, a program for performing this task automatically. Now we spent substantial effort in improving the running time of the CheckShift algorithm, which resulted in an running time decrease of 90%, thereby achieving equivalent quality to the former version of CheckShift. The reason for the running time decrease is twofold. Firstly we improved the search for the optimal re-referencing offset considerably. Secondly, as CheckShift is based on a secondary structure prediction from the amino acid sequence (formally PsiPred was used), we evaluated a wide range of available secondary structure prediction programs focusing on the special needs of the CheckShift algorithm. The results of this evaluation prove empirically that we can use faster secondary structure prediction programs than PsiPred without sacrificing CheckShift's accuracy. Very recently Wang and Markley (2009) gave a small list of extreme outliers of the former version of the CheckShift web-server. Those were due to the empirical reduction of the search space implemented in the old version. The new version of CheckShift now gives very similar results to RefDB and LACS for all outliers mentioned in Table 1 of Wang and Markley (2009).

Relationship between chemical shift value and accessible surface area for all amino acid atoms

BACKGROUND

Chemical shifts obtained from NMR experiments are an important tool in determining secondary, even tertiary, protein structure. The main repository for chemical shift data is the BioMagResBank, which provides NMR-STAR files with this type of information. However, it is not trivial to link this information to available coordinate data from the PDB for non-backbone atoms due to atom and chain naming differences, as well as sequence numbering changes.

RESULTS

We here describe the analysis of a consistent set of chemical shift and coordinate data, in which we focus on the relationship between the per-atom solvent accessible surface area (ASA) in the reported coordinates and their reported chemical shift value. The data is available online on http://www.ebi.ac.uk/pdbe/docs/NMR/shiftAnalysis/index.html.

CONCLUSION

Atoms with zero per-atom ASA have a significantly larger chemical shift dispersion and often have a different chemical shift distribution compared to those that are solvent accessible. With higher per-atom ASA, the chemical shift values also tend towards random coil values. The per-atom ASA, although not the determinant of the chemical shift, thus provides a way to directly correlate chemical shift information to the atomic coordinates.

SimShiftDB; local conformational restraints derived from chemical shift similarity searches on a large synthetic database

We present SimShiftDB, a new program to extract conformational data from protein chemical shifts using structural alignments. The alignments are obtained in searches of a large database containing 13,000 structures and corresponding back-calculated chemical shifts. SimShiftDB makes use of chemical shift data to provide accurate results even in the case of low sequence similarity, and with even coverage of the conformational search space. We compare SimShiftDB to HHSearch, a state-of-the-art sequence-based search tool, and to TALOS, the current standard tool for the task. We show that for a significant fraction of the predicted similarities, SimShiftDB outperforms the other two methods. Particularly, the high coverage afforded by the larger database often allows predictions to be made for residues not involved in canonical secondary structure, where TALOS predictions are both less frequent and more error prone. Thus SimShiftDB can be seen as a complement to currently available methods.

Discriminative learning for protein conformation sampling

Protein structure prediction without using templates (i.e., ab initio folding) is one of the most challenging problems in structural biology. In particular, conformation sampling poses as a major bottleneck of ab initio folding. This article presents CRFSampler, an extensible protein conformation sampler, built on a probabilistic graphical model Conditional Random Fields (CRFs). Using a discriminative learning method, CRFSampler can automatically learn more than ten thousand parameters quantifying the relationship among primary sequence, secondary structure, and (pseudo) backbone angles. Using only compactness and self-avoiding constraints, CRFSampler can efficiently generate protein-like conformations from primary sequence and predicted secondary structure. CRFSampler is also very flexible in that a variety of model topologies and feature sets can be defined to model the sequence-structure relationship without worrying about parameter estimation. Our experimental results demonstrate that using a simple set of features, CRFSampler can generate decoys with much higher quality than the most recent HMM model.

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.

ANGLOR: a composite machine-learning algorithm for protein backbone torsion angle prediction

We developed a composite machine-learning based algorithm, called ANGLOR, to predict real-value protein backbone torsion angles from amino acid sequences. The input features of ANGLOR include sequence profiles, predicted secondary structure and solvent accessibility. In a large-scale benchmarking test, the mean absolute error (MAE) of the phi/psi prediction is 28°/46°, which is ∼10% lower than that generated by software in literature. The prediction is statistically different from a random predictor (or a purely secondary-structure-based predictor) with p-value <1.0×10⁻³⁰⁰ (or <1.0×10⁻¹⁴⁸) by Wilcoxon signed rank test. For some residues (ILE, LEU, PRO and VAL) and especially the residues in helix and buried regions, the MAE of phi angles is much smaller (10–20°) than that in other environments. Thus, although the average accuracy of the ANGLOR prediction is still low, the portion of the accurately predicted dihedral angles may be useful in assisting protein fold recognition and ab initio 3D structure modeling.

Structure of the human voltage-dependent anion channel

The voltage-dependent anion channel (VDAC), also known as mitochondrial porin, is the most abundant protein in the mitochondrial outer membrane (MOM). VDAC is the channel known to guide the metabolic flux across the MOM and plays a key role in mitochondrially induced apoptosis. Here, we present the 3D structure of human VDAC1, which was solved conjointly by NMR spectroscopy and x-ray crystallography. Human VDAC1 (hVDAC1) adopts a beta-barrel architecture composed of 19 beta-strands with an alpha-helix located horizontally midway within the pore. Bioinformatic analysis indicates that this channel architecture is common to all VDAC proteins and is adopted by the general import pore TOM40 of mammals, which is also located in the MOM.

Dependence of amino acid side chain 13C shifts on dihedral angle: application to conformational analysis

Chemical shift data from the BiomagResDataBank and conformational data derived from the protein data bank have been correlated in order to explore the conformational dependence of side chain (13)C resonance shifts. Consistent with predictions based on steric compression, upfield shifts for Cgamma resonances of Thr, Val, Ile, Leu, Met, Arg, Lys, Glu, and Gln residues correlate with both the number of heavy atom (nonproton) gamma-substituents and with gauche conformational orientations of gamma-substituents. The (13)C shift/conformation correlations are most apparent for Cgamma carbons but also can be observed at positions further from the backbone. Intraresidue steric conflict leads to a correlation between upfield-shifted side chain (13)C resonances and statistically lower probabilities in surveys of protein side chain conformation. Illustrative applications to the DNA pol lambda lyase domain and to dihydrofolate reductase are discussed. In the latter case, (13)C shift analysis indicates that the conformation of the remote residue V119 on the betaF-betaG loop is correlated with the redox state of the bound pyridine nucleotide cofactor, providing one basis for discrimination between substrate and product. It is anticipated that (13)C shift data for protein sidechains can provide a useful basis for the analysis of conformational changes even in large, deuterated proteins. Additionally, the large dependence of the leucine methyl shift difference, deltaCdelta1-deltaCdelta2, on both chi1 and chi2 is sufficient to allow this parameter to be used as a restraint in structure calculations if stereospecific assignment data are available.

Isotropic chemical shifts in magic-angle spinning NMR spectra of proteins

Here we examine the effect of magic-angle spinning (MAS) rate upon lineshape and observed peak position for backbone carbonyl (C') peaks in NMR spectra of uniformly-(13)C,15N-labeled (U-(13)C,15N) solid proteins. 2D N-C' spectra of U-(13)C,15N microcrystalline protein GB1 were acquired at six MAS rates, and the site-resolved C' lineshapes were analyzed by numerical simulations and comparison to spectra from a sparsely labeled sample (derived from 1,3-(13)C-glycerol). Spectra of the U-(13)C,15N sample demonstrate large variations in the signal-to-noise ratio and peak positions, which are absent in spectra of the sparsely labeled sample, in which most 13C' sites do not possess a directly bonded 13CA. These effects therefore are a consequence of rotational resonance, which is a well-known phenomenon. Yet the magnitude of this effect pertaining to chemical shift assignment has not previously been examined. To quantify these effects in high-resolution protein spectra, we performed exact numerical two- and four-spin simulations of the C' lineshapes, which reproduced the experimentally observed features. Observed peak positions differ from the isotropic shift by up to 1.0 ppm, even for MAS rates relatively far (a few ppm) from rotational resonance. Although under these circumstances the correct isotropic chemical shift values may be determined through simulation, systematic errors are minimized when the MAS rate is equivalent to approximately 85 ppm for 13C. This moderate MAS condition simplifies spectral assignment and enables data sets from different labeling patterns and spinning rates to be used most efficiently for structure determination.

CheckShift: automatic correction of inconsistent chemical shift referencing

The construction of a consistent protein chemical shift database is an important step toward making more extensive use of this data in structural studies. Unfortunately, progress in this direction has been hampered by the quality of the available data, particularly with respect to chemical shift referencing, which is often either inaccurate or inconsistently annotated. Preprocessing of the data is therefore required to detect and correct referencing errors. We have developed a program for performing this task, based on the comparison of reported and expected chemical shift distributions. This program, named CheckShift, does not require additional data and is therefore applicable to data sets where structures are not available. Therefore CheckShift provides the possibility to re-reference chemical shifts prior to their use as structural constraints.

Spectral fitting for signal assignment and structural analysis of uniformly 13C-labeled solid proteins by simulated annealing based on chemical shifts and spin dynamics

We describe an approach for the signal assignment and structural analysis with a suite of two-dimensional (13)C-(13)C magic-angle-spinning solid-state NMR spectra of uniformly (13)C-labeled peptides and proteins. We directly fit the calculated spectra to experimental ones by simulated annealing in restrained molecular dynamics program CNS as a function of atomic coordinates. The spectra are calculated from the conformation dependent chemical shift obtained with SHIFTX and the cross-peak intensities computed for recoupled dipolar interactions. This method was applied to a membrane-bound 14-residue peptide, mastoparan-X. The obtained C', C(alpha) and C(beta) chemical shifts agreed with those reported previously at the precisions of 0.2, 0.7 and 0.4 ppm, respectively. This spectral fitting program also provides backbone dihedral angles with a precision of about 50 degrees from the spectra even with resonance overlaps. The restraints on the angles were improved by applying protein database program TALOS to the obtained chemical shifts. The peptide structure provided by these restraints was consistent with the reported structure at the backbone RMSD of about 1 A.

Solution structure of the coxsackievirus and adenovirus receptor domain 2

The coxsackievirus and adenovirus receptor (CAR) mediates entry of coxsackievirus and adenovirus. CAR possesses an extracellular region that is comprised of 2 immunoglobulin domains termed CAR-D1 and CAR-D2. In the present work, the solution structure of CAR-D2, consisting of residues 142-235 of human CAR, has been determined by NMR spectroscopy. CAR-D2 is shown to be a beta-sandwich motif comprised of two beta-sheets, which are stabilized by two disulfide bonds. The first beta-sheet is comprised of beta-strands A, B, and E, and the second beta-sheet is comprised of beta-strands C, F, and G. A relatively hydrophobic helix is found between beta-strands C and E, which replaces beta-strand D of the classical c-type immunoglobulin fold.

Filamentous Phage Studied by Magic-Angle Spinning NMR: Resonance Assignment and Secondary Structure of the Coat Protein in Pf1

Assignments are presented for resonances in the magic-angle spinning solid-state NMR spectra of the major coat protein subunit of the filamentous bacteriophage Pf1. NMR spectra were collected on uniformly 13C and 15N isotopically enriched, polyethylene glycol precipitated samples of fully infectious and hydrated phage. Site-specific assignments were achieved for 231 of the 251 labeled atoms (92%) of the 46-residue-long coat protein, including 136 of the 138 backbone atoms, by means of two- and three-dimensional 15N and 13C correlation experiments. A single chemical shift was observed for the vast majority of atoms, suggesting a single conformation for the 7300 subunits in the 36 MDa virion in its high-temperature form. On the other hand, multiple chemical shifts were observed for the Calpha, Cbeta, and Cgamma atoms of T5 in the helix terminus and the Calpha and Cbeta atoms of M42 in the DNA interaction domain. The chemical shifts of the backbone atoms indicate that the coat protein conformation involves a 40-residue continuous alpha-helix extending from residue 6 to the C-terminus.

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° 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: .