PCS-based structure determination of protein–protein complexes

A simple and fast nuclear magnetic resonance method for docking proteins using pseudo-contact shift (PCS) and ¹H^N/¹⁵N chemical shift perturbation is presented. PCS is induced by a paramagnetic lanthanide ion that is attached to a target protein using a lanthanide binding peptide tag anchored at two points. PCS provides long-range (~40 Å) distance and angular restraints between the lanthanide ion and the observed nuclei, while the ¹H^N/¹⁵N chemical shift perturbation data provide loose contact-surface information. The usefulness of this method was demonstrated through the structure determination of the p62 PB1-PB1 complex, which forms a front-to-back 20 kDa homo-oligomer. As p62 PB1 does not intrinsically bind metal ions, the lanthanide binding peptide tag was attached to one subunit of the dimer at two anchoring points. Each monomer was treated as a rigid body and was docked based on the backbone PCS and backbone chemical shift perturbation data. Unlike NOE-based structural determination, this method only requires resonance assignments of the backbone ¹H^N/¹⁵N signals and the PCS data obtained from several sets of two-dimensional ¹⁵N-heteronuclear single quantum coherence spectra, thus facilitating rapid structure determination of the protein–protein complex.     

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.     

Capturing Conformational States in Proteins Using Sparse Paramagnetic NMR Data

Capturing conformational changes in proteins or protein-protein complexes is a challenge for both experimentalists and computational biologists. Solution nuclear magnetic resonance (NMR) is unique in that it permits structural studies of proteins under greatly varying conditions, and thus allows us to monitor induced structural changes. Paramagnetic effects are increasingly used to study protein structures as they give ready access to rich structural information of orientation and long-range distance restraints from the NMR signals of backbone amides, and reliable methods have become available to tag proteins with paramagnetic metal ions site-specifically and at multiple sites. In this study, we show how sparse pseudocontact shift (PCS) data can be used to computationally model conformational states in a protein system, by first identifying core structural elements that are not affected by the environmental change, and then computationally completing the remaining structure based on experimental restraints from PCS. The approach is demonstrated on a 27 kDa two-domain NS2B-NS3 protease system of the dengue virus serotype 2, for which distinct closed and open conformational states have been observed in crystal structures. By changing the input PCS data, the observed conformational states in the dengue virus protease are reproduced without modifying the computational procedure. This data driven Rosetta protocol enables identification of conformational states of a protein system, which are otherwise difficult to obtain either experimentally or computationally.     

Efficient χ-tensor determination and NH assignment of paramagnetic proteins

Anisotropic magnetic susceptibility tensors χ of paramagnetic metal ions are manifested in pseudocontact shifts, residual dipolar couplings, and other paramagnetic observables that present valuable long-range information for structure determinations of protein-ligand complexes. A program was developed for automatic determination of the χ-tensor anisotropy parameters and amide resonance assignments in proteins labeled with paramagnetic metal ions. The program requires knowledge of the three-dimensional structure of the protein, the backbone resonance assignments of the diamagnetic protein, and a pair of 2D ¹⁵N-HSQC or 3D HNCO spectra recorded with and without paramagnetic metal ion. It allows the determination of reliable χ-tensor anisotropy parameters from 2D spectra of uniformly ¹⁵N-labeled proteins of fairly high molecular weight. Examples are shown for the 185-residue N-terminal domain of the subunit ε from E. coli DNA polymerase III in complex with the subunit θ and La³⁺ in its diamagnetic and Dy³⁺, Tb³⁺, and Er³⁺ in its paramagnetic form.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.The first two authors contributed equally to the project.     

Toward the quantum chemical calculation of nuclear magnetic resonance chemical shifts of proteins

Despite the many protein structures solved successfully by nuclear magnetic resonance (NMR) spectroscopy, quality control of NMR structures is still by far not as well established and standardized as in crystallography. Therefore, there is still the need for new, independent, and unbiased evaluation tools to identify problematic parts and in the best case also to give guidelines that how to fix them. We present here, quantum chemical calculations of NMR chemical shifts for many proteins based on our fragment-based quantum chemical method: the adjustable density matrix assembler (ADMA). These results show that (13)C chemical shifts of reasonable accuracy can be obtained that can already provide a powerful measure for the structure validation. (1)H and even more (15)N chemical shifts deviate more strongly from experiment due to the insufficient treatment of solvent effects and conformational averaging.     

An NMR structural study of nickel-substituted rubredoxin

The Ni(II) and Zn(II) derivatives of Desulfovibrio vulgaris rubredoxin (DvRd) have been studied by NMR spectroscopy to probe the structure at the metal centre. The βCH₂ proton pairs from the cysteines that bind the Ni(II) atom have been identified using 1D nuclear Overhauser enhancement (NOE) difference spectra and sequence specifically assigned via NOE correlations to neighbouring protons and by comparison with the published X-ray crystal structure of a Ni(II) derivative of Clostridium pasteurianum rubredoxin. The solution structures of DvRd(Zn) and DvRd(Ni) have been determined and the paramagnetic form refined using pseudocontact shifts. The determination of the magnetic susceptibility anisotropy tensor allowed the contact and pseudocontact contributions to the observed chemical shifts to be obtained. Analysis of the pseudocontact and contact chemical shifts of the cysteine Hβ protons and backbone protons close to the metal centre allowed conclusions to be drawn as to the geometry and hydrogen-bonding pattern at the metal binding site. The importance of NH–S hydrogen bonds at the metal centre for the delocalization of electron spin density is confirmed for rubredoxins and can be extrapolated to metal centres in Cu proteins: amicyanin, plastocyanin, stellacyanin, azurin and pseudoazurin.     

Automated protein fold determination using a minimal NMR constraint strategy

Determination of precise and accurate protein structures by NMR generally requires weeks or even months to acquire and interpret all the necessary NMR data. However, even medium-accuracy fold information can often provide key clues about protein evolution and biochemical function(s). In this article we describe a largely automatic strategy for rapid determination of medium-accuracy protein backbone structures. Our strategy derives from ideas originally introduced by other groups for determining medium-accuracy NMR structures of large proteins using deuterated, (13)C-, (15)N-enriched protein samples with selective protonation of side-chain methyl groups ((13)CH(3)). Data collection includes acquiring NMR spectra for automatically determining assignments of backbone and side-chain (15)N, H(N) resonances, and side-chain (13)CH(3) methyl resonances. These assignments are determined automatically by the program AutoAssign using backbone triple resonance NMR data, together with Spin System Type Assignment Constraints (STACs) derived from side-chain triple-resonance experiments. The program AutoStructure then derives conformational constraints using these chemical shifts, amide (1)H/(2)H exchange, nuclear Overhauser effect spectroscopy (NOESY), and residual dipolar coupling data. The total time required for collecting such NMR data can potentially be as short as a few days. Here we demonstrate an integrated set of NMR software which can process these NMR spectra, carry out resonance assignments, interpret NOESY data, and generate medium-accuracy structures within a few days. The feasibility of this combined data collection and analysis strategy starting from raw NMR time domain data was illustrated by automatic analysis of a medium accuracy structure of the Z domain of Staphylococcal protein A.     

Hash: a program to accurately predict protein Hα shifts from neighboring backbone shifts

Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H^α chemical shifts suffer from the following limitations. (1) For large proteins, the H^α chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C^α that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H^α chemical shifts. Predicting accurate H^α chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict H^α chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H^α chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins.     

Strategies for the uses of lanthanide NMR shift probes in the determination of protein structure in solutio. Application to the EF calcium binding site of carp parvalbumin.

The homologous sequences observed for many calcium binding proteins such as parvalbumin, troponin C, the myosin light chains, and calmodulin has lead to the hypothesis that these proteins have homologous structures at the level of their calcium binding sites. This paper discusses the development of a nuclear magnetic resonance (NMR) technique which will enable us to test this structural hypothesis in solution. The technique involves the substitution of a paramagnetic lanthanide ion for the calcium ion which results in lanthanide induced shifts and broadening in the 1H NMR spectrum of the protein. These shifts are sensitive monitors of the precise geometrical orientation of each proton nucleus relative to the metal. The values of several parameters in the equation relating the NMR shifts to the structure are however known as priori. We have attempted to determine these parameters, the orientation and principal elements of the magnetic susceptibility tensor of the protein bound metal, by studying the lanthanide induced shifts for the protein parvalbumin whose structure has been determined by x-ray crystallographic techniques. The interaction of the lanthanide ytterbium with parvalbumin results in high resolution NMR spectra exhibiting a series of resonances with shifts spread over the range 32 to -19 ppm. The orientation and principal elements of the ytterbium magnetic susceptibility tensor have been determined using three assigned NMR resonances, the His-26 C2 and C4 protons and the amino terminal acetyl protons, and seven methyl groups; all with known geometry relative to the EF calcium binding site. The elucidation of these parameters has allowed us to compare the observed spectrum of the nuclei surrounding the EF calcium binding site of parvalbumin with that calculated from the x-ray structure. A significant number of the calculated shifts are larger than any of the observed shifts. We feel that a refinement of the x-ray based proton coordinates will be possible utilizing the geometric information contained in the lanthanide shifted NMR spectrum.     

Structural basis for the observed differential magnetic anisotropic tensorial values in calcium binding proteins

Lanthanide ions (Ln(3+)), which have ionic radii similar to those of Ca(2+), can displace the latter in a calcium binding protein, without affecting its tertiary structure. The paramagnetic Ln(3+) possesses large anisotropic magnetic susceptibilities and produce pseudocontact shifts (PCSs), which have r(-3) dependence. The PCS can be seen for spins as far as 45 A from the paramagnetic ion. They aid in structure refinement of proteins by providing long-range distance constraints. Besides, they can be used to determine the interdomain orientation in multidomain proteins. This is particularly important in the context of a calcium binding protein from Entamoeba histolytica (EhCaBP), which consists of two globular domains connected by a flexible linker region containing 8 residues. As a first step to obtain the interdomain orientation in EhCaBP, a suite of 2D and 3D heteronuclear experiments were recorded on EhCaBP by displacing calcium with Ce(3+), Ho(3+), Er(3+), Tm(3+), Dy(3+), and Yb(3+) ions in separate experiments, and the PCS of (1)H(N) and (15)N spins were measured. Such data have been used in the refinement of the individual domain structures of the protein in parallel with the calculation of the respective magnetic anisotropy tensorial values, which differ substantially (2.1-2.8 times) from what is found in other Ca(2+) binding loops. This study provides a structural basis for such variations in the magnetic anisotropy tensorial values.     

Prediction of Xaa-Pro peptide bond conformation from sequence and chemical shifts

We present a program, named Promega, to predict the Xaa-Pro peptide bond conformation on the basis of backbone chemical shifts and the amino acid sequence. Using a chemical shift database of proteins of known structure together with the PDB-extracted amino acid preference of cis Xaa-Pro peptide bonds, a cis/trans probability score is calculated from the backbone and ¹³C^β chemical shifts of the proline and its neighboring residues. For an arbitrary number of input chemical shifts, which may include Pro-¹³C^γ, Promega calculates the statistical probability that a Xaa-Pro peptide bond is cis. Besides its potential as a validation tool, Promega is particularly useful for studies of larger proteins where Pro-¹³C^γ assignments can be challenging, and for on-going efforts to determine protein structures exclusively on the basis of backbone and ¹³C^β chemical shifts.     

Nitrotyrosine chelation of nuclear magnetic resonance shift probes in proteins: application to bovine pancreatic trypsin inhibitor

The interactions of Pr(III) and Eu(III) with specifically nitrated derivatives of the basic bovine pancreatic trypsin inhibitor have been studied using optical spectroscopy and nuclear magnetic resonance (NMR) at 250 and 270 MHz. Stability constants for proton and metal binding to nitrotyrosines 10 and 21 determined optically are in good agreement with those from NMR. Observations of the Eu(III)-induced NMR shifts of the ring protons of nitrotyrosine 21 allowed calibration of the magnetic interactions for this binding site. The Pr(III)-induced shifts for several resolved nonexchangeable backbone proton resonances were compared with calculated shifts using the known x-ray structure. With several simplifying assumptions, the Pr(III)-induced shifts were used to assign one alpha-CH and five NH protons to compatible sets of backbone positions which are consistent with the known pH dependence and resistance to exchange with solvent D2O. Some of the more general aspects of lanthanide-induced shifts are discussed with reference to their use in proteins. Due to the complexities of the analysis of the shift data, the most straightforward use of this technique is in conjunction with the relaxation probe Gd(III) for measurement of intramolecular distances.     

Determination of solution structures of paramagnetic proteins by NMR

Standard procedures for using nuclear Overhauser enhancements (NOE) between protons to generate structures for diamagnetic proteins in solution from NMR data may be supplemented by using dipolar shifts if the protein is paramagnetic. This is advantageous since the electron-nuclear dipolar coupling provides relatively long-range geometric information with respect to the paramagnetic centre which complements the short-range distance constraints from NOEs. Several different strategies have been developed to date, but none of these attempts to combine data from NOEs and dipolar shifts in the initial stages of structure calculation or to determine three dimensional protein structures together with their magnetic properties. This work shows that the magnetic and atomic structures are highly correlated and that it is important to have additional constraints both to provide starting parameters for the magnetic properties and to improve the definition of the best fit. Useful parameters can be obtained for haem proteins from Fermi contact shifts; this approach is compared with a new method based on the analysis of dipolar shifts in haem methyl groups with respect to data from horse and tuna ferricytochromes c. The methods developed for using data from NOEs and dipolar shifts have been incorporated in a new computer program, PARADYANA, which is demonstrated in application to a model data set for the sequence of the haem octapeptide known as microperoxidase-8. Received: 13 October 1997 / Accepted: 19 December 1997     

Protein Structure Validation and Refinement Using Amide Proton Chemical Shifts Derived from Quantum Mechanics

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (^h3 J_NC'') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to obtain this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding.     

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     

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.     

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (?, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ¹ rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.     

Structure-based prediction of methyl chemical shifts in proteins

Protein methyl groups have recently been the subject of much attention in NMR spectroscopy because of the opportunities that they provide to obtain information about the structure and dynamics of proteins and protein complexes. With the advent of selective labeling schemes, methyl groups are particularly interesting in the context of chemical shift based protein structure determination, an approach that to date has exploited primarily the mapping between protein structures and backbone chemical shifts. In order to extend the scope of chemical shifts for structure determination, we present here the CH3Shift method of performing structure-based predictions of methyl chemical shifts. The terms considered in the predictions take account of ring current, magnetic anisotropy, electric field, rotameric type, and dihedral angle effects, which are considered in conjunction with polynomial functions of interatomic distances. We show that the CH3Shift method achieves an accuracy in the predictions that ranges from 0.133 to 0.198 ppm for ¹H chemical shifts for Ala, Thr, Val, Leu and Ile methyl groups. We illustrate the use of the method by assessing the accuracy of side-chain structures in structural ensembles representing the dynamics of proteins.