Residual dipolar couplings: Synergy between NMR and structural genomics

Structural genomics is on a quest for the structure and function of a significant fraction of gene products. Current efforts are focusing on structure determination of single-domain proteins, which can readily be targeted by X-ray crystallography, NMR spectroscopy and computational homology modeling. However, comprehensive association of gene products with functions also requires systematic determination of more complex protein structures and other biomolecules participating in cellular processes such as nucleic acids, and characterization of biomolecular interactions and dynamics relevant to function. Such NMR investigations are becoming more feasible, not only due to recent advances in NMR methodology, but also because structural genomics is providing valuable structural information and new experimental and computational tools. The measurement of residual dipolar couplings in partially oriented systems and other new NMR methods will play an important role in this synergistic relationship between NMR and structural genomics. Both an expansion in the domain of NMR application, and important contributions to future structural genomics efforts can be anticipated.     

Intermolecular relaxation has little effect on intra-peptide exchange-transferred NOE intensities

Exchange-transferred nuclear Overhauser enhancement (etNOE) provides a useful method for determining the 3-dimensional structure of a ligand bound to a high-molecular-weight complex. Some concern about the accuracy of such structures has arisen because indirect relaxation can occur between the ligand and macromolecule. Such indirect relaxation, or spin diffusion, would lead to errors in interproton distances used as restraints in structure determination. We address this concern by assessing the extent of intermolecular spin diffusion in nineteen peptide-protein complexes of known structure. Transferred NOE intensities were simulated with the program CORONA (Calculated OR Observed NOESY Analysis) using the rate-matrix approach to include contributions from indirect relaxation between protein-ligand and intraligand proton pairs. Intermolecular spin diffusion contributions were determined by comparing intensities calculated with protonated protein to those calculated with fully deuterated protein. The differences were found to be insignificant overall, and to diminish at short mixing times and high mole ratios of peptide to protein. Spin diffusion between the peptide ligand and the protein contributes less to the etNOE intensities and alters fewer cross peaks than the well-studied intramolecular spin diffusion effects. Errors in intraligand interproton distances due to intermolecular relaxation effects were small on average and can be accounted for with the restraint functions commonly used in NMR structure determination methods. In addition, a rate-matrix approach to calculate distances from etNOESY intensities using a volume matrix comprising only intraligand intensities was found to give accurate values. Based on these results, we conclude that structures determined from etNOESY data are no less accurate due to spin diffusion than structures determined from conventional NOE intensities.     

Computer modeling of nitroxide spin labels on proteins

Electron paramagnetic resonance using site‐directed spin labeling can be used as an approach for determination of protein structures that are difficult to solve by other methods. One important aspect of this approach is the measurement of interlabel distances using the double electron–electron resonance (DEER) method. Interpretation of experimental data could be facilitated by a computational approach to calculation of interlabel distances. We describe an algorithm, PRONOX, for rapid computation of interlabel distances based on calculation of spin label conformer distributions at any site of a protein. The program incorporates features of the label distribution established experimentally, including weighting of favorable conformers of the label. Distances calculated by PRONOX were compared with new DEER distances for amphiphysin and annexin B12 and with published data for FCHo2 (F‐BAR), endophilin, and α‐synuclein, a total of 44 interlabel distances. The program reproduced these distances accurately (r² = 0.94, slope = 0.98). For 9 of the 11 distances for amphiphysin, PRONOX reproduced the experimental data to within 2.5 Å. The speed and accuracy of PRONOX suggest that the algorithm can be used for fitting to DEER data for determination of protein tertiary structure. © 2011 Wiley Periodicals, Inc. Biopolymers 97: 35–44, 2012.     

Systematic application of high-resolution, phase-sensitive two-dimensional 1H-NMR techniques for the identification of the amino-acid-proton spin systems in proteins. Rabbit metallothionein-2

Novel strategies for elucidation and classification of amino acid 1H-NMR spin systems in proteins were developed exploiting recently introduced two-dimensional NMR techniques such as phase-sensitive double-quantum-filtered correlated spectroscopy, relayed coherence transfer spectroscopy, double quantum spectroscopy and nuclear Overhauser spectroscopy. Due to the improved resolution in phase-sensitive spectra, the fine structure of cross peaks could be exploited as a powerful source of information for establishing 1H-1H connectivities. Principles for the interpretation of multiplet structures of absorption mode cross peaks are discussed. With these methods the 1H spin systems of rabbit liver metallothionein-2 were elucidated and classified according to amino acid types. Despite the intrinsically difficult situation arising from the unusual amino acid composition of this protein, a more complete characterization of the 1H spin systems prior to the step of sequential resonance assignments was achieved with the presently introduced methodology than was possible in earlier studies of proteins of similar size.     

G‐protein‐coupled receptor structures were not built in a day

Among the most exciting recent developments in structural biology is the structure determination of G‐protein‐coupled receptors (GPCRs), which comprise the largest class of membrane proteins in mammalian cells and have enormous importance for disease and drug development. The GPCR structures are perhaps the most visible examples of a nascent revolution in membrane protein structure determination. Like other major milestones in science, however, such as the sequencing of the human genome, these achievements were built on a hidden foundation of technological developments. Here, we describe some of the methods that are fueling the membrane protein structure revolution and have enabled the determination of the current GPCR structures, along with new techniques that may lead to future structures.     

Histogram-based scoring schemes for protein NMR resonance assignment

In NMR protein structure determination, after the resonance peaks have been identified and chemical shifts from peaks across multiple spectra have been grouped into spin systems, associating these spin systems to their host residues is the key toward the success of structural information extraction and thus the key to the success of the structure calculation. To achieve accurate enough structure calculation, a near complete and accurate assignment is a prerequisite. There are two pieces of information that can be used into the assignment, one of which is the adjacency information among the spin systems and the other is the signature information of the spin systems. The signature information reflects the fact that, generally speaking, for one type of amino acid residing in a specific local structural environment, the chemical shifts for the atoms inside the amino acid fall into some very narrow distinct ranges. In most of the existing work, normal distributions are assumed with means and standard deviations statistically collected from the available data. In this paper, we followed a simple yet effective histogram-based way to estimate for every spin system the probability that its host is a certain type of amino acid residing in a certain type of secondary structure. We used two combinations of chemical shifts to demonstrate the effectiveness of this type of histogram-based scoring schemes.     

Geometry dependent two-dimensional heteronuclear multiplet effects in paramagnetic proteins

We report experimental observation and numerical simulation of a two-dimensional multiplet effect in the heteronuclear correlation spectrum of a paramagnetic protein that depends on molecular geometry. This effect arises as a consequence of cross-correlated relaxation involving the Curie spin relaxation and internuclear dipolar relaxation mechanisms. It also manifests itself in resolution and sensitivity improvement in transverse relaxation optimised spectroscopy (TROSY) kind of experiments. Characteristic multiplet patterns in heteronuclear coupled two-dimensional NMR spectra encode directional information for the heteronuclear bond with respect to the paramagnetic center. These patterns, which are simulated here using Redfield's relaxation theory, can be used to obtain a new type of geometry restriction for structure determination and refinement of paramagnetic macromolecular systems.     

Calculation of protein conformations by proton-proton distance constraints. A new efficient algorithm

We have developed a method to determine the three-dimensional structure of a protein molecule from such a set of distance constraints as can be determined by nuclear magnetic resonance studies. The currently popular methods for distance geometry based on the use of the metric matrix are applicable only to small systems. The method developed here is applicable to large molecules, such as proteins, with all atoms treated explicitly. This method works in the space of variable dihedral angles and determines a three-dimensional structure by minimization of a target function. We avoid difficulties hitherto inherent in this type of approach by two new devices: the use of variable target functions; and a method of rapid calculation of the gradient of the target functions. The method is applied to the determination of the structures of a small globular protein, bovine pancreatic trypsin inhibitor, from several artificial sets of distance constraints extracted from the X-ray crystal structure of this molecule. When a good set of constraints was available for both short- and long-range distances, the crystal structure was regenerated nearly exactly. When some ambiguities, such as those expected in experimental information, are allowed, the protein conformation can be determined up to a few local deformations. These ambiguities are mainly associated with the low resolving power of the short-range information.     

Automated structure determination from NMR spectra

Automated methods for protein structure determination by NMR have increasingly gained acceptance and are now widely used for the automated assignment of distance restraints and the calculation of three-dimensional structures. This review gives an overview of the techniques for automated protein structure analysis by NMR, including both NOE-based approaches and methods relying on other experimental data such as residual dipolar couplings and chemical shifts, and presents the FLYA algorithm for the fully automated NMR structure determination of proteins that is suitable to substitute all manual spectra analysis and thus overcomes a major efficiency limitation of the NMR method for protein structure determination.     

Backbone solution structures of proteins using residual dipolar couplings: Application to a novel structural genomics target

Structural genomics (or proteomics) activities are critically dependent on the availability of high-throughput structure determination methodology. Development of such methodology has been a particular challenge for NMR based structure determination because of the demands for isotopic labeling of proteins and the requirements for very long data acquisition times. We present here a methodology that gains efficiency from a focus on determination of backbone structures of proteins as opposed to full structures with all sidechains in place. This focus is appropriate given the presumption that many protein structures in the future will be built using computational methods that start from representative fold family structures and replace as many as 70% of the sidechains in the course of structure determination. The methodology we present is based primarily on residual dipolar couplings (RDCs), readily accessible NMR observables that constrain the orientation of backbone fragments irrespective of separation in space. A new software tool is described for the assembly of backbone fragments under RDC constraints and an application to a structural genomics target is presented. The target is an 8.7 kDa protein from Pyrococcus furiosus, PF1061, that was previously not well annotated, and had a nearest structurally characterized neighbor with only 33% sequence identity. The structure produced shows structural similarity to this sequence homologue, but also shows similarity to other proteins, which suggests a functional role in sulfur transfer. Given the backbone structure and a possible functional link this should be an ideal target for development of modeling methods. This revised version was published online in March 2005 with corrections to the references.     

Backbone solution structures of proteins using residual dipolar couplings: application to a novel structural genomics target

Structural genomics (or proteomics) activities are critically dependent on the availability of high-throughput structure determination methodology. Development of such methodology has been a particular challenge for NMR based structure determination because of the demands for isotopic labeling of proteins and the requirements for very long data acquisition times. We present here a methodology that gains efficiency from a focus on determination of backbone structures of proteins as opposed to full structures with all sidechains in place. This focus is appropriate given the presumption that many protein structures in the future will be built using computational methods that start from representative fold family structures and replace as many as 70% of the sidechains in the course of structure determination. The methodology we present is based primarily on residual dipolar couplings (RDCs), readily accessible NMR observables that constrain the orientation of backbone fragments irrespective of separation in space. A new software tool is described for the assembly of backbone fragments under RDC constraints and an application to a structural genomics target is presented. The target is an 8.7 kDa protein from Pyrococcus furiosus, PF1061, that was previously not well annotated, and had a nearest structurally characterized neighbor with only 33% sequence identity. The structure produced shows structural similarity to this sequence homologue, but also shows similarity to other proteins, which suggests a functional role in sulfur transfer. Given the backbone structure and a possible functional link this should be an ideal target for development of modeling methods.     

Protein structure validation by generalized linear model root-mean-square deviation prediction

Large-scale initiatives for obtaining spatial protein structures by experimental or computational means have accentuated the need for the critical assessment of protein structure determination and prediction methods. These include blind test projects such as the critical assessment of protein structure prediction (CASP) and the critical assessment of protein structure determination by nuclear magnetic resonance (CASD-NMR). An important aim is to establish structure validation criteria that can reliably assess the accuracy of a new protein structure. Various quality measures derived from the coordinates have been proposed. A universal structural quality assessment method should combine multiple individual scores in a meaningful way, which is challenging because of their different measurement units. Here, we present a method based on a generalized linear model (GLM) that combines diverse protein structure quality scores into a single quantity with intuitive meaning, namely the predicted coordinate root-mean-square deviation (RMSD) value between the present structure and the (unavailable) "true" structure (GLM-RMSD). For two sets of structural models from the CASD-NMR and CASP projects, this GLM-RMSD value was compared with the actual accuracy given by the RMSD value to the corresponding, experimentally determined reference structure from the Protein Data Bank (PDB). The correlation coefficients between actual (model vs. reference from PDB) and predicted (model vs. "true") heavy-atom RMSDs were 0.69 and 0.76, for the two datasets from CASD-NMR and CASP, respectively, which is considerably higher than those for the individual scores (-0.24 to 0.68). The GLM-RMSD can thus predict the accuracy of protein structures more reliably than individual coordinate-based quality scores.     

The Protein Model Portal

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at and from the PSI Structural Genomics Knowledgebase.     

Structural similarity of DNA-binding domains of bacteriophage repressors and the globin core

BACKGROUND: In recent years, the determination of large numbers of protein structures has created a need for automatic and objective methods for the comparison of structures or conformations. Many protein structures show similarities of conformation that are undetectable by comparing their sequences. Comparison of structures can reveal similarities between proteins thought to be unrelated, providing new insight into the interrelationships of sequence, structure and function. RESULTS: Using a new tool that we have developed to perform rapid structural alignment, we present the highlights of an exhaustive comparison of all pairs of protein structures in the Brookhaven protein database. Notably, we find that the DNA-binding domain of the bacteriophage repressor family is almost completely embedded in the larger eight-helix fold of the globin family of proteins. The significant match of specific residues is correlated with functional, structural and evolutionary information. CONCLUSION: Our method can help to identify structurally similar folds rapidly and with high-sensitivity, providing a powerful tool for analyzing the ever-increasing number of protein structures being elucidated.     

Distance mapping of protein-binding sites using spin-labeled oligosaccharide ligands

The binding of a nitroxide spin-labeled analog of N-acetyllactosamine to galectin-3, a mammalian lectin of 26 kD size, is studied to map the binding sites of this small oligosaccharide on the protein surface. Perturbation of intensities of cross-peaks in the (15)N heteronuclear single quantum coherence (HSQC) spectrum of full-length galectin-3 owing to the bound spin label is used qualitatively to identify protein residues proximate to the binding site for N-acetyllactosamine. A protocol for converting intensity measurements to a more quantitative determination of distances between discrete protein amide protons and the bound spin label is then described. This protocol is discussed as part of a drug design strategy in which subsequent perturbation of chemical shifts of distance mapped amide cross-peaks can be used effectively to screen a library of compounds for other ligands that bind to the target protein at distances suitable for chemical linkage to the primary ligand. This approach is novel in that it bypasses the need for structure determination and resonance assignment of the target protein.     

NMR of membrane proteins in micelles and bilayers: the FXYD family proteins

Determining the atomic resolution structures of membrane proteins is of particular interest in contemporary structural biology. Helical membrane proteins constitute one-third of the expressed proteins encoded in a genome, many drugs have membrane-bound proteins as their receptors, and mutations in membrane proteins result in human diseases. Although integral membrane proteins provide daunting technical challenges for all methods of protein structure determination, nuclear magnetic resonance (NMR) spectroscopy can be an extremely versatile and powerful method for determining their structures and characterizing their dynamics, in lipid environments that closely mimic the cell membranes. Once milligram amounts of isotopically labeled protein are expressed and purified, micelle samples can be prepared for solution NMR analysis, and lipid bilayer samples can be prepared for solid-state NMR analysis. The two approaches are complementary and can provide detailed structural and dynamic information. This paper describes the steps for membrane protein structure determination using solution and solid-state NMR. The methods for protein expression and purification, sample preparation and NMR experiments are described and illustrated with examples from the FXYD proteins, a family of regulatory subunits of the Na,K-ATPase.     

Protein complexes: structure prediction challenges for the 21st century

Only a tiny fraction of the many hundreds of known protein complexes are also of known three-dimensional structure. The experimental difficulties surrounding structure determination of complexes make methods that are able to predict structures paramount. The challenge of predicting complex structures is daunting and raises many issues that need to be addressed. To produce the best models, new prediction methods have to somehow combine partial structures with a mixed bag of experimental data, including interactions and low-resolution electron microscopy images.     

Paramagnetic effects in NMR for protein structures and ensembles: Studies of metalloproteins

Paramagnetic effects on the NMR spectra are known to encode information on structure, electronic properties and dynamics hardly accessible with any other technique, especially in the field of biological systems. Paramagnetism-based restraints are conveniently used for the de novo determination of protein structures, the structural refinement starting from crystallographic models, and for the determination of the internal arrangement of domains with known structures. Conformational variability can also be profitably interrogated including the possibility of uncovering the presence of states with very low population. The recent advances in the quantum chemistry treatment of paramagnetic NMR effects has provided new momentum to the field, allowing for the refinement of protein structures at the metal coordination site to an unprecedented resolution.     

ABACUS, a direct method for protein NMR structure computation via assembly of fragments

The ABACUS algorithm obtains the protein NMR structure from unassigned NOESY distance restraints. ABACUS works as an integrated approach that uses the complete set of available NMR experimental information in parallel and yields spin system typing, NOE spin pair identities, sequence specific resonance assignments, and protein structure, all at once. The protocol starts from unassigned molecular fragments (including single amino acid spin systems) derived from triple-resonance (1)H/(13)C/(15)N NMR experiments. Identifications of connected spin systems and NOEs precede the full sequence specific resonance assignments. The latter are obtained iteratively via Monte Carlo-Metropolis and/or probabilistic sequence selections, molecular dynamics structure computation and BACUS filtering (A. Grishaev and M. Llinás, J Biomol NMR 2004;28:1-10). ABACUS starts from scratch, without the requirement of an initial approximate structure, and improves iteratively the NOE identities in a self-consistent fashion. The procedure was run as a blind test on data recorded on mth1743, a 70-amino acid genomic protein from M. thermoautotrophicum. It converges to a structure in ca. 15 cycles of computation on a 3-GHz processor PC. The calculated structures are very similar to the ones obtained via conventional methods (1.22 A backbone RMSD). The success of ABACUS on mth1743 further validates BACUS as a NOESY identification protocol.