An integrated platform for automated analysis of protein NMR structures

Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA

Nuclear Magnetic Resonance (NMR) spectroscopy is a major technique in structural biology with over 11,800 protein structures deposited in the Protein Data Bank. NMR can elucidate structures and dynamics of small and medium size proteins in solution, living cells, and solids, but has been limited by the tedious data analysis process. It typically requires weeks or months of manual work of a trained expert to turn NMR measurements into a protein structure. Automation of this process is an open problem, formulated in the field over 30 years ago. We present a solution to this challenge that enables the completely automated analysis of protein NMR data within hours after completing the measurements. Using only NMR spectra and the protein sequence as input, our machine learning-based method, ARTINA, delivers signal positions, resonance assignments, and structures strictly without human intervention. Tested on a 100-protein benchmark comprising 1329 multidimensional NMR spectra, ARTINA demonstrated its ability to solve structures with 1.44 Å median RMSD to the PDB reference and to identify 91.36% correct NMR resonance assignments. ARTINA can be used by non-experts, reducing the effort for a protein assignment or structure determination by NMR essentially to the preparation of the sample and the spectra measurements.

Role of backbone strain in de novo design of complex α/β protein structures

We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αβ-proteins with four or fewer β-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and β-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded β-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the β-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.

A common binding motif in the ET domain of BRD3 forms polymorphic structural interfaces with host and viral proteins

The extraterminal (ET) domain of BRD3 is conserved among BET proteins (BRD2, BRD3, BRD4), interacting with multiple host and viral protein-protein networks. Solution NMR structures of complexes formed between the BRD3 ET domain and either the 79-residue murine leukemia virus integrase (IN) C-terminal domain (IN_329-408) or its 22-residue IN tail peptide (IN_386-407) alone reveal similar intermolecular three-stranded β-sheet formations. ¹⁵N relaxation studies reveal a 10-residue linker region (IN_379-388) tethering the SH3 domain (IN_329-378) to the ET-binding motif (IN_389-405):ET complex. This linker has restricted flexibility, affecting its potential range of orientations in the IN:nucleosome complex. The complex of the ET-binding peptide of the host NSD3 protein (NSD3_148-184) and the BRD3 ET domain includes a similar three-stranded β-sheet interaction, but the orientation of the β hairpin is flipped compared with the two IN:ET complexes. These studies expand our understanding of molecular recognition polymorphism in complexes of ET-binding motifs with viral and host proteins.

A method for validating the accuracy of NMR protein structures

We present a method that measures the accuracy of NMR protein structures. It compares random coil index [RCI] against local rigidity predicted by mathematical rigidity theory, calculated from NMR structures [FIRST], using a correlation score (which assesses secondary structure), and an RMSD score (which measures overall rigidity). We test its performance using: structures refined in explicit solvent, which are much better than unrefined structures; decoy structures generated for 89 NMR structures; and conventional predictors of accuracy such as number of restraints per residue, restraint violations, energy of structure, ensemble RMSD, Ramachandran distribution, and clashscore. Restraint violations and RMSD are poor measures of accuracy. Comparisons of NMR to crystal structures show that secondary structure is equally accurate, but crystal structures are typically too rigid in loops, whereas NMR structures are typically too floppy overall. We show that the method is a useful addition to existing measures of accuracy.

Inhibitor Bound Dengue NS2B-NS3pro Reveals Multiple Dynamic Binding Modes

Dengue virus poses a significant global health threat as the source of increasingly deleterious dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. As no specific antiviral treatment exists for dengue infection, considerable effort is being applied to discover therapies and drugs for maintenance and prevention of these afflictions. The virus is primarily transmitted by mosquitoes, and infection occurs following viral endocytosis by host cells. Upon entering the cell, viral RNA is translated into a large multisubunit polyprotein which is post-translationally cleaved into mature, structural and nonstructural (NS) proteins. The viral genome encodes the enzyme to carry out cleavage of the large polyprotein, specifically the NS2B-NS3pro cofactor-protease complex-a target of high interest for drug design. One class of recently discovered NS2B-NS3pro inhibitors is the substrate-based trifluoromethyl ketone containing peptides. These compounds interact covalently with the active site Ser135 via a hemiketal adduct. A detailed picture of the intermolecular protease/inhibitor interactions of the hemiketal adduct is crucial for rational drug design. We demonstrate, through the use of protein- and ligand-detected solution-state ¹⁹F and ¹H NMR methods, an unanticipated multibinding mode behavior of a representative of this class of inhibitors to dengue NS2B-NS3pro. Our results illustrate the highly dynamic nature of both the covalently bound ligand and protease protein structure, and the need to consider these dynamics when designing future inhibitors in this class.

Introduction of a polar core into the de novo designed protein Top7

Design of polar interactions is a current challenge for protein design. The de novo designed protein Top7, like almost all designed proteins, has an entirely nonpolar core. Here we describe the replacing of a sizable fraction (5 residues) of this core with a designed polar hydrogen bond network. The polar core design is expressed at high levels in E. coli, has a folding free energy of 10 kcal/mol, and retains the multiphasic folding kinetics of the original Top7. The NMR structure of the design shows that conformations of three of the five residues, and the designed hydrogen bonds between them, are very close to those in the design model. The remaining two residues, which are more solvent exposed, sample a wide range of conformations in the NMR ensemble. These results show that hydrogen bond networks can be designed in protein cores, but also highlight challenges that need to be overcome when there is competition with solvent.

Critical assessment of methods of protein structure prediction: Progress and new directions in round XI

Modeling of protein structure from amino acid sequence now plays a major role in structural biology. Here we report new developments and progress from the CASP11 community experiment, assessing the state of the art in structure modeling. Notable points include the following: (1) New methods for predicting three dimensional contacts resulted in a few spectacular template free models in this CASP, whereas models based on sequence homology to proteins with experimental structure continue to be the most accurate. (2) Refinement of initial protein models, primarily using molecular dynamics related approaches, has now advanced to the point where the best methods can consistently (though slightly) improve nearly all models. (3) The use of relatively sparse NMR constraints dramatically improves the accuracy of models, and another type of sparse data, chemical crosslinking, introduced in this CASP, also shows promise for producing better models. (4) A new emphasis on modeling protein complexes, in collaboration with CAPRI, has produced interesting results, but also shows the need for more focus on this area. (5) Methods for estimating the accuracy of models have advanced to the point where they are of considerable practical use. (6) A first assessment demonstrates that models can sometimes successfully address biological questions that motivate experimental structure determination. (7) There is continuing progress in accuracy of modeling regions of structure not directly available by comparative modeling, while there is marginal or no progress in some other areas. Proteins 2016; 84(Suppl 1):4-14. © 2016 Wiley Periodicals, Inc.

A community resource of experimental data for NMR / X-ray crystal structure pairs

We have developed an online NMR / X-ray Structure Pair Data Repository. The NIGMS Protein Structure Initiative (PSI) has provided many valuable reagents, 3D structures, and technologies for structural biology. The Northeast Structural Genomics Consortium was one of several PSI centers. NESG used both X-ray crystallography and NMR spectroscopy for protein structure determination. A key goal of the PSI was to provide experimental structures for at least one representative of each of hundreds of targeted protein domain families. In some cases, structures for identical (or nearly identical) constructs were determined by both NMR and X-ray crystallography. NMR spectroscopy and X-ray diffraction data for 41 of these "NMR / X-ray" structure pairs determined using conventional triple-resonance NMR methods with extensive sidechain resonance assignments have been organized in an online NMR / X-ray Structure Pair Data Repository. In addition, several NMR data sets for perdeuterated, methyl-protonated protein samples are included in this repository. As an example of the utility of this repository, these data were used to revisit questions about the precision and accuracy of protein NMR structures first outlined by Levy and coworkers several years ago (Andrec et al., Proteins 2007;69:449-465). These results demonstrate that the agreement between NMR and X-ray crystal structures is improved using modern methods of protein NMR spectroscopy. The NMR / X-ray Structure Pair Data Repository will provide a valuable resource for new computational NMR methods development.

Performance of the WeNMR CS-Rosetta3 web server in CASD-NMR

We present here the performance of the WeNMR CS-Rosetta3 web server in CASD-NMR, the critical assessment of automated structure determination by NMR. The CS-Rosetta server uses only chemical shifts for structure prediction, in combination, when available, with a post-scoring procedure based on unassigned NOE lists (Huang et al. in J Am Chem Soc 127:1665-1674, 2005b, doi: 10.1021/ja047109h). We compare the original submissions using a previous version of the server based on Rosetta version 2.6 with recalculated targets using the new R3FP fragment picker for fragment selection and implementing a new annotation of prediction reliability (van der Schot et al. in J Biomol NMR 57:27-35, 2013, doi: 10.1007/s10858-013-9762-6), both implemented in the CS-Rosetta3 WeNMR server. In this second round of CASD-NMR, the WeNMR CS-Rosetta server has demonstrated a much better performance than in the first round since only converged targets were submitted. Further, recalculation of all CASD-NMR targets using the new version of the server demonstrates that our new annotation of prediction quality is giving reliable results. Predictions annotated as weak are often found to provide useful models, but only for a fraction of the sequence, and should therefore only be used with caution.

The second round of Critical Assessment of Automated Structure Determination of Proteins by NMR: CASD-NMR-2013

The second round of the community-wide initiative Critical Assessment of automated Structure Determination of Proteins by NMR (CASD-NMR-2013) comprised ten blind target datasets, consisting of unprocessed spectral data, assigned chemical shift lists and unassigned NOESY peak and RDC lists, that were made available in both curated (i.e. manually refined) or un-curated (i.e. automatically generated) form. Ten structure calculation programs, using fully automated protocols only, generated a total of 164 three-dimensional structures (entries) for the ten targets, sometimes using both curated and un-curated lists to generate multiple entries for a single target. The accuracy of the entries could be established by comparing them to the corresponding manually solved structure of each target, which was not available at the time the data were provided. Across the entire data set, 71 % of all entries submitted achieved an accuracy relative to the reference NMR structure better than 1.5 Å. Methods based on NOESY peak lists achieved even better results with up to 100% of the entries within the 1.5 Å threshold for some programs. However, some methods did not converge for some targets using un-curated NOESY peak lists. Over 90% of the entries achieved an accuracy better than the more relaxed threshold of 2.5 Å that was used in the previous CASD-NMR-2010 round. Comparisons between entries generated with un-curated versus curated peaks show only marginal improvements for the latter in those cases where both calculations converged.

Protein structure determination by combining sparse NMR data with evolutionary couplings

Accurate protein structure determination by NMR is challenging for larger proteins, for which experimental data is often incomplete and ambiguous. Fortunately, the upsurge in evolutionary sequence information and advances in maximum entropy statistical methods now provide a rich complementary source of structural constraints. We have developed a hybrid approach (EC-NMR) combining sparse NMR data with evolutionary residue-residue couplings, and demonstrate accurate structure determination for several 6 to 41 kDa proteins.

Structural and sequencing analysis of local target DNA recognition by MLV integrase

Target-site selection by retroviral integrase (IN) proteins profoundly affects viral pathogenesis. We describe the solution nuclear magnetic resonance structure of the Moloney murine leukemia virus IN (M-MLV) C-terminal domain (CTD) and a structural homology model of the catalytic core domain (CCD). In solution, the isolated MLV IN CTD adopts an SH3 domain fold flanked by a C-terminal unstructured tail. We generated a concordant MLV IN CCD structural model using SWISS-MODEL, MMM-tree and I-TASSER. Using the X-ray crystal structure of the prototype foamy virus IN target capture complex together with our MLV domain structures, residues within the CCD α2 helical region and the CTD β1-β2 loop were predicted to bind target DNA. The role of these residues was analyzed in vivo through point mutants and motif interchanges. Viable viruses with substitutions at the IN CCD α2 helical region and the CTD β1-β2 loop were tested for effects on integration target site selection. Next-generation sequencing and analysis of integration target sequences indicate that the CCD α2 helical region, in particular P187, interacts with the sequences distal to the scissile bonds whereas the CTD β1-β2 loop binds to residues proximal to it. These findings validate our structural model and disclose IN-DNA interactions relevant to target site selection.

NMR structure validation in relation to dynamics and structure determination

NMR spectroscopy is a key technique for understanding the behaviour of proteins, especially highly dynamic proteins that adopt multiple conformations in solution. Overall, protein structures determined from NMR spectroscopy data constitute just over 10% of the Protein Data Bank archive. This review covers the validation of these NMR protein structures, but rather than describing currently available methodology, it focuses on concepts that are important for understanding where and how validation is most relevant. First, the inherent characteristics of the protein under study have an influence on quality and quantity of the distinct types of data that can be acquired from NMR experiments. Second, these NMR data are necessarily transformed into a model for use in a structure calculation protocol, and the protein structures that result from this reflect the types of NMR data used as well as the protein characteristics. The validation of NMR protein structures should therefore take account, wherever possible, of the inherent behavioural characteristics of the protein, the types of available NMR data, and the calculation protocol. These concepts are discussed in the context of 'knowledge based' and 'model versus data' validation, with suggestions for questions to ask and different validation categories to consider. The principal aim of this review is to stimulate discussion and to help the reader understand the relationships between the above elements in order to make informed decisions on which validation approaches are the most relevant in particular cases.

High-quality NMR structure of human anti-apoptotic protein domain Mcl-1(171-327) for cancer drug design

A high-quality NMR solution structure is presented for protein hMcl-1(171–327) which comprises residues 171–327 of the human anti-apoptotic protein Mcl-1 (hMcl-1). Since this construct contains the three Bcl-2 homology (BH) sequence motifs which participate in forming a binding site for inhibitors of hMcl-1, it is deemed to be crucial for structure-based design of novel anti-cancer drugs blocking the Mcl1 related anti-apoptotic pathway. While the coordinates of an NMR solution structure for a corresponding construct of the mouse homologue (mMcl-1) are publicly available, our structure is the first atomic resolution structure reported for the ‘apo form’ of the human protein. Comparison of the two structures reveals that hMcl-1(171–327) exhibits a somewhat wider ligand/inhibitor binding groove as well as a different charge distribution within the BH3 binding groove. These findings strongly suggest that the availability of the human structure is of critical importance to support future design of cancer drugs.

PDBStat: a universal restraint converter and restraint analysis software package for protein NMR

The heterogeneous array of software tools used in the process of protein NMR structure determination presents organizational challenges in the structure determination and validation processes, and creates a learning curve that limits the broader use of protein NMR in biology. These challenges, including accurate use of data in different data formats required by software carrying out similar tasks, continue to confound the efforts of novices and experts alike. These important issues need to be addressed robustly in order to standardize protein NMR structure determination and validation. PDBStat is a C/C++ computer program originally developed as a universal coordinate and protein NMR restraint converter. Its primary function is to provide a user-friendly tool for interconverting between protein coordinate and protein NMR restraint data formats. It also provides an integrated set of computational methods for protein NMR restraint analysis and structure quality assessment, relabeling of prochiral atoms with correct IUPAC names, as well as multiple methods for analysis of the consistency of atomic positions indicated by their convergence across a protein NMR ensemble. In this paper we provide a detailed description of the PDBStat software, and highlight some of its valuable computational capabilities. As an example, we demonstrate the use of the PDBStat restraint converter for restrained CS-Rosetta structure generation calculations, and compare the resulting protein NMR structure models with those generated from the same NMR restraint data using more traditional structure determination methods. These results demonstrate the value of a universal restraint converter in allowing the use of multiple structure generation methods with the same restraint data for consensus analysis of protein NMR structures and the underlying restraint data.

Solution NMR structure of the helicase associated domain BVU_0683(627-691) from Bacteroides vulgatus provides first structural coverage for protein domain family PF03457 and indicates domain binding to DNA

A high-quality NMR structure of the helicase associated (HA) domain comprising residues 627-691 of the 753-residue protein BVU_0683 from Bacteroides vulgatus exhibits an all α-helical fold. The structure presented here is the first representative for the large protein domain family PF03457 (currently 742 members) of HA domains. Comparison with structurally similar proteins supports the hypothesis that HA domains bind to DNA and that binding specificity varies greatly within the family of HA domains constituting PF03457.

Principles for designing ideal protein structures

Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features--for example kinked α-helices, bulged β-strands, strained loops and buried polar groups--that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.

Solution NMR and X-ray crystal structures of Pseudomonas syringae Pspto_3016 from protein domain family PF04237 (DUF419) adopt a "double wing" DNA binding motif

The protein Pspto_3016 is a 117-residue member of the protein domain family PF04237 (DUF419), which is to date a functionally uncharacterized family of proteins. In this report, we describe the structure of Pspto_3016 from Pseudomonas syringae solved by both solution NMR and X-ray crystallography at 2.5 Å resolution. In both cases, the structure of Pspto_3016 adopts a "double wing" α/β sandwich fold similar to that of protein YjbR from Escherichia coli and to the C-terminal DNA binding domain of the MotA transcription factor (MotCF) from T4 bacteriophage, along with other uncharacterized proteins. Pspto_3016 was selected by the Protein Structure Initiative of the National Institutes of Health and the Northeast Structural Genomics Consortium (NESG ID PsR293).

A new algorithm for reliable and general NMR resonance assignment

The new FLYA automated resonance assignment algorithm determines NMR chemical shift assignments on the basis of peak lists from any combination of multidimensional through-bond or through-space NMR experiments for proteins. Backbone and side-chain assignments can be determined. All experimental data are used simultaneously, thereby exploiting optimally the redundancy present in the input peak lists and circumventing potential pitfalls of assignment strategies in which results obtained in a given step remain fixed input data for subsequent steps. Instead of prescribing a specific assignment strategy, the FLYA resonance assignment algorithm requires only experimental peak lists and the primary structure of the protein, from which the peaks expected in a given spectrum can be generated by applying a set of rules, defined in a straightforward way by specifying through-bond or through-space magnetization transfer pathways. The algorithm determines the resonance assignment by finding an optimal mapping between the set of expected peaks that are assigned by definition but have unknown positions and the set of measured peaks in the input peak lists that are initially unassigned but have a known position in the spectrum. Using peak lists obtained by purely automated peak picking from the experimental spectra of three proteins, FLYA assigned correctly 96-99% of the backbone and 90-91% of all resonances that could be assigned manually. Systematic studies quantified the impact of various factors on the assignment accuracy, namely the extent of missing real peaks and the amount of additional artifact peaks in the input peak lists, as well as the accuracy of the peak positions. Comparing the resonance assignments from FLYA with those obtained from two other existing algorithms showed that using identical experimental input data these other algorithms yielded significantly (40-142%) more erroneous assignments than FLYA. The FLYA resonance assignment algorithm thus has the reliability and flexibility to replace most manual and semi-automatic assignment procedures for NMR studies of proteins.

Solution NMR structures reveal a distinct architecture and provide first structures for protein domain family PF04536

The protein family (Pfam) PF04536 is a broadly conserved domain family of unknown function (DUF477), with more than 1,350 members in prokaryotic and eukaryotic proteins. High-quality NMR structures of the N-terminal domain comprising residues 41-180 of the 684-residue protein CG2496 from Corynebacterium glutamicum and the N-terminal domain comprising residues 35-182 of the 435-residue protein PG0361 from Porphyromonas gingivalis both exhibit an α/β fold comprised of a four-stranded β-sheet, three α-helices packed against one side of the sheet, and a fourth α-helix attached to the other side. In spite of low sequence similarity (18%) assessed by structure-based sequence alignment, the two structures are globally quite similar. However, moderate structural differences are observed for the relative orientation of two of the four helices. Comparison with known protein structures reveals that the α/β architecture of CG2496(41-180) and PG0361(35-182) has previously not been characterized. Moreover, calculation of surface charge potential and identification of surface clefts indicate that the two domains very likely have different functions.

Comprehensive automation for NMR structure determination of proteins

This chapter gives an overview of automated protein structure determination by nuclear magnetic resonance (NMR) with the UNIO protocol that enables high to full automation of all NMR data analysis steps involved. Four established algorithms, namely, the MATCH algorithm for sequence-specific resonance assignment, the ASCAN algorithm for side-chain resonance assignment, the CANDID algorithm for NOE assignment, and the ATNOS algorithm for signal identification in NMR spectra, are assembled into three principal UNIO NMR data analysis components (MATCH, ATNOS/ASCAN, and ATNOS/CANDID) that are accessed thanks to a particularly intuitive and flexible, yet powerful graphical user interface (GUI). UNIO is designed to work independently or in association with other NMR software. The principal data analysis components for sequence-specific backbone, side-chain and NOE assignment may be run separately or out of sequence. User-intervention at individual stages is encouraged and facilitated by graphical tools included for the preparation, analysis, validation, and subsequent presentation of the NMR structure.

A software framework for analysing solid-state MAS NMR data

Solid-state magic-angle-spinning (MAS) NMR of proteins has undergone many rapid methodological developments in recent years, enabling detailed studies of protein structure, function and dynamics. Software development, however, has not kept pace with these advances and data analysis is mostly performed using tools developed for solution NMR which do not directly address solid-state specific issues. Here we present additions to the CcpNmr Analysis software package which enable easier identification of spinning side bands, straightforward analysis of double quantum spectra, automatic consideration of non-uniform labelling schemes, as well as extension of other existing features to the needs of solid-state MAS data. To underpin this, we have updated and extended the CCPN data model and experiment descriptions to include transfer types and nomenclature appropriate for solid-state NMR experiments, as well as a set of experiment prototypes covering the experiments commonly employed by solid-sate MAS protein NMR spectroscopists. This work not only improves solid-state MAS NMR data analysis but provides a platform for anyone who uses the CCPN data model for programming, data transfer, or data archival involving solid-state MAS NMR data.

Bayesian estimation of NMR restraint potential and weight: a validation on a representative set of protein structures

The classical procedure for nuclear magnetic resonance structure calculation allocates empirical distance ranges and uses historical values for weighting factors. However, Bayesian analysis suggests that there are more optimal choices for potential shape (bounds-free log-harmonic shape) and restraints weights. We compare the classical protocol with the Bayesian approach for more than 300 protein structures. We analyze the conformation similarity to the corresponding X-ray crystal structure, the distribution of the conformations around their average, and independent validation criteria. On average, the log-harmonic potential reduces the difference to the X-ray crystal structure. If the log-harmonic potential is used, the constant weighting tightens the distribution around the average conformation, with respect to the distributions obtained with Bayesian weighting. Conversely, the structure quality is improved by the Bayesian weighting over the classical procedure, whereas constant weighting worsens some criteria. The quality improvement obtained with the log-harmonic potential coupled to Bayesian weighting validates this approach on a representative set of protein structures.

Binding site identification and structure determination of protein-ligand complexes by NMR a semiautomated approach

Over the last 15 years, the role of NMR spectroscopy in the lead identification and optimization stages of pharmaceutical drug discovery has steadily increased. NMR occupies a unique niche in the biophysical analysis of drug-like compounds because of its ability to identify binding sites, affinities, and ligand poses at the level of individual amino acids without necessarily solving the structure of the protein-ligand complex. However, it can also provide structures of flexible proteins and low-affinity (K(d)>10(-6)M) complexes, which often fail to crystallize. This chapter emphasizes a throughput-focused protocol that aims to identify practical aspects of binding site characterization, automated and semiautomated NMR assignment methods, and structure determination of protein-ligand complexes by NMR.

Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of β1 immunoglobulin binding domain of protein G (GB1)

Magic-angle spinning solid-state NMR (MAS SSNMR) represents a fast developing experimental technique with great potential to provide structural and dynamics information for proteins not amenable to other methods. However, few automated analysis tools are currently available for MAS SSNMR. We present a methodology for automating protein resonance assignments of MAS SSNMR spectral data and its application to experimental peak lists of the β1 immunoglobulin binding domain of protein G (GB1) derived from a uniformly ¹³C- and ¹⁵N-labeled sample. This application to the 56 amino acid GB1 produced an overall 84.1% assignment of the N, CO, CA, and CB resonances with no errors using peak lists from NCACX 3D, CANcoCA 3D, and CANCOCX 4D experiments. This proof of concept demonstrates the tractability of this problem.

SAIL – stereo-array isotope labeling

Optimal stereospecific and regiospecific labeling of proteins with stable isotopes enhances the nuclear magnetic resonance (NMR) method for the determination of the three-dimensional protein structures in solution. Stereo-array isotope labeling (SAIL) offers sharpened lines, spectral simplification without loss of information and the ability to rapidly collect and automatically evaluate the structural restraints required to solve a high-quality solution structure for proteins up to twice as large as before. This review gives an overview of stable isotope labeling methods for NMR spectroscopy with proteins and provides an in-depth treatment of the SAIL technology.

DsrR, a novel IscA-like protein lacking iron- and Fe-S-binding functions, involved in the regulation of sulfur oxidation in Allochromatium vinosum

In the purple sulfur bacterium Allochromatium vinosum, the reverse-acting dissimilatory sulfite reductase (DsrAB) is the key enzyme responsible for the oxidation of intracellular sulfur globules. The genes dsrAB are the first and the gene dsrR is the penultimate of the 15 genes of the dsr operon in A. vinosum. Genes homologous to dsrR occur in a number of other environmentally important sulfur-oxidizing bacteria utilizing Dsr proteins. DsrR exhibits sequence similarities to A-type scaffolds, like IscA, that partake in the maturation of protein-bound iron-sulfur clusters. We used nuclear magnetic resonance (NMR) spectroscopy to solve the solution structure of DsrR and to show that the protein is indeed structurally highly similar to A-type scaffolds. However, DsrR does not retain the Fe-S- or the iron-binding ability of these proteins, which is due to the lack of all three highly conserved cysteine residues of IscA-like scaffolds. Taken together, these findings suggest a common function for DsrR and IscA-like proteins different from direct participation in iron-sulfur cluster maturation. An A. vinosum DeltadsrR deletion strain showed a significantly reduced sulfur oxidation rate that was fully restored upon complementation with dsrR in trans. Immunoblot analyses revealed a reduced level of DsrE and DsrL in the DeltadsrR strain. These proteins are absolutely essential for sulfur oxidation. Transcriptional and translational gene fusion experiments suggested the participation of DsrR in the posttranscriptional control of the dsr operon, similar to the alternative function of cyanobacterial IscA as part of the sense and/or response cascade set into action upon iron limitation.

Automated protein NMR structure determination in solution

The main drawback of protein NMR spectroscopy today is still the extensive amount of time required for solving a single structure. The main bottleneck in this respect is the manual evaluation of the experimental spectra. A clear solution to this challenge is the development of automated methods for this purpose. At the current stage of development, this goal has been almost or in a few cases fully reached for favorable cases such as well-behaved, stably folding smaller proteins below the 25 kDa range. For larger and/or more difficult molecules, the input of a human expert is still required. However, even here, automated routines will substantially speed up the structure determination process. In this report, we will summarize recent developments in this field and especially emphasize practical aspects important for a successful automated protein structure determination in solution. An important aspect closely related to structure determination is structure validation. Therefore, we devote a section to automated approaches for this topic.

Slight mistuning of a cryogenic probe significantly perturbs the water 1H precession frequency

A shift of the water proton precession frequency is described that can introduce errors in chemical shifts derived using the water signal as the chemical shift reference. This shift, f(s), arises as a consequence of radiation damping when the water proton and detector circuit resonance frequencies differ. Herein it is shown that experimental values of f(s), measured as a function of detector circuit tuning offset for 500 and 900 MHz cryogenic probes, are in good agreement with theory. Of importance is the fact that even a small degree of mistuning, which does not significantly impact the performance of a pulse sequence, introduces chemical shift errors of +/-0.03 ppm, that negatively impact many types of experiments. A simple remedy that attenuates the frequency shift is presented.

Advances in Nuclear Magnetic Resonance for Drug Discovery

BACKGROUND: Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. OBJECTIVE/METHOD: A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR. CONCLUSION: NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, in-cell imaging techniques, and the expansion of NMR amenable targets.

Clean absorption mode NMR data acquisition based on time-proportional phase incrementation

Clean absorption mode NMR data acquisition is presented based on mirrored time domain sampling and widely used time-proportional phase incrementation (TPPI) for quadrature detection. The resulting NMR spectra are devoid of dispersive frequency domain peak components. Those peak components exacerbate peak identification and shift peak maxima, and thus impede automated spectral analysis. The new approach is also of unique value for obtaining clean absorption mode reduced-dimensionality projection NMR spectra, which can rapidly provide high-dimensional spectral information for high-throughput NMR structure determination.

Unique opportunities for NMR methods in structural genomics

This Perspective, arising from a workshop held in July 2008 in Buffalo NY, provides an overview of the role NMR has played in the United States Protein Structure Initiative (PSI), and a vision of how NMR will contribute to the forthcoming PSI-Biology program. NMR has contributed in key ways to structure production by the PSI, and new methods have been developed which are impacting the broader protein NMR community.

Automated protein structure calculation from NMR data

Current software is almost at the stage to permit completely automatic structure determination of small proteins of <15 kDa, from NMR spectra to structure validation with minimal user interaction. This goal is welcome, as it makes structure calculation more objective and therefore more easily validated, without any loss in the quality of the structures generated. Moreover, it releases expert spectroscopists to carry out research that cannot be automated. It should not take much further effort to extend automation to ca 20 kDa. However, there are technological barriers to further automation, of which the biggest are identified as: routines for peak picking; adoption and sharing of a common framework for structure calculation, including the assembly of an automated and trusted package for structure validation; and sample preparation, particularly for larger proteins. These barriers should be the main target for development of methodology for protein structure determination, particularly by structural genomics consortia.

Structure of the N terminus of a nonmuscle alpha-tropomyosin in complex with the C terminus: implications for actin binding

Tropomyosin is a coiled-coil actin binding protein that stabilizes the filament, protects it from severing, and cooperatively regulates actin's interaction with myosin. Depending on the first coding exon, tropomyosins are low molecular weight (LMW), found in the cytoskeleton and predominant in transformed cells, or high molecular weight (HMW), found in muscle and nonmuscle cells. The N- and C-terminal ends form a complex that allows tropomyosin to associate N terminus-to-C terminus along the actin filament. We determined the structure of a LMW tropomyosin N-terminal model peptide complexed with a smooth/nonmuscle tropomyosin C-terminal peptide. Using NMR and circular dichroism we showed that both ends become more helical upon complex formation but that the C-terminal peptide is partially unfolded at 20 degrees C. The first five residues of the N terminus that are disordered in the free peptide are more helical and are part of the overlap complex. NMR data indicate residues 2-17 bind to the C terminus in the complex. The data support a model for the LMW overlap complex that is homologous to the striated muscle tropomyosin complex in which the ends are oriented in parallel N terminus-to-C terminus with the plane of the N-terminal coiled coil perpendicular to the plane of the C terminus. The main difference is that the overlap spans 16 residues in the LMW tropomyosin complex compared to 11 residues in the HMW striated muscle overlap complex. We discuss the relevance of a stable but dynamic intermolecular junction for high-affinity binding to actin.

Protein chaperones Q8ZP25_SALTY from Salmonella typhimurium and HYAE_ECOLI from Escherichia coli exhibit thioredoxin-like structures despite lack of canonical thioredoxin active site sequence motif

The structure of the 142-residue protein Q8ZP25_SALTY encoded in the genome of Salmonella typhimurium LT2 was determined independently by NMR and X-ray crystallography, and the structure of the 140-residue protein HYAE_ECOLI encoded in the genome of Escherichia coli was determined by NMR. The two proteins belong to Pfam (Finn et al. 34:D247-D251, 2006) PF07449, which currently comprises 50 members, and belongs itself to the 'thioredoxin-like clan'. However, protein HYAE_ECOLI and the other proteins of Pfam PF07449 do not contain the canonical Cys-X-X-Cys active site sequence motif of thioredoxin. Protein HYAE_ECOLI was previously classified as a [NiFe] hydrogenase-1 specific chaperone interacting with the twin-arginine translocation (Tat) signal peptide. The structures presented here exhibit the expected thioredoxin-like fold and support the view that members of Pfam family PF07449 specifically interact with Tat signal peptides.

Structural biology by NMR: structure, dynamics, and interactions

The function of bio-macromolecules is determined by both their 3D structure and conformational dynamics. These molecules are inherently flexible systems displaying a broad range of dynamics on time-scales from picoseconds to seconds. Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as the method of choice for studying both protein structure and dynamics in solution. Typically, NMR experiments are sensitive both to structural features and to dynamics, and hence the measured data contain information on both. Despite major progress in both experimental approaches and computational methods, obtaining a consistent view of structure and dynamics from experimental NMR data remains a challenge. Molecular dynamics simulations have emerged as an indispensable tool in the analysis of NMR data.

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.

Automated NMR assignment of protein side chain resonances using automated projection spectroscopy (APSY)

This paper describes an automated method for sequence-specific NMR assignment of the aliphatic resonances of protein side chains in small- and medium-sized globular proteins in aqueous solution. The method requires the recording of a five-dimensional (5D) automated projection spectroscopy (APSY-) NMR experiment and the subsequent analysis of the APSY peak list with the algorithm ALASCA (Algorithm for local and linear assignment of side chains from APSY data). The 5D APSY-HC(CC-TOCSY)CONH experiment yields 5D chemical shift correlations of aliphatic side chain C-H moieties with the backbone atoms H(N), N, and C'. A simultaneous variation of the TOCSY mixing times and the projection angles in this APSY-type TOCSY experiment gives access to all aliphatic C-H moieties in the 20 proteinogenic amino acids. The correlation peak list resulting from the 5D APSY-HC(CC-TOCSY)CONH experiment together with the backbone assignment of the protein under study is the sole input for the algorithm ALASCA that assigns carbon and proton resonances of protein side chains. The algorithm is described, and it is shown that the aliphatic parts of 17 of the 20 common amino acid side chains are assigned unambiguously, whereas the remaining three amino acids are assigned with a certainty of above 95%. The overall feasibility of the approach is demonstrated with the globular 116-residue protein TM1290, for which reference assignments are known. For this protein, 97% of the expected side chain carbon atoms and 87% of the expected side chain protons were detected with the 5D APSY-HC(CC-TOCSY)CONH experiment in 24 h of spectrometer time, and all these resonances were correctly assigned by ALASCA. Based on the experience with TM1290, we expect that the approach presented in this work is routinely applicable to globular proteins with sizes up to at least 120 amino acids.

Allochromatium vinosum DsrC: solution-state NMR structure, redox properties, and interaction with DsrEFH, a protein essential for purple sulfur bacterial sulfur oxidation

Sequenced genomes of dissimilatory sulfur-oxidizing and sulfate-reducing bacteria containing genes coding for DsrAB, the enzyme dissimilatory sulfite reductase, inevitably also contain the gene coding for the 12-kDa DsrC protein. DsrC is thought to have a yet unidentified role associated with the activity of DsrAB. Here we report the solution structure of DsrC from the sulfur-oxidizing purple sulfur bacterium Allochromatium vinosum determined with NMR spectroscopy in reducing conditions, and we describe the redox behavior of two conserved cysteine residues upon transfer to an oxidizing environment. In reducing conditions, the DsrC structure is disordered in the highly conserved carboxy-terminus. We present multiple lines of evidence that, in oxidizing conditions, a strictly conserved cysteine (Cys111) at the penultimate position in the sequence forms an intramolecular disulfide bond with Cys100, which is conserved in DsrC in all organisms with DsrAB. While an intermolecular Cys111-Cys111 disulfide-bonded dimer is rapidly formed under oxidizing conditions, the intramolecularly disulfide-bonded species (Cys100-Cys111) is the thermodynamically stable form of the protein under these conditions. Treatment of the disulfidic forms with reducing agent regenerates the monomeric species that was structurally characterized. Using a band-shift technique under nondenaturing conditions, we obtained evidence for the interaction of DsrC with heterohexameric DsrEFH, a protein encoded in the same operon. Mutation of Cys100 to serine prevented formation of the DsrC species assigned as an intramolecular disulfide in oxidizing conditions, while still allowing formation of the intermolecular Cys111-Cys111 dimer. In the reduced form, this mutant protein still interacted with DsrEFH. This was not the case for the Cys111Ser and Cys100Ser/Cys111Ser mutants, both of which also did not form protein dimers. Our observations highlight the central importance of the carboxy-terminal DsrC cysteine residues and are consistent with a role as a sulfur-substrate binding/transferring protein, as well as with an electron-transfer function via thiol-disulfide interchanges.

The war of tools: how can NMR spectroscopists detect errors in their structures?

Protein structure determination by NMR methods has started in the mid-eighties and has been growing steadily since then. Ca. 14% of the protein structures deposited in the PDB have been solved by NMR. The evaluation of the quality of NMR structures however is still lacking a well-established practice. In this work, we examined various tools for the assessment of structural quality to ascertain the extent to which these tools could be applied to detect flaws in NMR structures. In particular, we investigated the variation in the scores assigned by these programs as a function of the deviation of the structures induced by errors in assignments or in the upper distance limits used. These perturbations did not distort radically the protein fold, but resulted in backbone RMS deviations up to 3 A, which is in line with errors highlighted in the available literature. We found that it is quite difficult to discriminate the structures perturbed because of misassignments from the original ones, also because the spread in score over the conformers of the original bundle is relatively large. varphi-psi distributions and normality scores related to the backbone conformation and to the distribution of side-chain dihedral angles are the most sensitive indicators of flaws.

An automated assignment-free Bayesian approach for accurately identifying proton contacts from NOESY data

The identification of proton contacts from NOE spectra remains the major bottleneck in NMR protein structure calculations. We describe an automated assignment-free system for deriving proton contact probabilities from NOESY peak lists that can be viewed as a quantitative extension of manual assignment techniques. Rather than assigning contacts to NOESY crosspeaks, a rigorous Bayesian methodology is used to transform initial proton contact probabilities derived from a set of 2992 protein structures into posterior probabilities using the observed crosspeaks as evidence. Given a target protein, the Bayesian approach is used to derive probabilities for all possible proton contacts. We evaluated the accuracy of this approach at predicting proton contacts on 60 (15)N separated NOESY and (13)C separated NOESY datasets simulated from experimentally determined NMR structures and compared it to CYANA, an established method for proton constraint assignment. On average, at the highest confidence level, our method accurately identifies 3.16/3.17 long range contacts per residue and 12.11/12.18 interresidue proton contacts per residue. These accuracies represent a significant increase over the performance of CYANA on the same data set. On a difficult real dataset that is publicly available, the coverage is lower but our method retains its advantage in accuracy over CANDID/CYANA. The algorithm is publicly available via the Protinfo NMR webserver http://protinfo.compbio.washington.edu/protinfo_nmr .

Fully automated structure determinations of the Fes SH2 domain using different sets of NMR spectra

The recently introduced fully automated protein NMR structure determination algorithm (FLYA) yields, without any human intervention, a three-dimensional (3D) protein structure starting from a set of two- and three-dimensional NMR spectra. This paper investigates the influence of reduced sets of experimental spectra on the quality of NMR structures obtained with FLYA. In a case study using the Src homology domain 2 from the human feline sarcoma oncogene Fes (Fes SH2), five reduced data sets selected from the full set of 13 three-dimensional spectra of the previously determined conventional structure were used to calculate the protein structure. Three reduced data sets utilized only CBCA(CO)NH and CBCANH for the backbone assignments and two data sets used only CBCA(CO)NH. All, some, or none of the five original side-chain assignment spectra were used. Results were compared with those of a FLYA calculation for the complete set of spectra and those of the conventionally determined structure. In four of the five cases tested, the three-dimensional structures deviated by less than 1.3 A in backbone RMSD from the conventionally determined Fes SH2 reference structure, showing that the FLYA algorithm is remarkably stable and accurate when used with reduced sets of input spectra.