Increased reliability of nuclear magnetic resonance protein structures by consensus structure bundles

Improved methodology for protein NMR structure calculation using hydrogen bond restraints and ANSURR validation: The SH2 domain of SH2B1

Protein structures calculated using NMR data are less accurate and less well-defined than they could be. Here we use the program ANSURR to show that this deficiency is at least in part due to a lack of hydrogen bond restraints. We describe a protocol to introduce hydrogen bond restraints into the structure calculation of the SH2 domain from SH2B1 in a systematic and transparent way and show that the structures generated are more accurate and better defined as a result. We also show that ANSURR can be used as a guide to know when the structure calculation is good enough to stop.

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.

Core packing of well‐defined X‐ray and NMR structures is the same

Numerous studies have investigated the differences and similarities between protein structures determined by solution NMR spectroscopy and those determined by X-ray crystallography. A fundamental question is whether any observed differences are due to differing methodologies or to differences in the behavior of proteins in solution versus in the crystalline state. Here, we compare the properties of the hydrophobic cores of high-resolution protein crystal structures and those in NMR structures, determined using increasing numbers and types of restraints. Prior studies have reported that many NMR structures have denser cores compared with those of high-resolution X-ray crystal structures. Our current work investigates this result in more detail and finds that these NMR structures tend to violate basic features of protein stereochemistry, such as small non-bonded atomic overlaps and few Ramachandran and sidechain dihedral angle outliers. We find that NMR structures solved with more restraints, and which do not significantly violate stereochemistry, have hydrophobic cores that have a similar size and packing fraction as their counterparts determined by X-ray crystallography at high resolution. These results lead us to conclude that, at least regarding the core packing properties, high-quality structures determined by NMR and X-ray crystallography are the same, and the differences reported earlier are most likely a consequence of methodology, rather than fundamental differences between the protein in the two different environments.

Solution structure of Gaussia Luciferase with five disulfide bonds and identification of a putative coelenterazine binding cavity by heteronuclear NMR

Gaussia luciferase (GLuc) is a small luciferase (18.2 kDa; 168 residues) and is thus attracting much attention as a reporter protein, but the lack of structural information is hampering further application. Here, we report the first solution structure of a fully active, recombinant GLuc determined by heteronuclear multidimensional NMR. We obtained a natively folded GLuc by bacterial expression and efficient refolding using a Solubility Enhancement Petide (SEP) tag. Almost perfect assignments of GLuc’s ¹H, ¹³C and ¹⁵N backbone signals were obtained. GLuc structure was determined using CYANA, which automatically identified over 2500 NOEs of which > 570 were long-range. GLuc is an all-alpha-helix protein made of nine helices. The region spanning residues 10–18, 36–81, 96–145 and containing eight out of the nine helices was determined with a C_α-atom RMSD of 1.39 Å ± 0.39 Å. The structure of GLuc is novel and unique. Two homologous sequential repeats form two anti-parallel bundles made by 4 helices and tied together by three disulfide bonds. The N-terminal helix 1 is grabbed by these 4 helices. Further, we found a hydrophobic cavity where several residues responsible for bioluminescence were identified in previous mutational studies, and we thus hypothesize that this is a catalytic cavity, where the hydrophobic coelenterazine binds and the bioluminescence reaction takes place.

Structural Diversity and Dynamics of Human Three-Finger Proteins Acting on Nicotinic Acetylcholine Receptors

Ly-6/uPAR or three-finger proteins (TFPs) contain a disulfide-stabilized β-structural core and three protruding loops (fingers). In mammals, TFPs have been found in epithelium and the nervous, endocrine, reproductive, and immune systems. Here, using heteronuclear NMR, we determined the three-dimensional (3D) structure and backbone dynamics of the epithelial secreted protein SLURP-1 and soluble domains of GPI-anchored TFPs from the brain (Lynx2, Lypd6, Lypd6b) acting on nicotinic acetylcholine receptors (nAChRs). Results were compared with the data about human TFPs Lynx1 and SLURP-2 and snake α-neurotoxins WTX and NTII. Two different topologies of the β-structure were revealed: one large antiparallel β-sheet in Lypd6 and Lypd6b, and two β-sheets in other proteins. α-Helical segments were found in the loops I/III of Lynx2, Lypd6, and Lypd6b. Differences in the surface distribution of charged and hydrophobic groups indicated significant differences in a mode of TFPs/nAChR interactions. TFPs showed significant conformational plasticity: the loops were highly mobile at picosecond-nanosecond timescale, while the β-structural regions demonstrated microsecond-millisecond motions. SLURP-1 had the largest plasticity and characterized by the unordered loops II/III and cis-trans isomerization of the Tyr39-Pro40 bond. In conclusion, plasticity could be an important feature of TFPs adapting their structures for optimal interaction with the different conformational states of nAChRs.

ARIAweb: a server for automated NMR structure calculation

Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.

Residual Dipolar Couplings for Resolving Cysteine Bridges in Disulfide-Rich Peptides

Disulfide bridges in proteins are formed by the oxidation of pairs of cysteine residues. These cross-links play a critical role in stabilizing the 3D-structure of small disulfide rich polypeptides such as hormones and venom toxins. The arrangement of the multiple disulfide bonds directs the peptide fold into distinct structural motifs that have evolved for resistance against biochemical and physical insults. These structural scaffolds have, therefore, proven to be very attractive in bioengineering efforts to develop novel biologics with applications in health and agriculture. Structural characterization of small disulfide rich peptides (DRPs) presents unique challenges when using commonly applied biophysical methods. NMR is the most commonly used method for studying such molecules, where the relatively small size of these molecules results in highly precise structural ensembles defined by a large number of distance and dihedral angle restraints per amino acid. However, in NMR the sulfur atoms that are involved in three of the five dihedral angles in a disulfide bond cannot be readily measured. Given the central role of disulfide bonds in the structure of these molecules, it is unclear what the inherent resolution of such NMR structures is when using traditional NMR methods. Here, we use an extensive set of long-range residual dipolar couplings (RDCs) to assess the resolution of the NMR structure of a disulfide-rich peptide. We find that structures based primarily on NOEs, yield ensembles that are equivalent to a crystallographic resolution of 2-3 Å in resolution, and that incorporation of RDCs reduces this to ~1-1.5 Å resolution. At this resolution the sidechain of ordered amino acids can be defined accurately, allowing the geometry of the cysteine bridges to be better defined, and allowing for disulfide-bond connectivities to be determined with high confidence. The observed improvements in resolution when using RDCs is remarkable considering the small size of these peptides.

Structural and functional dissection of the DH and PH domains of oncogenic Bcr-Abl tyrosine kinase

The two isoforms of the Bcr-Abl tyrosine kinase, p210 and p190, are associated with different leukemias and have a dramatically different signaling network, despite similar kinase activity. To provide a molecular rationale for these observations, we study the Dbl-homology (DH) and Pleckstrin-homology (PH) domains of Bcr-Abl p210, which constitute the only structural differences to p190. Here we report high-resolution structures of the DH and PH domains and characterize conformations of the DH-PH unit in solution. Our structural and functional analyses show no evidence that the DH domain acts as a guanine nucleotide exchange factor, whereas the PH domain binds to various phosphatidylinositol-phosphates. PH-domain mutants alter subcellular localization and result in decreased interactions with p210-selective interaction partners. Hence, the PH domain, but not the DH domain, plays an important role in the formation of the differential p210 and p190 Bcr-Abl signaling networks.

NMR-based automated protein structure determination

NMR spectra analysis for protein structure determination can now in many cases be performed by automated computational methods. This overview of the computational methods for NMR protein structure analysis presents recent automated methods for signal identification in multidimensional NMR spectra, sequence-specific resonance assignment, collection of conformational restraints, and structure calculation, as implemented in the CYANA software package. These algorithms are sufficiently reliable and integrated into one software package to enable the fully automated structure determination of proteins starting from NMR spectra without manual interventions or corrections at intermediate steps, with an accuracy of 1-2 Å backbone RMSD in comparison with manually solved reference structures.

Structural and Functional Consequences of Connexin 36 (Cx36) Interaction with Calmodulin

Functional plasticity of neuronal gap junctions involves the interaction of the neuronal connexin36 with calcium/calmodulin-dependent kinase II (CaMKII). The important relationship between Cx36 and CaMKII must also be considered in the context of another protein partner, Ca2+ loaded calmodulin, binding an overlapping site in the carboxy-terminus of Cx36. We demonstrate that CaM and CaMKII binding to Cx36 is calcium-dependent, with Cx36 able to engage with CaM outside of the gap junction plaque. Furthermore, Ca2+ loaded calmodulin activates Cx36 channels, which is different to other connexins. The NMR solution structure demonstrates that CaM binds Cx36 in its characteristic compact state with major hydrophobic contributions arising from W277 at anchor position 1 and V284 at position 8 of Cx36. Our results establish Cx36 as a hub binding Ca2+ loaded CaM and they identify this interaction as a critical step with implications for functions preceding the initiation of CaMKII mediated plasticity at electrical synapses.

Mechanism of TAp73 inhibition by ΔNp63 and structural basis of p63/p73 hetero-tetramerization

Members of the p53 tumor-suppressor family are expressed as multiple isoforms. Isoforms with an N-terminal transactivation domain are transcriptionally active, while those ones lacking this domain often inhibit the transcriptional activity of other family members. In squamous cell carcinomas, the high expression level of ΔNp63α inhibits the tumor-suppressor function of TAp73β. This can in principle be due to blocking of the promoter or by direct interaction between both proteins. p63 and p73 can hetero-oligomerize through their tetramerization domains and a hetero-tetramer consisting of two p63 and two p73 molecules is thermodynamically more stable than both homo-tetramers. Here we show that cells expressing both p63 and p73 exist in mouse epidermis and hair follicle and that hetero-tetramer complexes can be detected by immunoprecipitation in differentiating keratinocytes. Through structure determination of the hetero-tetramer, we reveal why this hetero-tetramer is the thermodynamically preferred species. We have created mutants that exclusively form either hetero-tetramers or homo-tetramers, allowing to investigate the function of these p63/p73 hetero-tetramers. Using these tools, we show that inhibition of TAp73β in squamous cell carcinomas is due to promoter squelching and not direct interaction.

Atomic-resolution structure of a disease-relevant Aβ(1-42) amyloid fibril

Amyloid-β (Aβ) is present in humans as a 39- to 42-amino acid residue metabolic product of the amyloid precursor protein. Although the two predominant forms, Aβ(1-40) and Aβ(1-42), differ in only two residues, they display different biophysical, biological, and clinical behavior. Aβ(1-42) is the more neurotoxic species, aggregates much faster, and dominates in senile plaque of Alzheimer's disease (AD) patients. Although small Aβ oligomers are believed to be the neurotoxic species, Aβ amyloid fibrils are, because of their presence in plaques, a pathological hallmark of AD and appear to play an important role in disease progression through cell-to-cell transmissibility. Here, we solved the 3D structure of a disease-relevant Aβ(1-42) fibril polymorph, combining data from solid-state NMR spectroscopy and mass-per-length measurements from EM. The 3D structure is composed of two molecules per fibril layer, with residues 15-42 forming a double-horseshoe-like cross-β-sheet entity with maximally buried hydrophobic side chains. Residues 1-14 are partially ordered and in a β-strand conformation, but do not display unambiguous distance restraints to the remainder of the core structure.

Probabilistic validation of protein NMR chemical shift assignments

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data . ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/.

A consensus on protein structure accuracy in NMR?

The precision of an NMR structure may be manipulated by calculation parameters such as calibration factors. Its accuracy is, however, a different issue. In this issue of Structure, Buchner and Güntert present "consensus structure bundles," where precision analysis allows estimation of accuracy.

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.

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.

Combined automated NOE assignment and structure calculation with CYANA

The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but was so far not described in full detail. In this paper we present a complete description of the CYANA implementation of automated NOESY assignment, which differs extensively from its predecessor CANDID by the use of a consistent probabilistic treatment, and we discuss its performance in the second round of the critical assessment of structure determination by NMR.

Improved reliability, accuracy and quality in automated NMR structure calculation with ARIA

In biological NMR, assignment of NOE cross-peaks and calculation of atomic conformations are critical steps in the determination of reliable high-resolution structures. ARIA is an automated approach that performs NOE assignment and structure calculation in a concomitant manner in an iterative procedure. The log-harmonic shape for distance restraint potential and the Bayesian weighting of distance restraints, recently introduced in ARIA, were shown to significantly improve the quality and the accuracy of determined structures. In this paper, we propose two modifications of the ARIA protocol: (1) the softening of the force field together with adapted hydrogen radii, which is meaningful in the context of the log-harmonic potential with Bayesian weighting, (2) a procedure that automatically adjusts the violation tolerance used in the selection of active restraints, based on the fitting of the structure to the input data sets. The new ARIA protocols were fine-tuned on a set of eight protein targets from the CASD-NMR initiative. As a result, the convergence problems previously observed for some targets was resolved and the obtained structures exhibited better quality. In addition, the new ARIA protocols were applied for the structure calculation of ten new CASD-NMR targets in a blind fashion, i.e. without knowing the actual solution. Even though optimisation of parameters and pre-filtering of unrefined NOE peak lists were necessary for half of the targets, ARIA consistently and reliably determined very precise and highly accurate structures for all cases. In the context of integrative structural biology, an increasing number of experimental methods are used that produce distance data for the determination of 3D structures of macromolecules, stressing the importance of methods that successfully make use of ambiguous and noisy distance data.

Analysis of the structural quality of the CASD-NMR 2013 entries

We performed a comprehensive structure validation of both automated and manually generated structures of the 10 targets of the CASD-NMR-2013 effort. We established that automated structure determination protocols are capable of reliably producing structures of comparable accuracy and quality to those generated by a skilled researcher, at least for small, single domain proteins such as the ten targets tested. The most robust results appear to be obtained when NOESY peak lists are used either as the primary input data or to augment chemical shift data without the need to manually filter such lists. A detailed analysis of the long-range NOE restraints generated by the different programs from the same data showed a surprisingly low degree of overlap. Additionally, we found that there was no significant correlation between the extent of the NOE restraint overlap and the accuracy of the structure. This result was surprising given the importance of NOE data in producing good quality structures. We suggest that this could be explained by the information redundancy present in NOEs between atoms contained within a fixed covalent network.