Quality assessment of protein NMR structures

Next generation technologies for protein structure determination: challenges and breakthroughs in plant biology applications

Advancements in structural biology have significantly deepened our understanding of plant proteins, which are central to critical biological functions such as photosynthesis, metabolism, signal transduction, and structural architechture. Gaining insights into their structures is crucial for unraveling their functions and mechanisms, which in turn has profound implications for agriculture, biotechnology, and environmental sustainability. Traditional methods in protein structural biology often fall short in addressing large protein assemblies and membrane proteins, and, in particular the dynamics and structural features of proteins in the native cellular context. This paper explores how next-generation technologies are transforming the field of plant protein structural biology, offering powerful tools to overcome longstanding obstacles and enabling remarkable scientific breakthroughs. Key technologies discussed include advanced X-ray crystallography, Cryo-Electron microscopy, Nuclear Magnetic Resonance spectroscopy, Cross-linking mass spectrometry, and Artificial Intelligence-driven approaches. These technologies are examined in terms of their challenges, innovations, and application with particular emphasis on their relevance to plant systems. Future directions in plant protein structural biology are also discussed. Although technical details are not covered in depth, readers are referred to the primary literature for more comprehensive information.

Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB restraint violation report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB Restraint Violation Report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

Comprehensive characterization of higher order structure changes in methionine oxidized monoclonal antibodies via NMR chemometric analysis and biophysical approaches

The higher order structure (HOS) of monoclonal antibodies (mAbs) is an important quality attribute with strong contribution to clinically relevant biological functions and drug safety. Due to the multi-faceted nature of HOS, the synergy of multiple complementary analytical approaches can substantially improve the understanding, accuracy, and resolution of HOS characterization. In this study, we applied one- and two-dimensional (1D and 2D) nuclear magnetic resonance (NMR) spectroscopy coupled with chemometric analysis, as well as circular dichroism (CD), differential scanning calorimetry (DSC), and fluorescence spectroscopy as orthogonal methods, to characterize the impact of methionine (Met) oxidation on the HOS of an IgG1 mAb. We used a forced degradation method involving concentration-dependent oxidation by peracetic acid, in which Met oxidation is site-specifically quantified by liquid chromatography-mass spectrometry. Conventional biophysical techniques report nuanced results, in which CD detects no change to the secondary structure and little change in the tertiary structure. Yet, DSC measurements show the destabilization of Fab and Fc domains due to Met oxidation. More importantly, our study demonstrates that 1D and 2D NMR and chemometric analysis can provide semi-quantitative analysis of chemical modifications and resolve localized conformational changes with high sensitivity. Furthermore, we leveraged a novel 15N-Met labeling technique of the antibody to directly observe structural perturbations at the oxidation sites. The NMR methods described here to probe HOS changes are highly reliable and practical in biopharmaceutical characterization.

G-quadruplex DNA: A Longer Story

G-quadruplexes (G4s) are distinctive four-stranded DNA or RNA structures found within cells that are thought to play functional roles in gene regulation and transcription, translation, recombination, and DNA damage/repair. While G4 structures can be uni-, bi-, or tetramolecular with respect to strands, folded unimolecular conformations are most significant in vivo. Unimolecular G4 can potentially form in sequences with runs of guanines interspersed with what will become loops in the folded structure: 5'G_xL_yG_xL_yG_xL_yG_x, where x is typically 2-4 and y is highly variable. Such sequences are highly conserved and specifically located in genomes. In the folded structure, guanines from each run combine to form planar tetrads with four hydrogen-bonded guanine bases; these tetrads stack on one another to produce four strand segments aligned in specific parallel or antiparallel orientations, connected by the loop sequences. Three types of loops (lateral, diagonal, or "propeller") have been identified. The stacked tetrads form a central cavity that features strong coordination sites for monovalent cations that stabilize the G4 structure, with potassium or sodium preferred. A single monomeric G4 typically forms from a sequence containing roughly 20-30 nucleotides. Such short sequences have been the primary focus of X-ray crystallographic or NMR studies that have produced high-resolution structures of a variety of monomeric G4 conformations. These structures are often used as the basis for drug design efforts to modulate G4 function.We believe that the focus on monomeric G4 structures formed by such short sequences is perhaps myopic. Such short sequences for structural studies are often arbitrarily selected and removed from their native genomic sequence context, and then are often changed from their native sequences by base substitutions or deletions intended to optimize the formation of a homogeneous G4 conformation. We believe instead that G-quadruplexes prefer company and that in a longer natural sequence context multiple adjacent G4 units can form to combine into more complex multimeric G4 structures with richer topographies than simple monomeric forms. Bioinformatic searches of the human genome show that longer sequences with the potential for forming multiple G4 units are common. Telomeric DNA, for example, has a single-stranded overhang of hundreds of nucleotides with the requisite repetitive sequence with the potential for formation of multiple G4s. Numerous extended promoter sequences have similar potentials for multimeric G4 formation. X-ray crystallography and NMR methods are challenged by these longer sequences (>30 nt), so other tools are needed to explore the possible multimeric G4 landscape. We have implemented an integrated structural biology approach to address this challenge. This approach integrates experimental biophysical results with atomic-level molecular modeling and molecular dynamics simulations that provide quantitatively testable model structures. In every long sequence we have studied so far, we found that multimeric G4 structures readily form, with a surprising diversity of structures dependent on the exact native sequence used. In some cases, stable hairpin duplexes form along with G4 units to provide an even richer landscape. This Account provides an overview of our approach and recent progress and provides a new perspective on the G-quadruplex folding landscape.

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.

AlphaFold Models of Small Proteins Rival the Accuracy of Solution NMR Structures

Recent advances in molecular modeling using deep learning have the potential to revolutionize the field of structural biology. In particular, AlphaFold has been observed to provide models of protein structures with accuracies rivaling medium-resolution X-ray crystal structures, and with excellent atomic coordinate matches to experimental protein NMR and cryo-electron microscopy structures. Here we assess the hypothesis that AlphaFold models of small, relatively rigid proteins have accuracies (based on comparison against experimental data) similar to experimental solution NMR structures. We selected six representative small proteins with structures determined by both NMR and X-ray crystallography, and modeled each of them using AlphaFold. Using several structure validation tools integrated under the Protein Structure Validation Software suite (PSVS), we then assessed how well these models fit to experimental NMR data, including NOESY peak lists (RPF-DP scores), comparisons between predicted rigidity and chemical shift data (ANSURR scores), and 15N-1H residual dipolar coupling data (RDC Q factors) analyzed by software tools integrated in the PSVS suite. Remarkably, the fits to NMR data for the protein structure models predicted with AlphaFold are generally similar, or better, than for the corresponding experimental NMR or X-ray crystal structures. Similar conclusions were reached in comparing AlphaFold2 predictions and NMR structures for three targets from the Critical Assessment of Protein Structure Prediction (CASP). These results contradict the widely held misperception that AlphaFold cannot accurately model solution NMR structures. They also document the value of PSVS for model vs. data assessment of protein NMR structures, and the potential for using AlphaFold models for guiding analysis of experimental NMR data and more generally in structural biology.

Assessment of prediction methods for protein structures determined by NMR in CASP14: Impact of AlphaFold2

NMR studies can provide unique information about protein conformations in solution. In CASP14, three reference structures provided by solution NMR methods were available (T1027, T1029, and T1055), as well as a fourth data set of NMR‐derived contacts for an integral membrane protein (T1088). For the three targets with NMR‐based structures, the best prediction results ranged from very good (GDT_TS = 0.90, for T1055) to poor (GDT_TS = 0.47, for T1029). We explored the basis of these results by comparing all CASP14 prediction models against experimental NMR data. For T1027, NMR data reveal extensive internal dynamics, presenting a unique challenge for protein structure prediction methods. The analysis of T1029 motivated exploration of a novel method of “inverse structure determination,” in which an AlphaFold2 model was used to guide NMR data analysis. NMR data provided to CASP predictor groups for target T1088, a 238‐residue integral membrane porin, was also used to assess several NMR‐assisted prediction methods. Most groups involved in this exercise generated similar beta‐barrel models, with good agreement with the experimental data. However, as was also observed in CASP13, some pure prediction groups that did not use any NMR data generated models for T1088 that better fit the NMR data than the models generated using these experimental data. These results demonstrate the remarkable power of modern methods to predict structures of proteins with accuracies rivaling solution NMR structures, and that it is now possible to reliably use prediction models to guide and complement experimental NMR data analysis.

Structure, Biosynthesis, and Biological Activity of Succinylated Forms of Bacteriocin BacSp222

BacSp222 is a multifunctional peptide produced by Staphylococcus pseudintermedius 222. This 50-amino acid long peptide belongs to subclass IId of bacteriocins and forms a four-helix bundle molecule. In addition to bactericidal functions, BacSp222 possesses also features of a virulence factor, manifested in immunomodulatory and cytotoxic activities toward eukaryotic cells. In the present study, we demonstrate that BacSp222 is produced in several post-translationally modified forms, succinylated at the ε-amino group of lysine residues. Such modifications have not been previously described for any bacteriocins. NMR and circular dichroism spectroscopy studies have shown that the modifications do not alter the spatial structure of the peptide. At the same time, succinylation significantly diminishes its bactericidal and cytotoxic potential. We demonstrate that the modification of the bacteriocin is an effect of non-enzymatic reaction with a highly reactive intracellular metabolite, i.e., succinyl-coenzyme A. The production of succinylated forms of the bacteriocin depends on environmental factors and on the access of bacteria to nutrients. Our study indicates that the production of succinylated forms of bacteriocin occurs in response to the changing environment, protects producer cells against the autotoxicity of the excreted peptide, and limits the pathogenicity of the strain.

NMR-Based Methods for Protein Analysis

Nuclear magnetic resonance (NMR) spectroscopy is a well-established method for analyzing protein structure, interaction, and dynamics at atomic resolution and in various sample states including solution state, solid state, and membranous environment. Thanks to rapid NMR methodology development, the past decade has witnessed a growing number of protein NMR studies in complex systems ranging from membrane mimetics to living cells, which pushes the research frontier further toward physiological environments and offers unique insights in elucidating protein functional mechanisms. In particular, in-cell NMR has become a method of choice for bridging the huge gap between structural biology and cell biology. Herein, we review the recent developments and applications of NMR methods for protein analysis in close-to-physiological environments, with special emphasis on in-cell protein structural determination and the analysis of protein dynamics, both difficult to be accessed by traditional methods.

Salt bridges govern the structural heterogeneity of heme protein interactions and porphyrin networks: microperoxidase-11

In this work, a proteolytic digest of cytochrome c (microperoxidase 11, MP-11) was used as a model to study the structural aspects of heme protein interactions and porphyrin networks. The MP-11 structural heterogeneity was studied as a function of the starting pH (e.g., pH 3.1-6.1) and concentration (e.g., 1-50 μM) conditions and adduct coordination. Trapped ion mobility spectrometry coupled to mass spectrometry (TIMS-MS) showed the MP-11 structural dependence of the charge state distribution and molecular ion forms with the starting pH conditions. The singly charged (e.g., [M]+, [M - 2H + NH4]+, [M - H + Na]+ and [M - H + K]+) and doubly charged (e.g., [M + H]2+, [M - H + NH4]2+, [M + Na]2+ and [M + K]2+) molecular ion forms were observed for all solvent conditions, although the structural heterogeneity (e.g., number of mobility bands) significantly varied with the pH value and ion form. The MP-11 dimer formation as a model for heme-protein protein interactions showed that dimer formation is favored toward more neutral pH and favored when assisted by salt bridges (e.g., NH4 +, Na+ and K+ vs. H+). Inspection of the dimer mobility profiles (2+ and 3+ charge states) showed a high degree of structural heterogeneity as a function of the solution pH and ion form; the observation of common mobility bands suggest that the different salt bridges can stabilize similar structural motifs. In addition, the salt bridge influence on the MP-11 dimer formations was measured using collision induced dissociation and showed a strong dependence with the type of salt bridge (i.e., a CE50 of 10.0, 11.5, 11.8 and 13.0 eV was observed for [2M + H]3+, [2M - H + NH4]3+, [2M + Na]3+ and [2M + K]3+, respectively). Measurements of the dimer equilibrium constant showed that the salt bridge interactions increase the binding strength of the dimeric species.

Rapid Biophysical Characterization and NMR Spectroscopy Structural Analysis of Small Proteins from Bacteria and Archaea

Proteins encoded by small open reading frames (sORFs) have a widespread occurrence in diverse microorganisms and can be of high functional importance. However, due to annotation biases and their technically challenging direct detection, these small proteins have been overlooked for a long time and were only recently rediscovered. The currently rapidly growing number of such proteins requires efficient methods to investigate their structure-function relationship. Herein, a method is presented for fast determination of the conformational properties of small proteins. Their small size makes them perfectly amenable for solution-state NMR spectroscopy. NMR spectroscopy can provide detailed information about their conformational states (folded, partially folded, and unstructured). In the context of the priority program on small proteins funded by the German research foundation (SPP2002), 27 small proteins from 9 different bacterial and archaeal organisms have been investigated. It is found that most of these small proteins are unstructured or partially folded. Bioinformatics tools predict that some of these unstructured proteins can potentially fold upon complex formation. A protocol for fast NMR spectroscopy structure elucidation is described for the small proteins that adopt a persistently folded structure by implementation of new NMR technologies, including automated resonance assignment and nonuniform sampling in combination with targeted acquisition.

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.

Protein structure prediction assisted with sparse NMR data in CASP13

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and ¹⁵ N-¹ H residual dipolar coupling data, typical of that obtained for ¹⁵ N,¹³ C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CASP13 also assessed whether incorporation of sparse NMR data improves the accuracy of protein structure prediction relative to nonassisted regular methods. In most cases, incorporation of sparse, noisy NMR data results in models with higher accuracy. The best NMR-assisted models were also compared with the best regular predictions of any CASP13 group for the same target. For six of 13 targets, the most accurate model provided by any NMR-assisted prediction group was more accurate than the most accurate model provided by any regular prediction group; however, for the remaining seven targets, one or more regular prediction method provided a more accurate model than even the best NMR-assisted model. These results suggest a novel approach for protein structure determination, in which advanced prediction methods are first used to generate structural models, and sparse NMR data is then used to validate and/or refine these models.

Comparison of NMR and crystal structures of membrane proteins and computational refinement to improve model quality

Membrane proteins are challenging to study and restraints for structure determination are typically sparse or of low resolution because the membrane environment that surrounds them leads to a variety of experimental challenges. When membrane protein structures are determined by different techniques in different environments, a natural question is "which structure is most biologically relevant?" Towards answering this question, we compiled a dataset of membrane proteins with known structures determined by both solution NMR and X-ray crystallography. By investigating differences between the structures, we found that RMSDs between crystal and NMR structures are below 5 Å in the membrane region, NMR ensembles have a higher convergence in the membrane region, crystal structures typically have a straighter transmembrane region, have higher stereo-chemical correctness, and are more tightly packed. After quantifying these differences, we used high-resolution refinement of the NMR structures to mitigate them, which paves the way for identifying and improving the structural quality of membrane proteins.

Modern Technologies of Solution Nuclear Magnetic Resonance Spectroscopy for Three-dimensional Structure Determination of Proteins Open Avenues for Life Scientists

Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for structural studies of chemical compounds and biomolecules such as DNA and proteins. Since the NMR signal sensitively reflects the chemical environment and the dynamics of a nuclear spin, NMR experiments provide a wealth of structural and dynamic information about the molecule of interest at atomic resolution. In general, structural biology studies using NMR spectroscopy still require a reasonable understanding of the theory behind the technique and experience on how to recorded NMR data. Owing to the remarkable progress in the past decade, we can easily access suitable and popular analytical resources for NMR structure determination of proteins with high accuracy. Here, we describe the practical aspects, workflow and key points of modern NMR techniques used for solution structure determination of proteins. This review should aid NMR specialists aiming to develop new methods that accelerate the structure determination process, and open avenues for non-specialist and life scientists interested in using NMR spectroscopy to solve protein structures.

Towards an efficient compression of 3D coordinates of macromolecular structures

The size and complexity of 3D macromolecular structures available in the Protein Data Bank is constantly growing. Current tools and file formats have reached limits of scalability. New compression approaches are required to support the visualization of large molecular complexes and enable new and scalable means for data analysis. We evaluated a series of compression techniques for coordinates of 3D macromolecular structures and identified the best performing approaches. By balancing compression efficiency in terms of the decompression speed and compression ratio, and code complexity, our results provide the foundation for a novel standard to represent macromolecular coordinates in a compact and useful file format.

A protocol for the refinement of NMR structures using simultaneously pseudocontact shift restraints from multiple lanthanide ions

The binding of paramagnetic metal ions to proteins produces a number of different effects on the NMR spectra of the system. In particular, when the magnetic susceptibility of the metal ion is anisotropic, pseudocontact shifts (PCSs) arise and can be easily measured. They constitute very useful restraints for the solution structure determination of metal-binding proteins. In this context, there has been great interest in the use of lanthanide(III) ions to induce PCSs in diamagnetic proteins, e.g. through the replacement native calcium(II) ions. By preparing multiple samples in each of which a different ion of the lanthanide series is introduced, it is possible to obtain multiple independent PCS datasets that can be used synergistically to generate protein structure ensembles (typically called bundles). For typical NMR-based determination of protein structure, it is necessary to perform an energetic refinement of such initial bundles to obtain final structures whose geometric quality is suitable for deposition in the PDB. This can be conveniently done by using restrained molecular dynamics simulations (rMD) in explicit solvent. However, there are no available protocols for rMD using multiple PCS datasets as part of the restraints. In this work, we extended the PCS module of the AMBER MD package to handle multiple datasets and tuned a previously developed protocol for NMR structure refinement to achieve consistent convergence with PCS restraints. Test calculations with real experimental data show that this new implementation delivers the expected improvement of protein geometry, resulting in final structures that are of suitable quality for deposition. Furthermore, we observe that also initial structures generated only with traditional restraints can be successfully refined using traditional and PCS restraints simultaneously.

Analysis of the interface variability in NMR structure ensembles of protein-protein complexes

NMR structures consist in ensembles of conformers, all satisfying the experimental restraints, which exhibit a certain degree of structural variability. We analyzed here the interface in NMR ensembles of protein-protein heterodimeric complexes and found it to span a wide range of different conservations. The different exhibited conservations do not simply correlate with the size of the systems/interfaces, and are most probably the result of an interplay between different factors, including the quality of experimental data and the intrinsic complex flexibility. In any case, this information is not to be missed when NMR structures of protein-protein complexes are analyzed; especially considering that, as we also show here, the first NMR conformer is usually not the one which best reflects the overall interface. To quantify the interface conservation and to analyze it, we used an approach originally conceived for the analysis and ranking of ensembles of docking models, which has now been extended to directly deal with NMR ensembles. We propose this approach, based on the conservation of the inter-residue contacts at the interface, both for the analysis of the interface in whole ensembles of NMR complexes and for the possible selection of a single conformer as the best representative of the overall interface. In order to make the analyses automatic and fast, we made the protocol available as a web tool at: https://www.molnac.unisa.it/BioTools/consrank/consrank-nmr.html.

Protocol To Make Protein NMR Structures Amenable to Stable Long Time Scale Molecular Dynamics Simulations

A robust protocol for the treatment of NMR protein structures is presented that makes them amenable to long time scale molecular dynamics (MD) simulations that are stable. The protocol embeds an NMR structure in a native low energy region of the recently developed ff99SB_φψ(g24;CS) molecular mechanics force field. Extended MD trajectories that start from these structures show good consistency with proton-proton nuclear Overhauser effect data, and they reproduce NMR chemical shift data better than the original NMR structures as is demonstrated for four protein systems. Moreover, for all proteins studied here the simulations spontaneously approach the X-ray crystal structures, thereby improving the effective resolution of the initial structural models.

Computational approaches for inferring the functions of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are ubiquitously involved in cellular processes and often implicated in human pathological conditions. The critical biological roles of these proteins, despite not adopting a well-defined fold, encouraged structural biologists to revisit their views on the protein structure-function paradigm. Unfortunately, investigating the characteristics and describing the structural behavior of IDPs is far from trivial, and inferring the function(s) of a disordered protein region remains a major challenge. Computational methods have proven particularly relevant for studying IDPs: on the sequence level their dependence on distinct characteristics determined by the local amino acid context makes sequence-based prediction algorithms viable and reliable tools for large scale analyses, while on the structure level the in silico integration of fundamentally different experimental data types is essential to describe the behavior of a flexible protein chain. Here, we offer an overview of the latest developments and computational techniques that aim to uncover how protein function is connected to intrinsic disorder.

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.

Solution NMR Structure Determination of Polytopic α-Helical Membrane Proteins: A Guide to Spin Label Paramagnetic Relaxation Enhancement Restraints

Solution nuclear magnetic resonance structures of polytopic α-helical membrane proteins require additional restraints beyond the traditional Nuclear Overhauser Effect (NOE) restraints. Several methods have been developed and this review focuses on paramagnetic relaxation enhancement (PRE). Important aspects of spin labeling, PRE measurements, structure calculations, and structural quality are discussed.

Systematic solution to homo-oligomeric structures determined by NMR

Protein structure determination by NMR has predominantly relied on simulated annealing-based conformational search for a converged fold using primarily distance constraints, including constraints derived from nuclear Overhauser effects, paramagnetic relaxation enhancement, and cysteine crosslinkings. Although there is no guarantee that the converged fold represents the global minimum of the conformational space, it is generally accepted that good convergence is synonymous to the global minimum. Here, we show such a criterion breaks down in the presence of large numbers of ambiguous constraints from NMR experiments on homo-oligomeric protein complexes. A systematic evaluation of the conformational solutions that satisfy the NMR constraints of a trimeric membrane protein, DAGK, reveals 9 distinct folds, including the reported NMR and crystal structures. This result highlights the fundamental limitation of global fold determination for homo-oligomeric proteins using ambiguous distance constraints and provides a systematic solution for exhaustive enumeration of all satisfying solutions.

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.

The expanded FindCore method for identification of a core atom set for assessment of protein structure prediction

Maximizing the scientific impact of NMR-based structure determination requires robust and statistically sound methods for assessing the precision of NMR-derived structures. In particular, a method to define a core atom set for calculating superimpositions and validating structure predictions is critical to the use of NMR-derived structures as targets in the CASP competition. FindCore (Snyder and Montelione, Proteins 2005;59:673-686) is a superimposition independent method for identifying a core atom set and partitioning that set into domains. However, as FindCore optimizes superimposition by sensitively excluding not-well-defined atoms, the FindCore core may not comprise all atoms suitable for use in certain applications of NMR structures, including the CASP assessment process. Adapting the FindCore approach to assess predicted models against experimental NMR structures in CASP10 required modification of the FindCore method. This paper describes conventions and a standard protocol to calculate an "Expanded FindCore" atom set suitable for validation and application in biological and biophysical contexts. A key application of the Expanded FindCore method is to identify a core set of atoms in the experimental NMR structure for which it makes sense to validate predicted protein structure models. We demonstrate the application of this Expanded FindCore method in characterizing well-defined regions of 18 NMR-derived CASP10 target structures. The Expanded FindCore protocol defines "expanded core atom sets" that match an expert's intuition of which parts of the structure are sufficiently well defined to use in assessing CASP model predictions. We also illustrate the impact of this analysis on the CASP GDT assessment scores.