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To understand the dynamic nuclear polarization (DNP) enhancements of biradical polarizing agents, the magnetic resonance parameters need to be known. We describe a tailored EPR approach to accurately determine electron spin-spin coupling parameters using a combination of standard (9 GHz), high (95 GHz) and ultra-high (275 GHz) frequency EPR. Comparing liquid- and frozen-solution continuous-wave EPR spectra provides accurate anisotropic dipolar interaction D and isotropic exchange interaction J parameters of the DNP biradical AMUPol. We found that D was larger by as much as 30% compared to earlier estimates, and that J is 43 MHz, whereas before it was considered to be negligible. With the refined data, quantum mechanical calculations confirm that an increase in dipolar electron-electron couplings leads to higher cross-effect DNP efficiencies. Moreover, the DNP calculations qualitatively reproduce the difference of TOTAPOL and AMUPol DNP efficiencies found experimentally and suggest that AMUPol is particularly effective in improving the DNP efficiency at magnetic fields higher than 500 MHz. The multi-frequency EPR approach will aid in predicting the optimal structures for future DNP agents.

The wild-type Gtf180-ΔN glucansucrase enzyme from Lactobacillus reuteri 180 was found to catalyze the α-glucosylation of the steviol glycoside rebaudioside A, using sucrose as glucosyl donor in a transglucosylation process. Structural analysis of the formed products by MALDI-TOF mass spectrometry, methylation analysis and NMR spectroscopy showed that rebaudioside A is specifically α-d-glucosylated at the steviol C-19 β-d-glucosyl moiety (55% conversion). The main product is a mono-(α1 → 6)-glucosylated derivative (RebA-G1). A series of minor products, up to the incorporation of eight glucose residues, comprise elongations of RebA-G1 with mainly alternating (α1 → 3)- and (α1 → 6)-linked glucopyranose residues. These studies were carried out in the context of a program directed to the improvement of the taste of steviol glycosides via enzymatic modification of their naturally occurring carbohydrate moieties.

Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins. One possibility is to use the best available homology modeling and docking methods. However, the models built for the individual subunits often differ to a significant degree from the bound conformation in the complex, often much more so than the differences observed between free and bound structures of the same protein, and therefore additional conformational adjustments, both at the backbone and side chain levels need to be modeled to achieve an accurate docking prediction. In particular, even homology models of overall good accuracy frequently include localized errors that unfavorably impact docking results. The predicted reliability of the different regions in the model can also serve as a useful input for the docking calculations. Here we present a benchmark dataset that should help to explore and solve combined modeling and docking problems. This dataset comprises a subset of the experimentally solved 'target' complexes from the widely used Docking Benchmark from the Weng Lab (excluding antibody-antigen complexes). This subset is extended to include the structures from the PDB related to those of the individual components of each complex, and hence represent potential templates for investigating and benchmarking integrated homology modeling and docking approaches. Template sets can be dynamically customized by specifying ranges in sequence similarity and in PDB release dates, or using other filtering options, such as excluding sets of specific structures from the template list. Multiple sequence alignments, as well as structural alignments of the templates to their corresponding subunits in the target are also provided. The resource is accessible online or can be downloaded at http://cluspro.org/benchmark, and is updated on a weekly basis in synchrony with new PDB releases. This article is protected by copyright. All rights reserved.

We present a broadly applicable, user-friendly protocol that incorporates sparse and hybrid experimental data to calculate quasi-atomic-resolution structures of molecular machines. The protocol uses the HADDOCK framework, accounts for extensive structural rearrangements both at the domain and atomic levels and accepts input from all structural and biochemical experiments whose data can be translated into interatomic distances and/or molecular shapes.

Disaccharides are well known for their membrane protective ability. Interaction between sugars and multi-component membranes, however, remains largely unexplored. Here, we combine molecular dynamics simulations and fluorescence microscopy to study the effect of mono- and disaccharides on membranes that phase separate into Lo and Ld domains. We find that non-reducing disaccharides, sucrose and trehalose, strongly destabilize the phase separation leading to uniformly mixed membranes as opposed to monosaccharides and reducing disaccharides. To unveil the driving force for this process, simulations were performed in which the sugar linkage was artificially modified. The availability of accessible interfacial binding sites that can accommodate the non-reducing disaccharides is key for their strong impact on lateral membrane organization. These exclusive interactions between the non-reducing sugars and the membranes may rationalize why organisms such as yeasts, tardigrades, nematodes, bacteria and plants accumulate sucrose and trehalose, offering cell protection under anhydrobiotic conditions. The proposed mechanism might prove to be a more generic way by which surface bound agents could affect membranes.

Protein-protein complexes orchestrate most cellular processes such as transcription, signal transduction and apoptosis. The factors governing their affinity remain elusive however, especially when it comes to describing dissociation rates (koff). Here we demonstrate that, next to direct contributions from the interface, the non-interacting surface (NIS) also plays an important role in binding affinity, especially polar and charged residues. Their percentage on the NIS is conserved over orthologous complexes indicating an evolutionary selection pressure. Their effect on binding affinity can be explained by long-range electrostatic contributions and surface-solvent interactions that are known to determine the local frustration of the protein complex surface. Including these in a simple model significantly improves the affinity prediction of protein complexes from structural models. The impact of mutations outside the interacting surface on binding affinity is supported by experimental alanine scanning mutagenesis data. These results enable the development of more sophisticated and integrated biophysical models of binding affinity and open new directions in experimental control and modulation of biomolecular interactions.

The outer membrane protein BamA is the key player in β-barrel assembly in Gram-negative bacteria. Despite the availability of high-resolution crystal structures, the dynamic behavior of the transmembrane domain and the large periplasmic extension consisting of five POTRA (POlypeptide-TRansport-Associated) domains remains unclear. We demonstrate reconstitution of full-length BamA in proteoliposomes at low lipid-to-protein ratio, leading to high sensitivity and resolution in solid-state NMR (ssNMR) experiments. We detect POTRA domains in ssNMR experiments probing rigid protein segments in our preparations. These results suggest that the periplasmic region of BamA is firmly attached to the β-barrel and does not experience fast global motion around the angle between POTRA 2 and 3. We show that this behavior holds at lower protein concentrations and elevated temperatures. Chemical shift variations observed after reconstitution in lipids with different chain lengths and saturation levels are compatible with conformational plasticity of BamA's transmembrane domain. Electron microscopy of the ssNMR samples shows that BamA can cause local disruptions of the lipid bilayer in proteoliposomes. The observed interplay between protein–protein and protein–lipid interactions may be critical for BamA-mediated insertion of substrates into the outer membrane. © 2014 Elsevier Ltd. All rights reserved.

The HADDOCK score, a scoring function for both protein-protein and protein-nucleic acid modeling, has been successful in selecting near-native docking poses in a variety of cases, including those of the CAPRI blind prediction experiment. However, it has yet to be optimized for small molecules, and in particular inhibitors of protein-protein interactions, that constitute an "unmined gold reserve" for drug design ventures. We describe here HADDOCK(2P2I), a biophysical model capable of predicting the binding affinity of protein-protein complex inhibitors close to experimental error (~2-fold larger). The algorithm was trained and 4-fold cross-validated against experimental data for 27 inhibitors targeting 7 protein-protein complexes of various functions and tested on an independent set of 24 different inhibitors for which K(d)/IC50 data are available. In addition, two popular ligand topology generation and parametrization methods (ACPYPE and PRODRG) were assessed. The resulting HADDOCK(2P2I) model, derived from the original HADDOCK score, provides insights into inhibition determinants: while the role of electrostatics and desolvation energies is case-dependent, the interface area plays a more critical role compared to protein-protein interactions.

Polysialic acid (polySia) and polySia glycomimetic molecules support nerve cell regeneration, differentiation, and neuronal plasticity. With a combination of biophysical and biochemical methods, as well as data mining and molecular modeling techniques, it is possible to correlate specific ligand-receptor interactions with biochemical processes and in vivo studies that focus on the potential therapeutic impact of polySia, polySia glycomimetics, and sulfated polysaccharides in neuronal diseases. With this strategy, the receptor interactions of polySia and polySia mimetics can be understood on a submolecular level. As the HNK-1 glycan also enhances neuronal functions, we tested whether similar sulfated oligo- and polysaccharides from seaweed could be suitable, in addition to polySia, for finding potential new routes into patient care focusing on an improved cure for various neuronal diseases. The knowledge obtained here on the structural interplay between polySia or sulfated polysaccharides and their receptors can be exploited to develop new drugs and application routes for the treatment of neurological diseases and dysfunctions. Submolecular polySia-nce: Specific interactions of polysialic acid (polySia) and polySia glycomimetic molecules were studied at the submolecular level using a combination of NMR and molecular modeling. The structure-function interplay between polySia or sulfated polysaccharides and their receptors can be exploited to develop new drugs and application routes for the treatment of neurological diseases and dysfunctions.

Stem‐cell behavior is regulated by the material properties of the surrounding extracellular matrix, which has important implications for the design of tissue‐engineering scaffolds. However, our understanding of the material properties of stem‐cell scaffolds is limited to nanoscopic‐to‐macroscopic length scales. Herein, a solid‐state NMR approach is presented that provides atomic‐scale information on complex stem‐cell substrates at near physiological conditions and at natural isotope abundance. Using self‐assembled peptidic scaffolds designed for nervous‐tissue regeneration, we show at atomic scale how scaffold‐assembly degree, mechanics, and homogeneity correlate with favorable stem cell behavior. Integration of solid‐state NMR data with molecular dynamics simulations reveals a highly ordered fibrillar structure as the most favorable stem‐cell scaffold. This could improve the design of tissue‐engineering scaffolds and other self‐assembled biomaterials., In good molecular order: Solid‐state NMR spectroscopy demonstrates that atomic‐scale properties, including molecular order and mechanics, of tissue‐engineering scaffolds correlate with the viability of stem cell cultures. This insight could improve the design of tissue‐engineering scaffolds for regenerative medicine applications.

Understanding molecular recognition of small molecules by proteins in atomistic detail is key for drug design. Molecular docking is a widely used computational method to mimic ligand-protein association in silico. However, predicting conformational changes occurring in proteins upon ligand binding is still a major challenge. Ensemble docking approaches address this issue by considering a set of different conformations of the protein obtained either experimentally or from computer simulations, e.g., molecular dynamics. However, holo structures prone to host (the correct) ligands are generally poorly sampled by standard molecular dynamics simulations of the apo protein. In order to address this limitation, we introduce a computational approach based on metadynamics simulations called ensemble docking with enhanced sampling of pocket shape (EDES) that allows holo-like conformations of proteins to be generated by exploiting only their apo structures. This is achieved by defining a set of collective variables that effectively sample different shapes of the binding site, ultimately mimicking the steric effect due to the ligand. We assessed the method on three challenging proteins undergoing different extents of conformational changes upon ligand binding. In all cases our protocol generates a significant fraction of structures featuring a low RMSD from the experimental holo geometry. Moreover, ensemble docking calculations using those conformations yielded in all cases native-like poses among the top-ranked ones.

Objective The nuclear receptor PPARγ is the master regulator of adipocyte differentiation, distribution, and function. In addition, PPARγ induces terminal differentiation of several epithelial cell lineages, including colon epithelia. Loss-of-function mutations in PPARG result in familial partial lipodystrophy subtype 3 (FPDL3), a rare condition characterized by aberrant adipose tissue distribution and severe metabolic complications, including diabetes. Mutations in PPARG have also been reported in sporadic colorectal cancers, but the significance of these mutations is unclear. Studying these natural PPARG mutations provides valuable insights into structure-function relationships in the PPARγ protein. We functionally characterized a novel FPLD3-associated PPARγ L451P mutation in helix 9 of the ligand binding domain (LBD). Interestingly, substitution of the adjacent amino acid K450 was previously reported in a human colon carcinoma cell line. Methods We performed a detailed side-by-side functional comparison of these two PPARγ mutants. Results PPARγ L451P shows multiple intermolecular defects, including impaired cofactor binding and reduced RXRα heterodimerisation and subsequent DNA binding, but not in DBD-LBD interdomain communication. The K450Q mutant displays none of these functional defects. Other colon cancer-associated PPARγ mutants displayed diverse phenotypes, ranging from complete loss of activity to wildtype activity. Conclusions Amino acid changes in helix 9 can differently affect LBD integrity and function. In addition, FPLD3-associated PPARγ mutations consistently cause intra- and/or intermolecular defects; colon cancer-associated PPARγ mutations on the other hand may play a role in colon cancer onset and progression, but this is not due to their effects on the most well-studied functional characteristics of PPARγ., Highlights • Mutations in PPARG, encoding for the nuclear receptor PPARγ, underly lipodystrophy. • A novel lipodystrophy-associated PPARγ mutant, L451P, displays impaired activity. • Mutation of the adjacent K450, detected in colon cancer, has no effect. • Other colon cancer-associated PPARγ mutants display diverse phenotypes. • Lipodystrophy but not cancer-associated PPARγ mutants consistently display defects.

3D domain swapping (3D‐DS) is a complex protein aggregation process for which no unique mechanism exists. We report an analysis of 3D‐DS in bovine seminal ribonuclease, a homodimeric protein whose subunits are linked by two disulfide bridges, based on NMR and biochemical studies. The presence of the covalent bonds between the subunits stabilizes the unswapped dimer, and allows distinct evaluation of the structural and dynamic effects of the swapping with respect to the dimerization process. In comparison with the monomeric subunit, which, in solution has a compact structure without any propensity for local unfolding, both swapped and unswapped dimers show increased flexibility. NMR analysis, together with urea denaturation and hydrogen–deuterium exchange data, indicates that the two dimers have increased conformational fluctuations. Furthermore, we found that the rate‐limiting step of both the swapping and unswapping pathways is the detachment of the N‐terminal helices from the monomers. These results suggest a new general mechanism in which a dimeric intermediate could facilitate 3D‐DS in globular proteins. Structured digital abstract http://www.uniprot.org/uniprot/P00669 and http://www.uniprot.org/uniprot/P00669 http://www.ebi.ac.uk/ontology-lookup/?termId=MI:0407 by http://www.ebi.ac.uk/ontology-lookup/?termId=MI:0077 (http://www.ebi.ac.uk/intact/interaction/EBI-8870415), BS‐RNase is a unique dimeric protein, because it undergoes 3D domain swapping and exists as dimer also in the unswapped state. Our structural and dynamical comparative analysis among the swapped and unswapped isomers indicates that dimerization prepares the swapping, influencing the protein dynamics and conformational fluctuations. We suggest that this mechanism could be of more general occurrence.

Solution-state NMR spectroscopy has become a powerful tool to study soluble proteins in cells, provided that they tumble sufficiently fast. In addition, cryo-electron tomography (cryo-ET) has recently displayed a tremendous potential to probe structures of large proteins and assemblies in their native cellular environments. However, challenges remain to obtain atomic-level information in native cell settings for proteins that are small, disordered, or are strongly engaged in intermolecular interactions. In this Minireview, we discuss recent progress in using sensitivity enhanced solid-state NMR spectroscopy methods in the context of cellular structural biology.

Comment: 28 pages including 7 figures, The recent improvements in cryo-electron microscopy (cryo-EM) in the past few years are now allowing to observe molecular complexes at atomic resolution. As a consequence, numerous structures derived from cryo-EM are now available in the Protein Data Bank. However, if for some complexes atomic resolution is reached, this is not true for all. This is also the case in cryo-electron tomography where the achievable resolution is still limited. Furthermore the resolution in a cryo-EM map is not a constant, with often outer regions being of lower resolution, possibly linked to conformational variability. Although those low to medium resolution EM maps (or regions thereof) cannot directly provide atomic structure of large molecular complexes, they provide valuable information to model the individual components and their assembly into them. Most approaches for this kind of modelling are performing rigid fitting of the individual components into the EM density map. While this would appear an obvious option, they ignore key aspects of molecular recognition, the energetics and flexibility of the interfaces. Moreover, these often restricts the modelling to a unique source of data, the EM density map. In this chapter, we describe a protocol where an EM map is used as restraint in HADDOCK to guide the modelling process.

The three GxxxG repeating motifs from the C-terminal region of β-amyloid (Aβ) peptide play a significant role in regulating the aggregation kinetics of the peptide. Mutation of these glycine residues to leucine greatly accelerates the fibrillation process but generates a varied toxicity profile. Using an array of biophysical techniques, we demonstrated the uniqueness of the composite glycine residues in these structural repeats. We used solvent relaxation NMR spectroscopy to investigate the role played by the surrounding water molecules in determining the corresponding aggregation pathway. Notably, the conformational changes induced by Gly33 and Gly37 mutations result in significantly decreased toxicity in a neuronal cell line. Our results indicate that G33 xxxG37 is the primary motif responsible for Aβ neurotoxicity, hence providing a direct structure-function correlation. Targeting this motif, therefore, can be a promising strategy to prevent neuronal cell death associated with Alzheimer's and other related diseases, such as type II diabetes and Parkinson's.

The β-barrel assembly machinery (BAM) complex is an essential machinery in E. coli which is responsible for the correct folding and insertion of outer membrane β-barrel proteins into the outer membrane. Despite the wealth of information garnered from in vitro and in vivo experiments, debate still exists in regard to the mechanism employed by this machinery in an environment without external sources of energy. knowledge of the BAM complex is critical for understanding the mechanistic details of outer membrane protein biogenesis. Our goal was to study the BAM complex in an environment that mimics some of the characteristics of the outer membrane (lipid-to-protein ratio, lipid phase, hydrophobic thickness) whilst still allowing us to obtain such atomic level information. This information can then be transferred to studies of the BAM complex in its native environment. The studies described in this thesis relied on advancements in the field of solid-state NMR to be able to study such large membrane protein complexes, such as proton detection and dynamic nuclear polarization. The work described in this thesis is a significant advancement towards being able to study a large membrane protein complex in its native environment at the atomic level. Importantly, the approaches described are not restricted to the BAM but are generally applicable to large membrane protein complexes.

A major issue in the catalytic fast pyrolysis (CFP) of biomass is the rapid deactivation of the typically employed zeolite-based catalysts. Detailed understanding of the deactivation pathways and the type and location of coke deposits are essential for the further development of improved or new catalyst materials, including appropriate regeneration protocols. Such deactivation and regeneration studies focus almost invariably on small-scale CFP reactor units employing catalyst materials in powder form. In this study, we report the in-depth characterization of deactivated and regenerated ZrO2-promoted zeolite ZSM-5 catalyst extrudates after ex-situ CFP tests carried out in a bench scale reactor. The findings support that coking is the main reason for catalyst deactivation, i.e. for the observed decreased activity in cracking and deoxygenation. Post-mortem characterization by confocal fluorescence microscopy reveals an egg-shell spatial distribution of the coke deposits within the catalyst extrudates. These deposits are heavily poly-aromatic in nature. The majority of the coke build-up occurs in the first 20 min of the reaction and is formed on the strong Bronsted acid sites, which promote deep deoxygenation and cracking. With increasing time-on-stream, the coke deposition slows down, occurring now mainly on the external surface of the zeolite to generate a softer, i.e. more hydrogen-rich, coke on the ZrO2 domains. The catalyst is readily regenerated via thermal oxidation in air, with optimal regeneration at 500 °C. This temperature removes all coke deposits, with no detrimental effect on the catalyst’s structural, textural and acid (type and strength) properties.

Understanding of the molecular mechanisms of protein function requires detailed insight into the conformational landscape accessible to the protein. Conformational changes can be crucial for biological processes, such as ligand binding, protein folding, and catalysis. NMR spectroscopy is exquisitely sensitive to such dynamic changes in protein conformations. In particular, Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion experiments are a powerful tool to investigate protein dynamics on a millisecond time scale. CPMG experiments that probe the chemical shift modulation of 15N in-phase magnetization are particularly attractive, due to their high sensitivity. These experiments require high power 1H decoupling during the CPMG period to keep the 15N magnetization in-phase. Recently, an improved version of the in-phase 15N-CPMG experiment was introduced, offering greater ease of use by employing a single 1H decoupling power for all CPMG pulsing rates. In these experiments however, incomplete decoupling of off-resonance amide 1H spins introduces an artefactual dispersion of relaxation rates, the so-called slow-pulsing artifact. Here, we analyze the slow-pulsing artifact in detail and demonstrate that it can be suppressed through the use of composite pulse decoupling (CPD). We report the performances of various CPD schemes and show that CPD decoupling based on the 90x-240y-90x element results in high-quality dispersion curves free of artifacts, even for amides with high 1H offset.

Structural characterization of proteins and their complexes is a fundamental part in understanding any biological phenomena. Yet, the experimental determination of the three‐dimensional (3D) structure of proteins and their complexes remains a challenging undertaking. In order to complement the experimental approaches, computational methods have been developed based on a variety of algorithms and models to fill the gap between the amount of sequences and structures. In this article, we review the most common methodological approaches currently used in the field, highlighting the ab initio structure prediction methods and methods for the prediction and structural modeling of protein–protein interfaces (PPIs). We particularly focus on the use of evolutionary information to guide the modeling process.

Membrane proteins remain challenging targets for structural biology, despite much effort, as their native environment is heterogeneous and complex. Most methods rely on detergents to extract membrane proteins from their native environment, but this removal can significantly alter the structure and function of these proteins. Here, we overcome these challenges with a hybrid method to study membrane proteins in their native membranes, combining high-resolution solid-state nuclear magnetic resonance spectroscopy and electron cryotomography using the same sample. Our method allows the structure and function of membrane proteins to be studied in their native environments, across different spatial and temporal resolutions, and the combination is more powerful than each technique individually. We use the method to demonstrate that the bacterial membrane protein YidC adopts a different conformation in native membranes and that substrate binding to YidC in these native membranes differs from purified and reconstituted systems

The pdb-tools are a collection of Python scripts for working with molecular structure data in the Protein Data Bank (PDB) format. They allow users to edit, convert, and validate PDB files, from the command-line, in a simple but efficient manner. The pdb-tools are implemented in Python, without any external dependencies, and are freely available under the open-source Apache License at https://github.com/haddocking/pdb-tools/ and on PyPI.

The chiral configuration of the two radical parts is a crucial factor controlling the exchange interactions and DNP properties of trityl-nitroxide biradicals., The exchange (J) interaction of organic biradicals is a crucial factor controlling their physiochemical properties and potential applications and can be modulated by changing the nature of the linker. In the present work, we for the first time demonstrate the effect of chiral configurations of radical parts on the J values of trityl-nitroxide (TN) biradicals. Four diastereoisomers (TNT1, TNT2, TNL1 and TNL2) of TN biradicals were synthesized and purified by the conjugation of a racemic (R/S) nitroxide with the racemic (M/P) trityl radical vial-proline. The absolute configurations of these diastereoisomers were assigned by comparing experimental and calculated electronic circular dichroism (ECD) spectra as (M, S, S) for TNT1, (P, S, S) for TNT2, (M, S, R) for TNL1 and (P, S, R) for TNL2. Electron paramagnetic resonance (EPR) results showed that the configuration of the nitroxide part instead of the trityl part is dominant in controlling the exchange interactions and the order of the J values at room temperature is TNT1 (252 G) > TNT2 (127 G) ≫ TNL2 (33 G) > TNL1 (14 G). Moreover, the J values of TNL1/TNL2 with the S configuration in the nitroxide part vary with temperature and the polarity of solvents due to their flexible linker, whereas the J values of TNT1/TNT2 are almost insensitive to these two factors due to the rigidity of their linkers. The distinct exchange interactions between TNT1,2 and TNL1,2 in the frozen state led to strongly different high-field dynamic nuclear polarization (DNP) enhancements with ε = 7 for TNT1,2 and 40 for TNL1,2 under 800 MHz DNP conditions.

Architectural DNA-binding proteins are key to the organization and compaction of genomic DNA inside cells. The activity of architectural proteins is often subject to further modulation and regulation through the interaction with a diverse array of other protein factors. Detailed knowledge on the binding modes involved is crucial for our understanding of how these protein-protein and protein-DNA interactions shape the functional landscape of chromatin in all kingdoms of life: bacteria, archaea, and eukarya.Microscale thermophoresis (MST) is a biophysical technique that has seen increasing application in the study of biomolecular interactions thanks to its solution-based nature, its rapid application, modest sample demand, and the sensitivity of the thermophoresis effect to binding events. Here, we describe the use of MST in the study of chromatin interactions, with emphasis on the wide range of ways in which these experiments are set up and the diverse types of information they reveal. These aspects are illustrated with four very different systems: the sequence-dependent DNA compaction by architectural protein HMfB; the sequential binding of core histone complexes to histone chaperone APLF; the impact of the nucleosomal context on the recognition of histone modifications; and the binding of a LANA-derived peptide to nucleosome core. Special emphasis is given to the key steps in the design, execution, and analysis of MST experiments in the context of the provided examples.

Solid-state NMR (ssNMR) can provide structural information at the most detailed level and, at the same time, is applicable in highly heterogeneous and complex molecular environments, largely irrespective of solubility or crystallinity. In the following chapter, we discuss concepts to deal with the spectroscopic challenges of applying ssNMR to complex biomolecular systems and how to place structural information obtained from ssNMR in a (supra)molecular context. Applications range from protein biopolymers and hydrogels to drug delivery systems, biosilica, and other biomaterials.

Summary: We present DisVis, a Python package and command line tool to calculate the reduced accessible interaction space of distance-restrained binary protein complexes, allowing for direct visualization and quantification of the information content of the distance restraints. The approach is general and can also be used as a knowledge-based distance energy term in FFT-based docking directly during the sampling stage. Availability and implementation: The source code with documentation is freely available from https://github.com/haddocking/disvis. Contact: a.m.j.j.bonvin@uu.nl Supplementary information: Supplementary data are available at Bioinformatics online.

Humin by-products are formed during the acid-catalyzed dehydration of carbohydrates to bio-based platform molecules, such as hydroxymethylfurfural and levulinic acid. The molecular structure of these humins has not yet been unequivocally established. 1D 13C solid-state NMR data reported have, for example, provided considerable insight, but do not allow for the unambiguous assignment of key structural motifs. Complementary (2D) techniques are needed to gain additional insight into the molecular structure of humins. Here, the preparation of 13C-enriched humins is reported, together with the reactive solubilization of these labeled humins and their characterization with complementary 1D and 2D solid-state NMR techniques. 1D cross polarization (CP) and direct excitation (DE) 13C solid-state NMR spectra, 2D 13C-detected double-quantum single-quantum (DQSQ) as well as 2D 1H-detected heteronuclear correlation (HETCOR) were recorded with different excitation schemes. These experiments unambiguously established that the original humins have a furan-rich structure with aliphatic linkers and allowed for a refinement of the molecular structure proposed previously. Solid-state NMR data of alkali-treated 13C-labeled humins showed that an arene-rich structure is formed at the expense of the furanic network during alkaline pretreatment.

International audience; The glycopeptide CcTx, isolated from the venom of the piscivorous cone snail Conus consors, belongs to the κA-family of conopeptides. These toxins elicit excitotoxic responses in the prey by acting on voltage-gated sodium channels. The structure of CcTx, a first in the κA-family, has been determined by high-resolution NMR spectroscopy together with the analysis of its O-glycan at Ser7. A new type of glycopeptide O-glycan core structure, here registered as core type 9, containing two terminal L-galactose units {α-L-Galp-(1→4)-α-D-GlcpNAc-(1→6)-[α-L-Galp-(1→2)-β-D-Galp-(1→3)-]α-D-GalpNAc-(1→O)}, is highlighted. A sequence comparison to other putative members of the κA-family suggests that O-linked glycosylation might be more common than previously thought. This observation alone underlines the requirement for more careful and in-depth investigations into this type of post-translational modification in conotoxins.

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such "in silico" data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR ( http://www.wenmr.eu/services/FANDAS ).

Subversion of the host immune system by viruses is often mediated by molecular decoys that sequester host proteins pivotal to mounting effective immune responses. The widespread mammalian pathogen parapox Orf virus deploys GIF, a member of the poxvirus immune evasion superfamily, to antagonize GM-CSF (granulocyte macrophage colony-stimulating factor) and IL-2 (interleukin-2), two pleiotropic cytokines of the mammalian immune system. However, structural and mechanistic insights into the unprecedented functional duality of GIF have remained elusive. Here we reveal that GIF employs a dimeric binding platform that sequesters two copies of its target cytokines with high affinity and slow dissociation kinetics to yield distinct complexes featuring mutually exclusive interaction footprints. We illustrate how GIF serves as a competitive decoy receptor by leveraging binding hotspots underlying the cognate receptor interactions of GM-CSF and IL-2, without sharing any structural similarity with the cytokine receptors. Our findings contribute to the tracing of novel molecular mimicry mechanisms employed by pathogenic viruses., Viruses often subvert the host immune system using molecular decoys to prevent an effective immune response. Here, the authors examine the structural details of the viral decoy receptor GIF and its antagnosim of GM-CSF and IL-2.

Iron is a limiting nutrient in bacterial infection putting it at the centre of an evolutionary arms race between host and pathogen. Gram-negative bacteria utilize TonB-dependent outer membrane receptors to obtain iron during infection. These receptors acquire iron either in concert with soluble iron-scavenging siderophores or through direct interaction and extraction from host proteins. Characterization of these receptors provides invaluable insight into pathogenesis. However, only a subset of virulence-related TonB-dependent receptors have been currently described. Here we report the discovery of FusA, a new class of TonB-dependent receptor, which is utilized by phytopathogenic Pectobacterium spp. to obtain iron from plant ferredoxin. Through the crystal structure of FusA we show that binding of ferredoxin occurs through specialized extracellular loops that form extensive interactions with ferredoxin. The function of FusA and the presence of homologues in clinically important pathogens suggests that small iron-containing proteins represent an iron source for bacterial pathogens., Many bacteria use TonB-dependent outer membrane receptors to scavenge iron from their host during infection. Here, the authors report on the structure and function of FusA, which is a bacterial receptor that is used to obtain iron from plants.

Incorporation of Ca in ZSM-5 results in a twofold increase of propylene selectivity (53%), a total light-olefin selectivity of 90%, and a nine times longer catalyst lifetime (throughput 792 g(MeOH)g(catalyst)(-1)) in the methanol-to-olefins (MTO) reaction. Analysis of the product distribution and theoretical calculations reveal that post-synthetic modification with Ca2+ leads to the formation of CaOCaOH+ that strongly weaken the acid strength of the zeolite. As a result, the rate of hydride transfer and oligomerization reactions on these sites is greatly reduced, resulting in the suppression of the aromatic cycle. Our results further highlight the importance of acid strength on product selectivity and zeolite lifetime in MTO chemistry.

Ion conduction across the cellular membrane requires the simultaneous opening of activation and inactivation gates of the K+ channel pore. The bacterial KcsA channel has served as a powerful system for dissecting the structural changes that are related to four major functional states associated with K+ gating. Yet, the direct observation of the full gating cycle of KcsA has remained structurally elusive, and crystal structures mimicking these gating events require mutations in or stabilization of functionally relevant channel segments. Here, we found that changes in lipid composition strongly increased the KcsA open probability. This enabled us to probe all four major gating states in native-like membranes by combining electrophysiological and solid-state NMR experiments. In contrast to previous crystallographic views, we found that the selectivity filter and turret region, coupled to the surrounding bilayer, were actively involved in channel gating. The increase in overall steady-state open probability was accompanied by a reduction in activation-gate opening, underscoring the important role of the surrounding lipid bilayer in the delicate conformational coupling of the inactivation and activation gates.

Heteronuclear and homonuclear direct (D) and indirect (J) spin–spin interactions are important sources of structural information about nucleic acids (NAs). The Hamiltonians for the D and J interactions have the same functional form; thus, the experimentally measured apparent spin–spin coupling constant corresponds to a sum of J and D. In biomolecular NMR studies, it is commonly presumed that the dipolar contributions to Js are effectively canceled due to random molecular tumbling. However, in strong magnetic fields, such as those employed for NMR analysis, the tumbling of NA fragments is anisotropic because the inherent magnetic susceptibility of NAs causes an interaction with the external magnetic field. This motional anisotropy is responsible for non-zero D contributions to Js. Here, we calculated the field-induced D contributions to 33 structurally relevant scalar coupling constants as a function of magnetic field strength, temperature and NA fragment size. We identified two classes of Js, namely 1JCH and 3JHH couplings, whose quantitative interpretation is notably biased by NA motional anisotropy. For these couplings, the magnetic field-induced dipolar contributions were found to exceed the typical experimental error in J-coupling determinations by a factor of two or more and to produce considerable over- or under-estimations of the J coupling-related torsion angles, especially at magnetic field strengths >12 T and for NA fragments longer than 12 bp. We show that if the non-zero D contributions to J are not properly accounted for, they might cause structural artifacts/bias in NA studies that use solution NMR spectroscopy. Electronic supplementary material The online version of this article (doi:10.1007/s10858-015-0005-x) contains supplementary material, which is available to authorized users.

Signaling cascades depend on scaffold proteins that regulate the assembly of multiprotein complexes. Missense mutations in scaffold proteins are frequent in human cancer, but their relevance and mode of action are poorly understood. Here we show that cancer point mutations in the scaffold protein Axin derail Wnt signaling and promote tumor growth in vivo through a gain-of-function mechanism. The effect is conserved for both the human and Drosophila proteins. Mutated Axin forms nonamyloid nanometer-scale aggregates decorated with disordered tentacles, which 'rewire' the Axin interactome. Importantly, the tumor-suppressor activity of both the human and Drosophila Axin cancer mutants is rescued by preventing aggregation of a single nonconserved segment. Our findings establish a new paradigm for misregulation of signaling in cancer and show that targeting aggregation-prone stretches in mutated scaffolds holds attractive potential for cancer treatment.

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.

Kallikrein-related peptidases (KLKs) are crucial for epidermal barrier function and are involved in the proteolytic regulation of the desquamation process. Elevated KLK levels were reported in atopic dermatitis. In skin, the proteolytic activity of KLKs is regulated by specific inhibitors of the serine protease inhibitor of Kazal-type (SPINK) family. SPINK6 was shown to be expressed in human stratum corneum and is able to inhibit several KLKs such as KLK4, -5, -12, -13 and -14. In order to understand the structural traits of the specific inhibition we solved the structure of SPINK6 in solution by NMR-spectroscopy and studied its interaction with KLKs. Thereby, beside the conserved binding mode, we identified an alternate binding mode which has so far not been observed for SPINK inhibitors.

Phospho-MurNAc-pentapeptide translocase (MraY) catalyzes the synthesis of Lipid I, a bacterial peptidoglycan precursor. As such, MraY is essential for bacterial survival and therefore is an ideal target for developing novel antibiotics. However, the understanding of its catalytic mechanism, despite the recently determined crystal structure, remains limited. In the present study, the kinetic properties of Bacillus subtilis MraY (BsMraY) were investigated by fluorescence enhancement using dansylated UDP-Mur-NAc-pentapeptide and heptaprenyl phosphate (C35-P, shortchain homolog of undecaprenyl phosphate, the endogenous substrate of MraY) as second substrate. Varying the concentrations of both of these substrates and fitting the kinetics data to two-substrate models showed that the concomitant binding of both UDP-MurNAc-pentapeptide-DNS and C35-P to the enzyme is required before the release of the two products, Lipid I and UMP. We built a model of BsMraY and performed docking studies with the substrate C35-P to further deepen our understanding of how MraY accommodates this lipid substrate. Based on these modeling studies, a novel catalytic role was put forward for a fully conserved histidine residue in MraY (His-289 in BsMraY), which has been experimentally confirmed to be essential for MraY activity. Using the current model of BsMraY, we propose that a small conformational change is necessary to relocate the His-289 residue, such that the translocase reaction can proceed via a nucleophilic attack of the phosphate moiety of C35-P on bound UDP-MurNAc-pentapeptide.

Heteronuclear and homonuclear direct (D) and indirect (J) spin-spin interactions are important sources of structural information about nucleic acids (NAs). The Hamiltonians for the D and J interactions have the same functional form; thus, the experimentally measured apparent spin-spin coupling constant corresponds to a sum of J and D. In biomolecular NMR studies, it is commonly presumed that the dipolar contributions to Js are effectively canceled due to random molecular tumbling. However, in strong magnetic fields, such as those employed for NMR analysis, the tumbling of NA fragments is anisotropic because the inherent magnetic susceptibility of NAs causes an interaction with the external magnetic field. This motional anisotropy is responsible for non-zero D contributions to Js. Here, we calculated the field-induced D contributions to 33 structurally relevant scalar coupling constants as a function of magnetic field strength, temperature and NA fragment size. We identified two classes of Js, namely (1)JCH and (3)JHH couplings, whose quantitative interpretation is notably biased by NA motional anisotropy. For these couplings, the magnetic field-induced dipolar contributions were found to exceed the typical experimental error in J-coupling determinations by a factor of two or more and to produce considerable over- or under-estimations of the J coupling-related torsion angles, especially at magnetic field strengths12 T and for NA fragments longer than 12 bp. We show that if the non-zero D contributions to J are not properly accounted for, they might cause structural artifacts/bias in NA studies that use solution NMR spectroscopy.

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set.

Molecular-docking programs coupled with suitable scoring functions are now established and very useful tools enabling computational chemists to rapidly screen large chemical databases and thereby to identify promising candidate compounds for further experimental processing. In a broader scenario, predicting binding affinity is one of the most critical and challenging components of computer-aided structure-based drug design. The development of a molecular docking scoring function which in principle could combine both features, namely ranking putative poses and predicting complex affinity, would be of paramount importance. Here, we systematically investigated the performance of the MM-PBSA approach, using two different Poisson-Boltzmann solvers (APBS and DelPhi), in the currently rising field of protein-peptide interactions (PPIs), identifying the correct binding conformations of 19 different protein-peptide complexes and predicting their binding free energies. First, we scored the decoy structures from HADDOCK calculation via the MM-PBSA approach in order to assess the capability of retrieving near-native poses in the best-scoring clusters and of evaluating the corresponding free energies of binding. MM-PBSA behaves well in finding the poses corresponding to the lowest binding free energy, however the built-in HADDOCK score shows a better performance. In order to improve the MM-PBSA-based scoring function, we dampened the MM-PBSA solvation and coulombic terms by 0.2, as proposed in the HADDOCK score and LIE approaches. The new dampened MM-PBSA (dMM-PBSA) outperforms the original MM-PBSA and ranks the decoys structures as the HADDOCK score does. Second, we found a good correlation between the dMM-PBSA and HADDOCK scores for the near-native clusters of each system and the experimental binding energies, respectively. Therefore, we propose a new scoring function, dMM-PBSA, to be used together with the built-in HADDOCK score in the context of protein-peptide docking simulations.

The human Argonaute 2 (hAgo2) protein is a key player of RNA interference (RNAi). Upon complex formation with small non-coding RNAs, the protein initially interacts with the 5′-end of a given guide RNA through multiple interactions within the MID domain. This interaction has been reported to show a strong bias for U and A over C and G at the 5′-position. Performing molecular dynamics simulations of binary hAgo2/OH–guide–RNA complexes, we show that hAgo2 is a highly flexible protein capable of binding to guide strands with all four possible 5′-bases. Especially, in the case of C and G this is associated with rather large individual conformational rearrangements affecting the MID, PAZ and even the N-terminal domains to different degrees. Moreover, a 5′-G induces domain motions in the protein, which trigger a previously unreported interaction between the 5′-base and the L2 linker domain. Combining our in silico analyses with biochemical studies of recombinant hAgo2, we find that, contrary to previous observations, hAgo2 is capable of functionally accommodating guide strands regardless of the 5′-base.

Cryo-electron microscopy provides fascinating structural insight into large macromolecular machines at increasing detail. Despite significant advances in the field, the resolution of the resulting three-dimensional images is still typically insufficient for . de novo model building. To bridge the resolution gap and give an atomic interpretation to the data, high-resolution models are typically placed into the density as rigid bodies. Unfortunately, this is often done manually using graphics software, a subjective method that can lead to over-interpretation of the data. A more objective approach is to perform an exhaustive cross-correlation-based search to fit subunits into the density. Here we show, using five experimental ribosome maps ranging in resolution from 5.5 to 6.9. Å, that cross-correlation-based fitting is capable of successfully fitting subunits correctly in the density for over 90% of the cases. Importantly, we provide indicators for the reliability and ambiguity of a fit, using the Fisher z-transformation and its associated confidence intervals, giving a formal approach to identify over-interpreted regions in the density. In addition, we quantify the resolution requirement for a successful fit as a function of the subunit size. For larger subunits the resolution of the data can be down-filtered to 20. Å while still retaining an unambiguous fit. We leverage this information through the use of multi-scale image pyramids to accelerate the search up to 30-fold on CPUs and 40-fold on GPUs at a negligible loss in success rate. We implemented this approach in our rigid-body fitting software PowerFit, which can be freely downloaded from . https://github.com/haddocking/powerfit.