M-ZDOCK: a grid-based approach for Cn symmetric multimer docking

Sensory Rhodopsin I and Sensory Rhodopsin II Form Trimers of Dimers in Complex with their Cognate Transducers

Archaeal photoreceptors consist of sensory rhodopsins in complex with their cognate transducers. After light excitation, a two-component signaling chain is activated, which is homologous to the chemotactic signaling cascades in enterobacteria. The latter system has been studied in detail. From structural and functional studies, a picture emerges which includes stable signaling complexes, which assemble to receptor arrays displaying hexagonal structural elements. At this higher order structural level, signal amplification and sensory adaptation occur. Here, we describe electron microscopy data, which show that also the archaeal phototaxis receptors sensory rhodopsin I and II in complex with their cognate transducers can form hexagonal lattices even in the presence of a detergent. This result could be confirmed by molecular dynamics calculations, which revealed similar structural elements. Calculations of the global modes of motion displayed one mode, which resembles the "U"-"V" transition of the NpSRII:NpHtrII complex, which was previously argued to represent a functionally relevant global conformational change accompanying the activation process [Ishchenko et al. (2013) J. Photochem. Photobiol. B 123, 55-58]. A model of cooperativity at the transmembrane level is discussed.

Oligomer Formation Propensities of Dimeric Bundle Peptides Correlate with Cell Penetration Abilities

LK-3, an amphipathic dimeric peptide linked by two disulfide bonds, and related isomeric bundles were synthesized, and their cell penetrating abilities were investigated. The measurements using size exclusion chromatography and dynamic light scattering show that LK-3 and its isomers form cell penetrating oligomers. Calculations, performed for various types of peptide isomers, elucidate a strong correlation between the amphipathic character of dimers and cell penetration ability. The results suggest that the amphipathicities of LK-3 and related bundle dimers are responsible for their oligomerization propensities which in turn determine their cell penetrating abilities. The observations made in this study provide detailed information about the mechanism of cell uptake of LK-3 and suggest a plausible insight of the early stage of nanoparticle formation of the cell penetrating amphipathic peptides.

HSYMDOCK: a docking web server for predicting the structure of protein homo-oligomers with Cn or Dn symmetry

A major subclass of protein-protein interactions is formed by homo-oligomers with certain symmetry. Therefore, computational modeling of the symmetric protein complexes is important for understanding the molecular mechanism of related biological processes. Although several symmetric docking algorithms have been developed for Cn symmetry, few docking servers have been proposed for Dn symmetry. Here, we present HSYMDOCK, a web server of our hierarchical symmetric docking algorithm that supports both Cn and Dn symmetry. The HSYMDOCK server was extensively evaluated on three benchmarks of symmetric protein complexes, including the 20 CASP11-CAPRI30 homo-oligomer targets, the symmetric docking benchmark of 213 Cn targets and 35 Dn targets, and a nonredundant test set of 55 transmembrane proteins. It was shown that HSYMDOCK obtained a significantly better performance than other similar docking algorithms. The server supports both sequence and structure inputs for the monomer/subunit. Users have an option to provide the symmetry type of the complex, or the server can predict the symmetry type automatically. The docking process is fast and on average consumes 10∼20 min for a docking job. The HSYMDOCK web server is available at http://huanglab.phys.hust.edu.cn/hsymdock/.

Romo1 is a mitochondrial nonselective cation channel with viroporin-like characteristics

Romo1 regulates mitochondrial reactive oxygen species production and acts as an essential redox sensor in mitochondrial dynamics. Lee et al. demonstrate that Romo1 is a unique mitochondrial ion channel with viroporin-like characteristics that distinguish Romo1 from other known eukaryotic ion channels.

Reactive oxygen species (ROS) modulator 1 (Romo1) is a nuclear-encoded mitochondrial inner membrane protein known to regulate mitochondrial ROS production and to act as an essential redox sensor in mitochondrial dynamics. Although its physiological roles have been studied for a decade, the biophysical mechanisms that explain these activities of Romo1 are unclear. In this study, we report that Romo1 is a unique mitochondrial ion channel that differs from currently identified eukaryotic ion channels. Romo1 is a highly conserved protein with structural features of class II viroporins, which are virus-encoded nonselective cation channels. Indeed, Romo1 forms a nonselective cation channel with its amphipathic helical transmembrane domain necessary for pore-forming activity. Notably, channel activity was specifically inhibited by Fe²⁺ ions, an essential transition metal ion in ROS metabolism. Using structural bioinformatics, we designed an experimental data–guided structural model of Romo1 with a rational hexameric structure. We propose that Romo1 establishes a new category of viroporin-like nonselective cation channel in eukaryotes.

Lipophosphoglycan 3 From Leishmania infantum chagasi Binds Heparin With Micromolar Affinity

Leishmania infantum chagasi is an intracellular protozoan parasite responsible for visceral leishmaniasis, a fatal disease in humans. Heparin-binding proteins (HBPs) are proteins that bind to carbohydrates present in glycoproteins or glycolipids. Evidence suggests that HBPs present on Leishmania surface participate in the adhesion and invasion of parasites to tissues of both invertebrate and vertebrate hosts. In this study, we identified the product with an HSP90 (heat shock protein 90) domain encoded by lipophosphoglycan (LPG3) gene as a L infantum chagasi HBP (HBPLc). Structural analysis using the LPG3 recombinant protein suggests that it is organized as a tetramer. Binding analysis confirms that it is capable of binding heparin with micromolar affinity. Inhibition of adenosine triphosphatase activity in the presence of heparin, molecular modeling, and in silico docking analysis suggests that heparin-binding site superimposes with the adenosine triphosphate–binding site. Together, these results show new properties of LPG3 and suggest an important role in leishmaniasis.

Structural model of human dUTPase in complex with a novel proteinaceous inhibitor

Human deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase), essential for DNA integrity, acts as a survival factor for tumor cells and is a target for cancer chemotherapy. Here we report that the Staphylococcal repressor protein Stl_SaPIBov1 (Stl) forms strong complex with human dUTPase. Functional analysis reveals that this interaction results in significant reduction of both dUTPase enzymatic activity and DNA binding capability of Stl. We conducted structural studies to understand the mechanism of this mutual inhibition. Small-angle X-ray scattering (SAXS) complemented with hydrogen-deuterium exchange mass spectrometry (HDX-MS) data allowed us to obtain 3D structural models comprising a trimeric dUTPase complexed with separate Stl monomers. These models thus reveal that upon dUTPase-Stl complex formation the functional homodimer of Stl repressor dissociates, which abolishes the DNA binding ability of the protein. Active site forming dUTPase segments were directly identified to be involved in the dUTPase-Stl interaction by HDX-MS, explaining the loss of dUTPase activity upon complexation. Our results provide key novel structural insights that pave the way for further applications of the first potent proteinaceous inhibitor of human dUTPase.

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase.

Structure of the large terminase from a hyperthermophilic virus reveals a unique mechanism for oligomerization and ATP hydrolysis

The crystal structure of the large terminase from the Geobacillus stearothermophilus bacteriophage D6E shows a unique relative orientation of the N-terminal adenosine triphosphatase (ATPase) and C-terminal nuclease domains. This monomeric ‘initiation’ state with the two domains ‘locked’ together is stabilized via a conserved C-terminal arm, which may interact with the portal protein during motor assembly, as predicted for several bacteriophages. Further work supports the formation of an active oligomeric state: (i) AUC data demonstrate the presence of oligomers; (ii) mutational analysis reveals a trans-arginine finger, R158, indispensable for ATP hydrolysis; (iii) the location of this arginine is conserved with the HerA/FtsK ATPase superfamily; (iv) a molecular docking model of the pentamer is compatible with the location of the identified arginine finger. However, this pentameric model is structurally incompatible with the monomeric ‘initiation’ state and is supported by the observed increase in k_cat of ATP hydrolysis, from 7.8 ± 0.1 min⁻¹ to 457.7 ± 9.2 min⁻¹ upon removal of the C-terminal nuclease domain. Taken together, these structural, biophysical and biochemical data suggest a model where transition from the ‘initiation’ state into a catalytically competent pentameric state, is accompanied by substantial domain rearrangements, triggered by the removal of the C-terminal arm from the ATPase active site.

Novel Kunitz-like Peptides Discovered in the Zoanthid Palythoa caribaeorum through Transcriptome Sequencing

Palythoa caribaeorum (class Anthozoa) is a zoanthid that together jellyfishes, hydra, and sea anemones, which are venomous and predatory, belongs to the Phyllum Cnidaria. The distinguished feature in these marine animals is the cnidocytes in the body tissues, responsible for toxin production and injection that are used majorly for prey capture and defense. With exception for other anthozoans, the toxin cocktails of zoanthids have been scarcely studied and are poorly known. Here, on the basis of the analysis of P. caribaeorum transcriptome, numerous predicted venom-featured polypeptides were identified including allergens, neurotoxins, membrane-active, and Kunitz-like peptides (PcKuz). The three predicted PcKuz isotoxins (1-3) were selected for functional studies. Through computational processing comprising structural phylogenetic analysis, molecular docking, and dynamics simulation, PcKuz3 was shown to be a potential voltage gated potassium-channel inhibitor. PcKuz3 fitted well as new functional Kunitz-type toxins with strong antilocomotor activity as in vivo assessed in zebrafish larvae, with weak inhibitory effect toward proteases, as evaluated in vitro. Notably, PcKuz3 can suppress, at low concentration, the 6-OHDA-induced neurotoxicity on the locomotive behavior of zebrafish, which indicated PcKuz3 may have a neuroprotective effect. Taken together, PcKuz3 figures as a novel neurotoxin structure, which differs from known homologous peptides expressed in sea anemone. Moreover, the novel PcKuz3 provides an insightful hint for biodrug development for prospective neurodegenerative disease treatment.

Modeling the assembly order of multimeric heteroprotein complexes

Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes.

Exploring the association of rs10490924 polymorphism with age-related macular degeneration: An in silico approach

The polymorphism rs10490924 (A69S) in the age-related maculopathy susceptibility 2 (ARMS2) gene is highly associated with age-related macular degeneration, which is the leading cause of blindness among the elderly population. ARMS2 gene encodes a putative small (11 kDa) protein, which the function and localization of the ARMS2 protein remain under debate. For a better understanding of functional impacts of A69S mutation, we performed a detailed analysis of an ARMS2 sequence with a broad set of bioinformatics tools. In silico analysis was followed to predict the tertiary structure, putative binding site regions, and binding site residues. Also, the effects of this mutation on protein stability, aggregation propensity, and homodimerization were analyzed. Next, a molecular dynamic simulation was carried out to understand the dynamic behavior of wild-type, A69S, and phosphorylated A69S structures. The results showed alterations in the putative post-translational modification sites on the ARMS2 protein, due to the mutation. Furthermore, the stability of protein and putative homodimer conformations were affected by the mutation. Molecular dynamic simulation results revealed that A69S mutation enhances the rigidity of the ARMS2 structure and residue serine at position 69 is buried and may not be phosphorylated; however, phosphorylated serine enhances the flexibility of the ARMS2 structure. In conclusion, our study provides new insights into the deleterious effects of A69S mutation on the ARMS2 structure.

Template-based quaternary structure prediction of proteins using enhanced profile-profile alignments

Proteins often exist as their multimeric forms when they function as so‐called biological assemblies consisting of the specific number and arrangement of protein subunits. Consequently, elucidating biological assemblies is necessary to improve understanding of protein function. Template‐Based Modeling (TBM), based on known protein structures, has been used widely for protein structure prediction. Actually, TBM has become an increasingly useful approach in recent years because of the increased amounts of information related to protein amino acid sequences and three‐dimensional structures. An apparently similar situation exists for biological assembly structure prediction as protein complex structures in the PDB increase, although the inference of biological assemblies is not a trivial task. Many methods using TBM, including ours, have been developed for protein structure prediction. Using enhanced profile–profile alignments, we participated in the 12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP12), as the FONT team (Group # 480). Herein, we present experimental procedures and results of retrospective analyses using our approach for the Quaternary Structure Prediction category of CASP12. We performed profile–profile alignments of several types, based on FORTE, our profile–profile alignment algorithm, to identify suitable templates. Results show that these alignment results enable us to find templates in almost all possible cases. Moreover, we have come to understand the necessity of developing a model selection method that provides improved accuracy. Results also demonstrate that, to some extent, finding templates of protein complexes is useful even for MEDIUM and HARD assembly prediction.

Predictive and Experimental Approaches for Elucidating Protein-Protein Interactions and Quaternary Structures

The elucidation of protein-protein interactions is vital for determining the function and action of quaternary protein structures. Here, we discuss the difficulty and importance of establishing protein quaternary structure and review in vitro and in silico methods for doing so. Determining the interacting partner proteins of predicted protein structures is very time-consuming when using in vitro methods, this can be somewhat alleviated by use of predictive methods. However, developing reliably accurate predictive tools has proved to be difficult. We review the current state of the art in predictive protein interaction software and discuss the problem of scoring and therefore ranking predictions. Current community-based predictive exercises are discussed in relation to the growth of protein interaction prediction as an area within these exercises. We suggest a fusion of experimental and predictive methods that make use of sparse experimental data to determine higher resolution predicted protein interactions as being necessary to drive forward development.

Exploring the association of rs10490924 polymorphism with age-related macular degeneration: An in silico approach

The polymorphism rs10490924 (A69S) in the age-related maculopathy susceptibility 2 (ARMS2) gene is highly associated with age-related macular degeneration, which is the leading cause of blindness among the elderly population. The ARMS2 gene encodes a putative small (11kDa) protein, which the function and localization of the ARMS2 protein remain under debate. For a better understanding of functional impacts of the A69S mutation, we performed a detailed analysis of the ARMS2 sequence with a broad set of bioinformatics tools. In silico analysis was followed to predict the tertiary structure, putative binding site regions, and binding site residues. Also, the effects of this mutation on protein stability, aggregation propensity, and homodimerization were analyzed. Next, a molecular dynamic simulation was carried out to understand the dynamic behavior of wild-type, A69S, and phosphorylated A69S structures. The results showed alterations in the putative post-translational modification sites on the ARMS2 protein, due to the mutation. Furthermore, the stability of protein and putative homodimer conformations were affected by the mutation. Molecular dynamic simulation results revealed that the A69S mutation enhances the rigidity of the ARMS2 structure and residue serine at position 69 is buried and may not be phosphorylated; however, phosphorylated serine enhances the flexibility of the ARMS2 structure. In conclusion, our study provides new insights into the deleterious effects of the A69S mutation on the ARMS2 structure.

Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology

Cellular processes often depend on interactions between proteins and the formation of macromolecular complexes. The impairment of such interactions can lead to deregulation of pathways resulting in disease states, and it is hence crucial to gain insights into the nature of macromolecular assemblies. Detailed structural knowledge about complexes and protein-protein interactions is growing, but experimentally determined three-dimensional multimeric assemblies are outnumbered by complexes supported by non-structural experimental evidence. Here, we aim to fill this gap by modeling multimeric structures by homology, only using amino acid sequences to infer the stoichiometry and the overall structure of the assembly. We ask which properties of proteins within a family can assist in the prediction of correct quaternary structure. Specifically, we introduce a description of protein-protein interface conservation as a function of evolutionary distance to reduce the noise in deep multiple sequence alignments. We also define a distance measure to structurally compare homologous multimeric protein complexes. This allows us to hierarchically cluster protein structures and quantify the diversity of alternative biological assemblies known today. We find that a combination of conservation scores, structural clustering, and classical interface descriptors, can improve the selection of homologous protein templates leading to reliable models of protein complexes.

Signalling assemblies: the odds of symmetry

The assembly of proteins into complexes is fundamental to nearly all biological signalling processes. Symmetry is a dominant feature of the structures of experimentally determined protein complexes, observed in the vast majority of homomers and many heteromers. However, some asymmetric structures exist, and asymmetry also often forms transiently, intractable to traditional structure determination methods. Here, we explore the role of protein complex symmetry and asymmetry in cellular signalling, focusing on receptors, transcription factors and transmembrane channels, among other signalling assemblies. We highlight a recurrent tendency for asymmetry to be crucial for signalling function, often being associated with activated states. We conclude with a discussion of how consideration of protein complex symmetry and asymmetry has significant potential implications and applications for pharmacology and human disease.

The ClusPro web server for protein-protein docking

The ClusPro server (https://cluspro.org) is a widely used tool for protein-protein docking. The server provides a simple home page for basic use, requiring only two files in Protein Data Bank (PDB) format. However, ClusPro also offers a number of advanced options to modify the search; these include the removal of unstructured protein regions, application of attraction or repulsion, accounting for pairwise distance restraints, construction of homo-multimers, consideration of small-angle X-ray scattering (SAXS) data, and location of heparin-binding sites. Six different energy functions can be used, depending on the type of protein. Docking with each energy parameter set results in ten models defined by centers of highly populated clusters of low-energy docked structures. This protocol describes the use of the various options, the construction of auxiliary restraints files, the selection of the energy parameters, and the analysis of the results. Although the server is heavily used, runs are generally completed in <4 h.

Sketching of CD95 Oligomers by In Silico Investigations

This work aimed at building a 3D model of trimeric apo CD95. By combining different molecular modeling approaches and experimental information, we have been able to obtain a consensual organization of the complex. Our strategy permitted the construction of a plausible trimer, and to sketch the interface between protomers. The final model will guide further experimental investigations and understanding of CD95 structure and functions.

Molecular Docking at a Glance

The current chapter introduces different aspects of molecular docking technique in order to give an overview to the readers about the topics which will be dealt with throughout this volume. Like many other fields of science, molecular docking studies has experienced a lagging period of slow and steady increase in terms of acquiring attention of scientific community as well as its frequency of application, followed by a pronounced era of exponential expansion in theory, methodology, areas of application and performance due to developments in related technologies such as computational resources and theoretical as well as experimental biophysical methods. In the following sections the evolution of molecular docking will be reviewed and its different components including methods, search algorithms, scoring functions, validation of the methods, and area of applications plus few case studies will be touched briefly.

Computational design of self-assembling cyclic protein homo-oligomers

Self-assembling cyclic protein homo-oligomers play important roles in biology and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue pair transform method for assessing the design ability of a protein-protein interface. This method is sufficiently rapid to enable systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were experimentally characterized, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (4 homodimers, 6 homotrimers, 6 homotetramers and 1 homopentamer) had solution small angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each of these were shown to be very close to their design model.

PRISM-EM: template interface-based modelling of multi-protein complexes guided by cryo-electron microscopy density maps

The structures of protein assemblies are important for elucidating cellular processes at the molecular level. Three-dimensional electron microscopy (3DEM) is a powerful method to identify the structures of assemblies, especially those that are challenging to study by crystallography. Here, a new approach, PRISM-EM, is reported to computationally generate plausible structural models using a procedure that combines crystallographic structures and density maps obtained from 3DEM. The predictions are validated against seven available structurally different crystallographic complexes. The models display mean deviations in the backbone of <5 Å. PRISM-EM was further tested on different benchmark sets; the accuracy was evaluated with respect to the structure of the complex, and the correlation with EM density maps and interface predictions were evaluated and compared with those obtained using other methods. PRISM-EM was then used to predict the structure of the ternary complex of the HIV-1 envelope glycoprotein trimer, the ligand CD4 and the neutralizing protein m36.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking

Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex.

Revisiting the mechanism of coagulation factor XIII activation and regulation from a structure/functional perspective

The activation and regulation of coagulation Factor XIII (FXIII) protein has been the subject of active research for the past three decades. Although discrete evidence exists on various aspects of FXIII activation and regulation a combinatorial structure/functional view in this regard is lacking. In this study, we present results of a structure/function study of the functional chain of events for FXIII. Our study shows how subtle chronological submolecular changes within calcium binding sites can bring about the detailed transformation of the zymogenic FXIII to its activated form especially in the context of FXIIIA and FXIIIB subunit interactions. We demonstrate what aspects of FXIII are important for the stabilization (first calcium binding site) of its zymogenic form and the possible modes of deactivation (thrombin mediated secondary cleavage) of the activated form. Our study for the first time provides a structural outlook of the FXIIIA₂B₂ heterotetramer assembly, its association and dissociation. The FXIIIB subunits regulatory role in the overall process has also been elaborated upon. In summary, this study provides detailed structural insight into the mechanisms of FXIII activation and regulation that can be used as a template for the development of future highly specific therapeutic inhibitors targeting FXIII in pathological conditions like thrombosis.

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

Crystal structure of a TSH receptor monoclonal antibody: insight into Graves' disease pathogenesis

The TSH receptor (TSHR) A-subunit is more effective than the holoreceptor in inducing thyroid-stimulating antibodies (TSAb) that cause Graves' disease. A puzzling phenomenon is that 2 recombinant, eukaryotic forms of A-subunits (residues 22-289), termed active and inactive, are recognized mutually exclusively by pathogenic TSAb and mouse monoclonal antibody 3BD10, respectively. Understanding the structural difference between these TSHR A-subunit forms could provide insight into Graves' disease pathogenesis. The 3-dimensional structure of the active A-subunit (in complex with a human TSAb Fab, M22) is known, but the structural difference with inactive A-subunits is unknown. We solved the 3BD10 Fab 3-dimensional crystal structure. Guided by prior knowledge of a portion of its epitope, 3BD10 docked in silico with the known active TSHR-289 monomeric structure. Because both TSAb and 3BD10 recognize the active TSHR A-subunit monomer, this form of the molecule can be excluded as the basis for the active-inactive dichotomy, suggesting, instead a role for A-subunit quaternary structure. Indeed, in silico analysis revealed that M22, but not 3BD10, bound to a TSHR-289 trimer. In contrast, 3BD10, but not M22, bound to a TSHR-289 dimer. The validity of these models is supported experimentally by the temperature-dependent balance between active and inactive TSHR-289. In summary, we provide evidence for a structural basis to explain the conformational heterogeneity of TSHR A-subunits (TSHR-289). The pathophysiologic importance of these findings is that affinity maturation of pathogenic TSAb in Graves' disease is likely to involve a trimer of the shed TSHR A-subunit.

Spherical polar Fourier assembly of protein complexes with arbitrary point group symmetry

A novel fast Fourier transform-basedab initodocking algorithm calledSAMis presented, for building perfectly symmetrical models of protein complexes with arbitrary point group symmetry. The basic approach uses a novel and very fast one-dimensional symmetry-constrained spherical polar Fourier search to assemble cyclicCnsystems from a given protein monomer. Structures with higher-order (Dn,T,OandI) point group symmetries may be built using a subsequent symmetry-constrained Fourier domain search to assemble trimeric sub-units. The results reported here show that theSAMalgorithm can correctly assemble monomers of up to around 500 residues to produce a near-native complex structure with the given point group symmetry in 17 out of 18 test cases. TheSAMprogram may be downloaded for academic use at http://sam.loria.fr/.

Molecular dynamics of sialic acid analogues complex with cholera toxin and DFT optimization of ethylene glycol-mediated zinc nanocluster conjugation

Cholera is an infectious disease caused by cholera toxin (CT) protein of bacterium Vibrio cholerae. A sequence of sialic acid (N-acetylneuraminic acid, NeuNAc or Neu5Ac) analogues modified in its C-5 position is modelled using molecular modelling techniques and docked against the CT followed by molecular dynamics simulations. Docking results suggest better binding affinity of NeuNAc analogue towards the binding site of CT. The NeuNAc analogues interact with the active site residues GLU:11, TYR:12, HIS:13, GLY:33, LYS:34, GLU:51, GLN:56, HIE:57, ILE:58, GLN:61, TRP:88, ASN:90 and LYS:91 through intermolecular hydrogen bonding. Analogues N-glycolyl-NeuNAc, N-Pentanoyl-NeuNAc and N-Propanoyl-NeuNAc show the least XPGscore (docking score) of -9.90, -9.16, and -8.91, respectively, and glide energy of -45.99, -42.14 and -41.66 kcal/mol, respectively. Stable nature of CT-N-glycolyl-NeuNAc, CT-N-Pentanoyl-NeuNAc and CT-N-Propanoyl-NeuNAc complexes was verified through molecular dynamics simulations, each for 40 ns using the software Desmond. All the nine NeuNAc analogues show better score for drug-like properties, so could be considered as suitable candidates for drug development for cholera infection. To improve the enhanced binding mode of NeuNAc analogues towards CT, the nine NeuNAc analogues are conjugated with Zn nanoclusters through ethylene glycol (EG) as carriers. The NeuNAc analogues conjugated with EG-Zn nanoclusters show better binding energy towards CT than the unconjugated nine NeuNAc analogues. The electronic structural optimization of EG-Zn nanoclusters was carried out for optimizing their performance as better delivery vehicles for NeuNAc analogues through density functional theory calculations. These sialic acid analogues may be considered as novel leads for the design of drug against cholera and the EG-Zn nanocluster may be a suitable carrier for sialic acid analogues.

Structure determination of helical filaments by solid-state NMR spectroscopy

The controlled formation of filamentous protein complexes plays a crucial role in many biological systems and represents an emerging paradigm in signal transduction. The mitochondrial antiviral signaling protein (MAVS) is a central signal transduction hub in innate immunity that is activated by a receptor-induced conversion into helical superstructures (filaments) assembled from its globular caspase activation and recruitment domain. Solid-state NMR (ssNMR) spectroscopy has become one of the most powerful techniques for atomic resolution structures of protein fibrils. However, for helical filaments, the determination of the correct symmetry parameters has remained a significant hurdle for any structural technique and could thus far not be precisely derived from ssNMR data. Here, we solved the atomic resolution structure of helical MAVS(CARD) filaments exclusively from ssNMR data. We present a generally applicable approach that systematically explores the helical symmetry space by efficient modeling of the helical structure restrained by interprotomer ssNMR distance restraints. Together with classical automated NMR structure calculation, this allowed us to faithfully determine the symmetry that defines the entire assembly. To validate our structure, we probed the protomer arrangement by solvent paramagnetic resonance enhancement, analysis of chemical shift differences relative to the solution NMR structure of the monomer, and mutagenesis. We provide detailed information on the atomic contacts that determine filament stability and describe mechanistic details on the formation of signaling-competent MAVS filaments from inactive monomers.

Predicted binding site information improves model ranking in protein docking using experimental and computer-generated target structures

Background

Protein-protein interactions (PPIs) mediate the vast majority of biological processes, therefore, significant efforts have been directed to investigate PPIs to fully comprehend cellular functions. Predicting complex structures is critical to reveal molecular mechanisms by which proteins operate. Despite recent advances in the development of new methods to model macromolecular assemblies, most current methodologies are designed to work with experimentally determined protein structures. However, because only computer-generated models are available for a large number of proteins in a given genome, computational tools should tolerate structural inaccuracies in order to perform the genome-wide modeling of PPIs.

Results

To address this problem, we developed eRank^PPI, an algorithm for the identification of near-native conformations generated by protein docking using experimental structures as well as protein models. The scoring function implemented in eRank^PPI employs multiple features including interface probability estimates calculated by eFindSite^PPI and a novel contact-based symmetry score. In comparative benchmarks using representative datasets of homo- and hetero-complexes, we show that eRank^PPI consistently outperforms state-of-the-art algorithms improving the success rate by ~10 %.

Conclusions

eRank^PPI was designed to bridge the gap between the volume of sequence data, the evidence of binary interactions, and the atomic details of pharmacologically relevant protein complexes. Tolerating structure imperfections in computer-generated models opens up a possibility to conduct the exhaustive structure-based reconstruction of PPI networks across proteomes. The methods and datasets used in this study are available at www.brylinski.org/erankppi.

Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis

Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors.

Achaea and bacteria can “see” and “sniffle”, they have photo- and chemosensors that measure the environment. On the cell poles, these sensor proteins form large arrays built of several thousands of different receptors. The receptors comprise extracellular or transmembrane sensory domains and elongated homodimeric coiled-coil bundles, which transduce the signals from the membrane across ~20 nm to a conserved cytoplasmic signaling subdomain in an unknown manner. In our study we performed coarse-grained molecular dynamics simulations of the phototactic receptor/transducer complex from Natronomonas pharaonis. Comparing fully methylated and demethylated complexes reveals an interconversion between states of different dynamics along the coiled-coil bundle, which might represent the essential characteristics of the signal transfer from the membrane to the binding sites of the downstream kinase CheA.

Molecular logic of neuronal self-recognition through protocadherin domain interactions

Self-avoidance, a process preventing interactions of axons and dendrites from the same neuron during development, is mediated in vertebrates through the stochastic single-neuron expression of clustered protocadherin protein isoforms. Extracellular cadherin (EC) domains mediate isoform-specific homophilic binding between cells, conferring cell recognition through a poorly understood mechanism. Here, we report crystal structures for the EC1-EC3 domain regions from four protocadherin isoforms representing the α, β, and γ subfamilies. All are rod shaped and monomeric in solution. Biophysical measurements, cell aggregation assays, and computational docking reveal that trans binding between cells depends on the EC1-EC4 domains, which interact in an antiparallel orientation. We also show that the EC6 domains are required for the formation of cis-dimers. Overall, our results are consistent with a model in which protocadherin cis-dimers engage in a head-to-tail interaction between EC1-EC4 domains from apposed cell surfaces, possibly forming a zipper-like protein assembly, and thus providing a size-dependent self-recognition mechanism.

Dimeric interactions and complex formation using direct coevolutionary couplings

We develop a procedure to characterize the association of protein structures into homodimers using coevolutionary couplings extracted from Direct Coupling Analysis (DCA) in combination with Structure Based Models (SBM). Identification of dimerization contacts using DCA is more challenging than intradomain contacts since direct couplings are mixed with monomeric contacts. Therefore a systematic way to extract dimerization signals has been elusive. We provide evidence that the prediction of homodimeric complexes is possible with high accuracy for all the cases we studied which have rich sequence information. For the most accurate conformations of the structurally diverse dimeric complexes studied the mean and interfacial RMSDs are 1.95Å and 1.44Å, respectively. This methodology is also able to identify distinct dimerization conformations as for the case of the family of response regulators, which dimerize upon activation. The identification of dimeric complexes can provide interesting molecular insights in the construction of large oligomeric complexes and be useful in the study of aggregation related diseases like Alzheimer's or Parkinson's.

Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces

Macromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom-level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins. In this study, we propose a novel combinatorial greedy algorithm for assembling large oligomeric complexes from information on the approximate position of interaction interfaces of pairs of monomers in the complex. Prior information on complex symmetry is not required but rather the symmetry is inferred during assembly. We implement an efficient geometric score, the transformation match score, that bypasses the model ranking problems of state-of-the-art scoring functions by scoring the similarity between the inferred dimers of the same monomer simultaneously with different binding partners in a (sub)complex with a set of pregenerated docking poses. We compiled a diverse benchmark set of 308 homo and heteromeric complexes containing 6 to 60 monomers. To explore the applicability of the method, we considered 48 sets of parameters and selected those three sets of parameters, for which the algorithm can correctly reconstruct the maximum number, namely 252 complexes (81.8%) in, at least one of the respective three runs. The crossvalidation coverage, that is, the mean fraction of correctly reconstructed benchmark complexes during crossvalidation, was 78.1%, which demonstrates the ability of the presented method to correctly reconstruct topology of a large variety of biological complexes.

Structure and mechanism of the ATPase that powers viral genome packaging

Many viruses package their genomes into procapsids using an ATPase machine that is among the most powerful known biological motors. However, how this motor couples ATP hydrolysis to DNA translocation is still unknown. Here, we introduce a model system with unique properties for studying motor structure and mechanism. We describe crystal structures of the packaging motor ATPase domain that exhibit nucleotide-dependent conformational changes involving a large rotation of an entire subdomain. We also identify the arginine finger residue that catalyzes ATP hydrolysis in a neighboring motor subunit, illustrating that previous models for motor structure need revision. Our findings allow us to derive a structural model for the motor ring, which we validate using small-angle X-ray scattering and comparisons with previously published data. We illustrate the model's predictive power by identifying the motor's DNA-binding and assembly motifs. Finally, we integrate our results to propose a mechanistic model for DNA translocation by this molecular machine.

DockStar: a novel ILP-based integrative method for structural modeling of multimolecular protein complexes

MOTIVATION

Atomic resolution modeling of large multimolecular assemblies is a key task in Structural Cell Biology. Experimental techniques can provide atomic resolution structures of single proteins and small complexes, or low resolution data of large multimolecular complexes.

RESULTS

We present a novel integrative computational modeling method, which integrates both low and high resolution experimental data. The algorithm accepts as input atomic resolution structures of the individual subunits obtained from X-ray, NMR or homology modeling, and interaction data between the subunits obtained from mass spectrometry. The optimal assembly of the individual subunits is formulated as an Integer Linear Programming task. The method was tested on several representative complexes, both in the bound and unbound cases. It placed correctly most of the subunits of multimolecular complexes of up to 16 subunits and significantly outperformed the CombDock and Haddock multimolecular docking methods.

AVAILABILITY AND IMPLEMENTATION

http://bioinfo3d.cs.tau.ac.il/DockStar

CONTACT

naamaamir@mail.tau.ac.il or wolfson@tau.ac.il

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

An integrative approach to the study of filamentous oligomeric assemblies, with application to RecA

Oligomeric macromolecules in the cell self-organize into a wide variety of geometrical motifs such as helices, rings or linear filaments. The recombinase proteins involved in homologous recombination present many such assembly motifs. Here, we examine in particular the polymorphic characteristics of RecA, the most studied member of the recombinase family, using an integrative approach that relates local modes of monomer/monomer association to the global architecture of their screw-type organization. In our approach, local modes of association are sampled via docking or Monte Carlo simulations. This enables shedding new light on fiber morphologies that may be adopted by the RecA protein. Two distinct RecA helical morphologies, the so-called "extended" and "compressed" forms, are known to play a role in homologous recombination. We investigate the variability within each form in terms of helical parameters and steric accessibility. We also address possible helical discontinuities in RecA filaments due to multiple monomer-monomer association modes. By relating local interface organization to global filament morphology, the strategies developed here to study RecA self-assembly are particularly well suited to other DNA-binding proteins and to filamentous protein assemblies in general.

Hydrophobin film structure for HFBI and HFBII and mechanism for accelerated film formation

Hydrophobins represent an important group of proteins from both a biological and nanotechnological standpoint. They are the means through which filamentous fungi affect their environment to promote growth, and their properties at interfaces have resulted in numerous applications. In our study we have combined protein docking, molecular dynamics simulation, and electron cryo-microscopy to gain atomistic level insight into the surface structure of films composed of two class II hydrophobins: HFBI and HFBII produced by Trichoderma reesei. Together our results suggest a unit cell composed of six proteins; however, our computational results suggest P6 symmetry, while our experimental results show P3 symmetry with a unit cell size of 56 Å. Our computational results indicate the possibility of an alternate ordering with a three protein unit cell with P3 symmetry and a smaller unit cell size, and we have used a Monte Carlo simulation of a spin model representing the hydrophobin film to show how this alternate metastable structure may play a role in increasing the rate of surface coverage by hydrophobin films, possibly indicating a mechanism of more general significance to both biology and nanotechnology.

Filamentous fungi release a specific type of protein, belonging to a protein family known as “hydrophobins” into their environment to control interfaces in a fashion that promotes growth. Such protein coatings are the mechanism that allows for the mycelia to grow out of the water and into the air. When these hydrophobins form films at the air-water interface and on the surface of solid objects immersed in water, they impart properties to those surfaces that has led to their use in a wide range of industrial applications. Of particular interest is the properties they impart to air liquid interfaces, and as a mechanism to bring protective materials to coat nanoparticles in nanotechnology applications. A more detailed knowledge of the structure of these surfaces will allow for augmentation of their function that is possible through genetic engineering of the hydrophobins themselves. In this study we have combined computational and experimental methods to develop atomistic level insight into the structure of this surface for two important hydrophobins: HFBI and HFBII of Trichoderma reesei. In addition to insight into the surface structure, we have uncovered an intriguing possible new mechanism for film formation, which may explain some of the striking properties of hydrophobin films, and could be extended to a more general mechanism.

Modeling protein assemblies in the proteome

Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high- and low-resolution scales. Existing computational methods have made substantial progress toward this aim; however, current approaches are still limited. Some involve manual adjustment of experimental data; some are automated docking methods, which are computationally expensive and not applicable to large-scale proteome studies; and still others exploit the symmetry of the complexes and thus are not applicable to nonsymmetrical complexes. Our study aims to take steps toward overcoming these limitations. We have developed a strategy for the construction of protein assemblies computationally based on binary interactions predicted by a motif-based protein interaction prediction tool, PRISM (Protein Interactions by Structural Matching). Previously, we have shown its power in predicting pairwise interactions. Here we take a step toward multimolecular assemblies, reflecting the more prevalent cellular scenarios. With this method we are able to construct homo-/hetero-complexes and symmetric/asymmetric complexes without a limitation on the number of components. The method considers conformational changes and is applicable to large-scale studies. We also exploit electron microscopy density maps to select a solution from among the predictions. Here we present the method, illustrate its results, and highlight its current limitations.

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

Background

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units.

Results

Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures.

Conclusions

Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers

SUMMARY

Protein-protein interactions are essential to cellular and immune function, and in many cases, because of the absence of an experimentally determined structure of the complex, these interactions must be modeled to obtain an understanding of their molecular basis. We present a user-friendly protein docking server, based on the rigid-body docking programs ZDOCK and M-ZDOCK, to predict structures of protein-protein complexes and symmetric multimers. With a goal of providing an accessible and intuitive interface, we provide options for users to guide the scoring and the selection of output models, in addition to dynamic visualization of input structures and output docking models. This server enables the research community to easily and quickly produce structural models of protein-protein complexes and symmetric multimers for their own analysis.

AVAILABILITY

The ZDOCK server is freely available to all academic and non-profit users at: http://zdock.umassmed.edu. No registration is required.

Macromolecular symmetric assembly prediction using swarm intelligence dynamic modeling

Proteins often assemble in multimeric complexes to perform a specific biologic function. However, trapping these high-order conformations is difficult experimentally. Therefore, predicting how proteins assemble using in silico techniques can be of great help. The size of the associated conformational space and the fact that proteins are intrinsically flexible structures make this optimization problem extremely challenging. Nonetheless, known experimental spatial restraints can guide the search process, contributing to model biologically relevant states. We present here a swarm intelligence optimization protocol able to predict the arrangement of protein symmetric assemblies by exploiting a limited amount of experimental restraints and steric interactions. Importantly, within this scheme the native flexibility of each protein subunit is taken into account as extracted from molecular dynamics (MD) simulations. We show that this is a key ingredient for the prediction of biologically functional assemblies when, upon oligomerization, subunits explore activated states undergoing significant conformational changes.