HingeProt: automated prediction of hinges in protein structures

Flexible structural arrangement and DNA-binding properties of protein p6 from Bacillus subtillis phage φ29

The genome-organizing protein p6 of Bacillus subtilis bacteriophage φ29 plays an essential role in viral development by activating the initiation of DNA replication and participating in the early-to-late transcriptional switch. These activities require the formation of a nucleoprotein complex in which the DNA adopts a right-handed superhelix wrapping around a multimeric p6 scaffold, restraining positive supercoiling and compacting the viral genome. Due to the absence of homologous structures, prior attempts to unveil p6's structural architecture failed. Here, we employed AlphaFold2 to engineer rational p6 constructs yielding crystals for three-dimensional structure determination. Our findings reveal a novel fold adopted by p6 that sheds light on its self-association mechanism and its interaction with DNA. By means of protein-DNA docking and molecular dynamic simulations, we have generated a comprehensive structural model for the nucleoprotein complex that consistently aligns with its established biochemical and thermodynamic parameters. Besides, through analytical ultracentrifugation, we have confirmed the hydrodynamic properties of the nucleocomplex, further validating in solution our proposed model. Importantly, the disclosed structure not only provides a highly accurate explanation for previously experimental data accumulated over decades, but also enhances our holistic understanding of the structural and functional attributes of protein p6 during φ29 infection.

Macromolecular crowding impact on anti-CRISPR AcrIIC3/NmeCas9 complex: Insights from scaled particle theory, molecular dynamics, and elastic networks models

The coupling of Cas9 and its inhibitor AcrIIC3, both from the bacterium Neisseria meningitidis (Nme), form a homodimer of the (NmeCas9/AcrIIC3)₂ type. This coupling was studied to assess the impact of their interaction with the crowders in the following environments: (1) homogeneous crowded, (2) heterogeneous, and (3) microheterogeneous cytoplasmic. For this, statistical thermodynamic models based on the scaled particle theory (SPT) were used, considering the attractive and repulsive protein-crowders contributions and the stability of the formation of spherocylindrical homodimers and the effects of changes in the size of spherical dimers were estimated. Studies based on models of dynamics, elastic networks, and statistical potentials to the formation of complexes NmeCas9/AcrIIC3 using PEG as the crowding agent support the predictions from SPT. Macromolecular crowding stabilizes the formation of the dimers, being more significant when the attractive protein-crowder interactions are weaker and the crowders are smaller. The coupling is favored towards the formation of spherical and compact dimers due to crowding addition (excluded-volume effects) and the thermodynamic stability of the dimers is markedly dependent on the size of the crowders. These results support the experimental mechanistic proposal of inhibition of NmeCas9 mediated by AcrIIC3.

Intrinsic Dynamics of the ClpXP Proteolytic Machine Using Elastic Network Models

ClpXP complex is an ATP-dependent mitochondrial matrix protease that binds, unfolds, translocates, and subsequently degrades specific protein substrates. Its mechanisms of operation are still being debated, and several have been proposed, including the sequential translocation of two residues (SC/2R), six residues (SC/6R), and even long-pass probabilistic models. Therefore, it has been suggested to employ biophysical-computational approaches that can determine the kinetics and thermodynamics of the translocation. In this sense, and based on the apparent inconsistency between structural and functional studies, we propose to apply biophysical approaches based on elastic network models (ENM) to study the intrinsic dynamics of the theoretically most probable hydrolysis mechanism. The proposed models ENM suggest that the ClpP region is decisive for the stabilization of the ClpXP complex, contributing to the flexibility of the residues adjacent to the pore, favoring the increase in pore size and, therefore, with the energy of interaction of its residues with a larger portion of the substrate. It is predicted that the complex may undergo a stable configurational change once assembled and that the deformability of the system once assembled is oriented, to increase the rigidity of the domains of each region (ClpP and ClpX) and to gain flexibility of the pore. Our predictions could suggest under the conditions of this study the mechanism of the interaction of the system, of which the substrate passes through the unfolding of the pore in parallel with a folding of the bottleneck. The variations in the distance calculated by molecular dynamics could allow the passage of a substrate with a size equivalent to ∼3 residues. The theoretical behavior of the pore and the stability and energy of binding to the substrate based on ENM models suggest that in this system, there are thermodynamic, structural, and configurational conditions that allow a possible translocation mechanism that is not strictly sequential.

Dynamics of the secreted frizzled related protein Sizzled and potential implications for binding to bone morphogenetic protein-1 (BMP-1)

Sizzled (Szl) is both a secreted frizzled related protein (sFRP) and a naturally occurring inhibitor of the zinc metalloproteinase bone morphogenetic protein-1 (BMP-1), a key regulator of extracellular matrix assembly and growth factor activation. Here we present a new crystal structure for Szl which differs from that previously reported by a large scale (90°) hinge rotation between its cysteine-rich and netrin-like domains. We also present results of a molecular docking analysis showing interactions likely to be involved in the inhibition of BMP-1 activity by Szl. When compared with known structures of BMP-1 in complex with small molecule inhibitors, this reveals features that may be helpful in the design of new inhibitors to prevent the excessive accumulation of extracellular matrix that is the hallmark of fibrotic diseases.

Interaction of the new inhibitor paxlovid (PF-07321332) and ivermectin with the monomer of the main protease SARS-CoV-2: A volumetric study based on molecular dynamics, elastic networks, classical thermodynamics and SPT

The COVID-19 pandemic has accelerated the study of drugs, most notably ivermectin and more recently Paxlovid (PF-07321332) which is in phase III clinical trials with experimental data showing covalent binding to the viral protease M^pro. Theoretical developments of catalytic site-directed docking support thermodynamically feasible non-covalent binding to M^pro. Here we show that Paxlovid binds non-covalently at regions other than the catalytic sites with energies stronger than reported and at the same binding site as the ivermectin B1a homologue, all through theoretical methodologies, including blind docking. We volumetrically characterize the non-covalent interaction of the ivermectin homologues (avermectins B1a and B1b) and Paxlovid with the mM^pro monomer, through molecular dynamics and scaled particle theory (SPT). Using the fluctuation-dissipation theorem (FDT), we estimated the electric dipole moment fluctuations at the surface of each of complex involved in this study, with similar trends to that observed in the interaction volume. Using fluctuations of the intrinsic volume and the number of flexible fragments of proteins using anisotropic and Gaussian elastic networks (ANM+GNM) suggests the complexes with ivermectin are more dynamic and flexible than the unbound monomer. In contrast, the binding of Paxlovid to mM^pro shows that the mM^pro-PF complex is the least structurally dynamic of all the species measured in this investigation. The results support a differential molecular mechanism of the ivermectin and PF homologues in the mM^pro monomer. Finally, the results showed that Paxlovid despite beingbound in different sites through covalent or non-covalent forms behaves similarly in terms of its structural flexibility and volumetric behaviour.

Secretagogin is a Ca2+-dependent stress-responsive chaperone that may also play a role in aggregation-based proteinopathies

Secretagogin (SCGN) is a three-domain hexa-EF-hand Ca²⁺-binding protein that plays a regulatory role in the release of several hormones. SCGN is expressed largely in pancreatic β-cells, certain parts of the brain, and also in neuroendocrine tissues. The expression of SCGN is altered in several diseases, such as diabetes, cancers, and neurodegenerative disorders; however, the precise associations that closely link SCGN expression to such pathophysiologies are not known. In this work, we report that SCGN is an early responder to cellular stress, and SCGN expression is temporally upregulated by oxidative stress and heat shock. We show the overexpression of SCGN efficiently prevents cells from heat shock and oxidative damage. We further demonstrate that in the presence of Ca²⁺, SCGN efficiently prevents the aggregation of a broad range of model proteins in vitro. Small-angle X-ray scattering (BioSAXS) studies further reveal that Ca²⁺ induces the conversion of a closed compact apo-SCGN conformation into an open extended holo-SCGN conformation via multistate intermediates, consistent with the augmentation of chaperone activity of SCGN. Furthermore, isothermal titration calorimetry establishes that Ca²⁺ enables SCGN to bind α-synuclein and insulin, two target proteins of SCGN. Altogether, our data not only demonstrate that SCGN is a Ca²⁺-dependent generic molecular chaperone involved in protein homeostasis with broad substrate specificity but also elucidate the origin of its altered expression in several cancers. We describe a plausible mechanism of how perturbations in Ca²⁺ homeostasis and/or deregulated SCGN expression would hasten the process of protein misfolding, which is a feature of many aggregation-based proteinopathies.

A Comparative Molecular Dynamics Study of Selected Point Mutations in the Shwachman–Bodian–Diamond Syndrome Protein SBDS

The Shwachman–Diamond Syndrome (SDS) is an autosomal recessive disease whose majority of patients display mutations in a ribosome assembly protein named Shwachman–Bodian–Diamond Syndrome protein (SBDS). A specific therapy for treating this rare disease is missing, due to the lack of knowledge of the molecular mechanisms responsible for its pathogenesis. Starting from the observation that SBDS single-point mutations, localized in different domains of the proteins, are responsible for an SDS phenotype, we carried out the first comparative Molecular Dynamics simulations on three SBDS mutants, namely R19Q, R126T and I212T. The obtained 450-ns long trajectories were compared with those returned by both the open and closed forms of wild type SBDS and strongly indicated that two distinct conformations (open and closed) are both necessary for the proper SBDS function, in full agreement with recent experimental observations. Our study supports the hypothesis that the SBDS function is governed by an allosteric mechanism involving domains I and III and provides new insights into SDS pathogenesis, thus offering a possible starting point for a specific therapeutic option.

Coarse grained modelling highlights the binding differences in the two different allosteric sites of the Human Kinesin EG5 and its implications in inhibitor design

Kinesins involved in mitotic cell division have gained prominence as promising chemotherapy targets. One such kinesin, EG5, a motor protein responsible for cell division, is a validated chemotherapy target with several compounds at various stages of clinical trials. EG5 has an active site and two different allosteric sites that are known to have ligand specificity. Upon ligand binding, EG5's motor domain will no longer undergo nucleotide-dependent conformational changes required to complete the catalytic cycle. However, there is a lack of in-depth knowledge on the mechanism of inhibitor binding to the two different allosteric sites. To understand the EG5's inhibition mechanism and interactions at allosteric sites and other functionally important regions, we generated two coarse-grained models, Gaussian Network Model (GNM) and Anisotropic Network Model (ANM), to identify the dynamics and its correlation to EG5's function. The first three slowest modes of GNM showed marked differences between the various models of EG5. In the first mode, when the inhibitor is bound at allosteric site 1, there is a presence of a hinge region around residue 166, which is not found when the inhibitor is bound at allosteric site 2 or allosteric sites 1 and 2. The third slowest mode showed a distinctive positively correlated region when the inhibitor is bound at allosteric site 2. These differences indicated that the mechanism of binding at allosteric site 1 and allosteric site 2 are unique. Further, it was observed that the simultaneous ligand binding at allosteric sites 1 and 2 shares structural dynamics and interactions that were found while ligand binds at allosteric sites 1 and 2 independently, leading to a new mechanism. Taken together, our observations suggest that there are different mechanisms at play in each inhibitor bound system considered.

Prediction of Allosteric Communication Pathways in Proteins

MOTIVATION

Allostery in proteins is an essential phenomenon in biological processes. In this paper, we present a computational model to predict paths of maximum information transfer between active and allosteric sites. In this information theoretic study, we use mutual information as the measure of information transfer, where transition probability of information from one residue to its contacting neighbors is proportional to the magnitude of mutual information between the two residues. Starting from a given residue and using a Hidden Markov Model, we successively determine the neighboring residues that eventually lead to a path of optimum information transfer. The Gaussian approximation of mutual information between residue pairs is adopted. The limits of validity of this approximation are discussed in terms of a nonlinear theory of mutual information and its reduction to the Gaussian form.

RESULTS

Predictions of the model are tested on six widely studied cases, CheY Bacterial Chemotaxis, B-cell Lymphoma extra-large Bcl-xL, Human proline isomerase cyclophilin A (CypA), Dihydrofolate reductase DHFR, HRas GTPase, and Caspase-1. The communication transmission rendering the propagation of local fluctuations from the active sites throughout the structure in multiple paths correlate well with the known experimental data. Distinct paths originating from the active site may likely represent a multi functionality such as involving more than one allosteric site and/or preexistence of some other functional states. Our model is computationally fast and simple, and can give allosteric communication pathways, which are crucial for the understanding and control of protein functionality.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Structure and assembly of the S-layer in C. difficile

Many bacteria and archaea possess a two-dimensional protein array, or S-layer, that covers the cell surface and plays crucial roles in cell physiology. Here, we report the crystal structure of SlpA, the main S-layer protein of the bacterial pathogen Clostridioides difficile, and use electron microscopy to study S-layer organisation and assembly. The SlpA crystal lattice mimics S-layer assembly in the cell, through tiling of triangular prisms above the cell wall, interlocked by distinct ridges facing the environment. Strikingly, the array is very compact, with pores of only ~10 Å in diameter, compared to other S-layers (30-100 Å). The surface-exposed flexible ridges are partially dispensable for overall structure and assembly, although a mutant lacking this region becomes susceptible to lysozyme, an important molecule in host defence. Thus, our work gives insights into S-layer organisation and provides a basis for development of C. difficile-specific therapeutics.

Extracting the Dynamic Motion of Proteins Using Normal Mode Analysis

Normal mode analysis (NMA) is a technique for describing the conformational states accessible to a protein in a minimum energy conformation. NMA gives results similar to those produced by principal components analysis of a molecular dynamics simulation, but with only a fraction of the computational effort. Here, we provide a brief overview of the theory and describe three methods for carrying out NMA, including the use of one of the on-line services, the use of off-line software for calculating the projection of the modes calculated from one conformation onto another, and an all-atom NMA calculated using GROMACS. For all three methods, we will use the E1·2Ca²⁺ form of the Ca²⁺-ATPase as a concrete example.

X-ray Characterization of Conformational Changes of Human Apo- and Holo-Transferrin

Human serum transferrin (Tf) is a bilobed glycoprotein whose function is to transport iron through receptor-mediated endocytosis. The mechanism for iron release is pH-dependent and involves conformational changes in the protein, thus making it an attractive system for possible biomedical applications. In this contribution, two powerful X-ray techniques, namely Macromolecular X-ray Crystallography (MX) and Small Angle X-ray Scattering (SAXS), were used to study the conformational changes of iron-free (apo) and iron-loaded (holo) transferrin in crystal and solution states, respectively, at three different pH values of physiological relevance. A crystallographic model of glycosylated apo-Tf was obtained at 3.0 Å resolution, which did not resolve further despite many efforts to improve crystal quality. In the solution, apo-Tf remained mostly globular in all the pH conditions tested; however, the co-existence of closed, partially open, and open conformations was observed for holo-Tf, which showed a more elongated and flexible shape overall.

Improving the catalytic performance of xylanase from Bacillus circulans through structure-based rational design

Endo-1,4-β-xylanase is one of the most important enzymes employed in biorefineries for obtaining fermentable sugars from hemicellulosic components. Herein, we aimed to improve the catalytic performance of Bacillus circulans xylanase (Bcx) using a structure-guided rational design. A systematic analysis of flexible motions revealed that the R49 component of Bcx (i) constrains the global conformational changes essential for substrate binding and (ii) is involved in modulating flexible motion. Site-saturated mutagenesis of the R49 residue led to the engineering of the active mutants with the trade-off between flexibility and rigidity. The most active mutant R49N improved the catalytic performance, including its catalytic efficiency (7.51-fold), conformational stability (0.7 °C improvement), and production of xylose oligomers (2.18-fold higher xylobiose and 1.72-fold higher xylotriose). The results discussed herein can be applied to enhance the catalytic performance of industrially important enzymes by controlling flexibility.

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models

The COVID-19 pandemic has accelerated the study of the potential of multi-target drugs (MTDs). The mixture of homologues called ivermectin (avermectin-B1a + avermectin-B1b) has been shown to be a MTD with potential antiviral activity against SARS-CoV-2 in vitro. However, there are few reports on the effect of each homologue on the flexibility and stiffness of proteins associated with COVID-19, described as ivermectin targets. We observed that each homologue was stably bound to the proteins studied and was able to induce detectable changes with Elastic Network Models (ENM). The perturbations induced by each homologue were characteristic of each compound and, in turn, were represented by a disruption of native intramolecular networks (interactions between residues). The homologues were able to slightly modify the conformation and stability of the connection points between the Cα atoms of the residues that make up the structural network of proteins (nodes), compared to free proteins. Each homologue was able to modified differently the distribution of quasi-rigid regions of the proteins, which could theoretically alter their biological activities. These results could provide a biophysical-computational view of the potential MTD mechanism that has been reported for ivermectin.

Three ParA Dimers Cooperatively Assemble on Type Ia Partition Promoters

Accurate DNA segregation is essential for faithful inheritance of genetic material. In bacteria, this process is mainly ensured by partition systems composed of two proteins, ParA and ParB, and a centromere site. Auto-regulation of Par operon expression is important for efficient partitioning and is primarily mediated by ParA for type Ia plasmid partition systems. For the F-plasmid, four ParA_F monomers were proposed to bind to four repeated sequences in the promoter region. By contrast, using quantitative surface-plasmon-resonance, we showed that three ParA_F dimers bind to this region. We uncovered that one perfect inverted repeat (IR) motif, consisting of two hexamer sequences spaced by 28-bp, constitutes the primary ParA_F DNA binding site. A similar but degenerated motif overlaps the former. ParA_F binding to these motifs is well supported by biochemical and modeling analyses. Molecular dynamics simulations predict that the winged-HTH domain displays high flexibility, which may favor the cooperative ParA binding to the promoter. We propose that three ParA_F dimers bind cooperatively to overlapping motifs, thus covering the promoter region. A similar organization is found on closely related and distant plasmid partition systems, suggesting that such promoter organization for auto-regulated Par operons is widespread and may have evolved from a common ancestor.

Global Dynamics Renders Protein Sites with High Functional Response

Deep mutational scanning enables examination of the effects of many mutations at each amino acid position in a query protein, readily disclosing positions that are particularly sensitive. Mutations in these positions alter protein function the most. Here, on the premise that dynamics underlie function, we explore to what extent the measured sensitivity to mutations could be linked to-perhaps be explained by-the structural dynamics of the protein. We employ a minimalist perturbation-response approach based on the Gaussian Network Model (GNM) on a data set of seven proteins with deep mutational scanning data. The analysis shows that the mutation-sensitive positions are often of capacity to modulate the global dynamics and to intermediate allosteric interactions in the structure. With that, upon strain perturbation, these positions decrease residue fluctuations the most, affecting function via entropy changes. This is particularly relevant for positions that are distant from binding sites or other functional regions of the protein and are sensitive to mutations, nevertheless. Our results indicate that mutations in these positions allosterically manipulate protein function.

An Integrative Structural Biology Analysis of Von Willebrand Factor Binding and Processing by ADAMTS-13 in Solution

Von Willebrand Factor (vWF), a 300-kDa plasma protein key to homeostasis, is cleaved at a single site by multi-domain metallopeptidase ADAMTS-13. vWF is the only known substrate of this peptidase, which circulates in a latent form and becomes allosterically activated by substrate binding. Herein, we characterised the complex formed by a competent peptidase construct (AD13-MDTCS) comprising metallopeptidase (M), disintegrin-like (D), thrombospondin (T), cysteine-rich (C), and spacer (S) domains, with a 73-residue functionally relevant vWF-peptide, using nine complementary techniques. Pull-down assays, gel electrophoresis, and surface plasmon resonance revealed tight binding with sub-micromolar affinity. Cross-linking mass spectrometry with four reagents showed that, within the peptidase, domain D approaches M, C, and S. S is positioned close to M and C, and the peptide contacts all domains. Hydrogen/deuterium exchange mass spectrometry revealed strong and weak protection for C/D and M/S, respectively. Structural analysis by multi-angle laser light scattering and small-angle X-ray scattering in solution revealed that the enzyme adopted highly flexible unbound, latent structures and peptide-bound, active structures that differed from the AD13-MDTCS crystal structure. Moreover, the peptide behaved like a self-avoiding random chain. We integrated the results with computational approaches, derived an ensemble of structures that collectively satisfied all experimental restraints, and discussed the functional implications. The interaction conforms to a 'fuzzy complex' that follows a 'dynamic zipper' mechanism involving numerous reversible, weak but additive interactions that result in strong binding and cleavage. Our findings contribute to illuminating the biochemistry of the vWF:ADAMTS-13 axis.

HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions by using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures. The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.

Oncogenic mutations on Rac1 affect global intrinsic dynamics underlying GTP and PAK1 binding

Rac1 is a small member of the Rho GTPase family. One of the most important downstream effectors of Rac1 is a serine/threonine kinase, p21-activated kinase 1 (PAK1). Mutational activation of PAK1 by Rac1 has oncogenic signaling effects. Here, although we focus on Rac1-PAK1 interaction by atomic-force-microscopy-based single-molecule force spectroscopy experiments, we explore the effect of active mutations on the intrinsic dynamics and binding interactions of Rac1 by Gaussian network model analysis and molecular dynamics simulations. We observe that Rac1 oncogenic mutations are at the hinges of three global modes of motion, suggesting the mechanical changes as potential markers of oncogenicity. Indeed, the dissociation of wild-type Rac1-PAK1 complex shows two distinct unbinding dynamic states that are reduced to one with constitutively active Q61L and oncogenic Y72C mutant Rac1, as revealed by single-molecule force spectroscopy experiments. Q61L and Y72C mutations change the mechanics of the Rac1-PAK1 complex by increasing the elasticity of the protein and slowing down the transition to the unbound state. On the other hand, Rac1's intrinsic dynamics reveal more flexible GTP and PAK1-binding residues on switches I and II with Q61L, Y72C, oncogenic P29S and Q61R, and negative T17N mutations. The cooperativity in the fluctuations of GTP-binding sites around the p-loop and switch I decreases in all mutants, mostly in Q61L, whereas some PAK1-binding residues display enhanced coupling with GTP-binding sites in Q61L and Y72C and within each other in P29S. The predicted binding free energies of the modeled Rac1-PAK1 complexes show that the change in the dynamic behavior likely means a more favorable PAK1 interaction. Overall, these findings suggest that the active mutations affect intrinsic functional dynamic events and alter the mechanics underlying the binding of Rac1 to GTP and upstream and downstream partners including PAK1.

A graph-based algorithm for detecting rigid domains in protein structures

Background

Conformational transitions are implicated in the biological function of many proteins. Structural changes in proteins can be described approximately as the relative movement of rigid domains against each other. Despite previous efforts, there is a need to develop new domain segmentation algorithms that are capable of analysing the entire structure database efficiently and do not require the choice of protein-dependent tuning parameters such as the number of rigid domains.

Results

We develop a graph-based method for detecting rigid domains in proteins. Structural information from multiple conformational states is represented by a graph whose nodes correspond to amino acids. Graph clustering algorithms allow us to reduce the graph and run the Viterbi algorithm on the associated line graph to obtain a segmentation of the input structures into rigid domains. In contrast to many alternative methods, our approach does not require knowledge about the number of rigid domains. Moreover, we identified default values for the algorithmic parameters that are suitable for a large number of conformational ensembles. We test our algorithm on examples from the DynDom database and illustrate our method on various challenging systems whose structural transitions have been studied extensively.

Conclusions

The results strongly suggest that our graph-based algorithm forms a novel framework to characterize structural transitions in proteins via detecting their rigid domains. The web server is available at http://azifi.tz.agrar.uni-goettingen.de/webservice/.

Protein dynamics analysis identifies candidate cancer driver genes and mutations in TCGA data

Recently, it has been showed that cancer missense mutations selectively target the neighborhood of hinge residues, which are key sites in protein dynamics. Here, we show that this approach can be extended to find previously unknown candidate mutations and genes. To this aim, we developed a computational pipeline to detect significantly enriched three-dimensional (3D) clustering of missense mutations around hinge residues. The hinge residues were detected by applying a Gaussian network model. By systematically analyzing the PanCancer compendium of somatic mutations in nearly 10 000 tumors from the Cancer Genome Atlas, we identified candidate genes and mutations in addition to well known ones. For instance, we found significantly enriched 3D clustering of missense mutations in known cancer genes including CDK4, CDKN2A, TCL1A, and MAPK1. Beside these known genes, we also identified significantly enriched 3D clustering of missense mutations around hinge residues in PLA2G4A, which may lead to excessive phosphorylation of the extracellular signal-regulated kinases. Furthermore, we demonstrated that hinge-based features improves pathogenicity prediction for missense mutations. Our results show that the consideration of clustering around hinge residues can help us explain the functional role of the mutations in known cancer genes and identify candidate genes.

Effects of Distal Mutations on Prolyl-Adenylate Formation of Escherichia coli Prolyl-tRNA Synthetase

Enzymes play important roles in many biological processes. Amino acid residues in the active site pocket of an enzyme, which are in direct contact with the substrate(s), are generally believed to be critical for substrate recognition and catalysis. Identifying and understanding how these "catalytic" residues help enzymes achieve enormous rate enhancement has been the focus of many structural and biochemical studies over the past several decades. Recent studies have shown that enzymes are intrinsically dynamic and dynamic coupling between distant structural elements is essential for effective catalysis in modular enzymes. Therefore, distal residues are expected to have impact on enzyme function. However, few studies have investigated the role of distal residues on enzymatic catalysis. In the present study, the effects of distal residue mutations on the catalytic function of an aminoacyl-tRNA synthetase, namely, prolyl-tRNA synthase, were investigated. The present study demonstrates that distal residues significantly contribute to catalysis of the modular Escherichia coli prolyl-tRNA synthetase by maintaining intrinsic protein flexibility.

Mapping the underlying mechanisms of fibrinogen benzothiazole drug interactions using computational and experimental approaches

Three-dimensional conformational crystallographic binding-modes are of paramount importance to understand the docking mechanism of protein-ligand interactions and to identify potential "leading drugs" conformers towards rational drugs-design. Herein, we present an integrated computational-experimental study tackling the problem of multiple binding modes among the ligand 3-(2-Benzothiazolylthio)-propane sulfonic acid (BTS) and the fibrinogen receptor (E-region). Based on molecular docking simulations, we found that the free energy of binding values for nine of different BTS-docking complexes (i.e., BTS-pose_1-9) were very close. We have also identified a docking-mechanism of BTS-interaction mainly based on non-covalent hydrophobic interactions with H-bond contacts stabilizing the fibrinogen-BTS docking complexes. Interestingly, the different BTS-poses_1-9 were found to be able to block the fibrinogen binding site (E-region) by inducing local perturbations in effector and allosteric residues, reducing the degree of collectivity in its flexibility normal modes. As such, we theoretically suggest that the BTS-binding modes can significantly affect the physiological condition of the unoccupied fibrinogen protein structure by bringing global and local perturbations in the frequency domain spectra. The proposed theoretical mechanisms, the interactions involved and the conformational changes suggested, were further corroborated by different experimental techniques such as isothermal titration calorimetry (ITC), zeta potential, UV-vis, fluorescence and small angle X-ray scattering (SAXS). The combined results shall open new avenues towards the application of complex supra-molecular information in rational drugs-design.

Structural basis of cell-surface signaling by a conserved sigma regulator in Gram-negative bacteria

Cell-surface signaling (CSS) in Gram-negative bacteria involves highly conserved regulatory pathways that optimize gene expression by transducing extracellular environmental signals to the cytoplasm via inner-membrane sigma regulators. The molecular details of ferric siderophore-mediated activation of the iron import machinery through a sigma regulator are unclear. Here, we present the 1.56 Å resolution structure of the periplasmic complex of the C-terminal CSS domain (CCSSD) of PupR, the sigma regulator in the Pseudomonas capeferrum pseudobactin BN7/8 transport system, and the N-terminal signaling domain (NTSD) of PupB, an outer-membrane TonB-dependent transducer. The structure revealed that the CCSSD consists of two subdomains: a juxta-membrane subdomain, which has a novel all-β-fold, followed by a secretin/TonB, short N-terminal subdomain at the C terminus of the CCSSD, a previously unobserved topological arrangement of this domain. Using affinity pulldown assays, isothermal titration calorimetry, and thermal denaturation CD spectroscopy, we show that both subdomains are required for binding the NTSD with micromolar affinity and that NTSD binding improves CCSSD stability. Our findings prompt us to present a revised model of CSS wherein the CCSSD:NTSD complex forms prior to ferric-siderophore binding. Upon siderophore binding, conformational changes in the CCSSD enable regulated intramembrane proteolysis of the sigma regulator, ultimately resulting in transcriptional regulation.

Predicting Protein Functional Motions: an Old Recipe with a New Twist

Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.

Role of protein-protein interactions in allosteric drug design for DNA methyltransferases

DNA methyltransferases (DNMTs) not only play key roles in epigenetic gene regulation, but also serve as emerging targets for several diseases, especially for cancers. Due to the multi-domains of DNMT structures, targeting allosteric sites of protein-protein interactions (PPIs) is becoming an attractive strategy in epigenetic drug discovery. This chapter aims to review the major contemporary approaches utilized for the drug discovery based on PPIs in different dimensions, from the enumeration of allosteric mechanism to the identification of allosteric pockets. These include the construction of protein structure networks (PSNs) based on molecular dynamics (MD) simulations, performing elastic network models (ENMs) and perturbation response scanning (PRS) calculation, the sequence-based conservation and coupling analysis, and the allosteric pockets identification. Furthermore, we complement this methodology by highlighting the role of computational approaches in promising practical applications for the computer-aided drug design, with special focus on two DNMTs, namely, DNMT1 and DNMT3A.

RapidRMSD: rapid determination of RMSDs corresponding to motions of flexible molecules

Motivation

The root mean square deviation (RMSD) is one of the most used similarity criteria in structural biology and bioinformatics. Standard computation of the RMSD has a linear complexity with respect to the number of atoms in a molecule, making RMSD calculations time-consuming for the large-scale modeling applications, such as assessment of molecular docking predictions or clustering of spatially proximate molecular conformations. Previously, we introduced the RigidRMSD algorithm to compute the RMSD corresponding to the rigid-body motion of a molecule. In this study, we go beyond the limits of the rigid-body approximation by taking into account conformational flexibility of the molecule. We model the flexibility with a reduced set of collective motions computed with e.g. normal modes or principal component analysis.

Results

The initialization of our algorithm is linear in the number of atoms and all the subsequent evaluations of RMSD values between flexible molecular conformations depend only on the number of collective motions that are selected to model the flexibility. Therefore, our algorithm is much faster compared to the standard RMSD computation for large-scale modeling applications. We demonstrate the efficiency of our method on several clustering examples, including clustering of flexible docking results and molecular dynamics (MD) trajectories. We also demonstrate how to use the presented formalism to generate pseudo-random constant-RMSD structural molecular ensembles and how to use these in cross-docking.

Availability and implementation

We provide the algorithm written in C++ as the open-source RapidRMSD library governed by the BSD-compatible license, which is available at http://team.inria.fr/nano-d/software/RapidRMSD/. The constant-RMSD structural ensemble application and clustering of MD trajectories is available at http://team.inria.fr/nano-d/software/nolb-normal-modes/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Normal Mode Analysis as a Routine Part of a Structural Investigation

Normal mode analysis (NMA) is a technique that can be used to describe the flexible states accessible to a protein about an equilibrium position. These states have been shown repeatedly to have functional significance. NMA is probably the least computationally expensive method for studying the dynamics of macromolecules, and advances in computer technology and algorithms for calculating normal modes over the last 20 years have made it nearly trivial for all but the largest systems. Despite this, it is still uncommon for NMA to be used as a component of the analysis of a structural study. In this review, we will describe NMA, outline its advantages and limitations, explain what can and cannot be learned from it, and address some criticisms and concerns that have been voiced about it. We will then review the most commonly used techniques for reducing the computational cost of this method and identify the web services making use of these methods. We will illustrate several of their possible uses with recent examples from the literature. We conclude by recommending that NMA become one of the standard tools employed in any structural study.

Pre- and post-docking sampling of conformational changes using ClustENM and HADDOCK for protein-protein and protein-DNA systems

Incorporating the dynamic nature of biomolecules in the modeling of their complexes is a challenge, especially when the extent and direction of the conformational changes taking place upon binding is unknown. Estimating whether the binding of a biomolecule to its partner(s) occurs in a conformational state accessible to its unbound form (“conformational selection”) and/or the binding process induces conformational changes (“induced‐fit”) is another challenge. We propose here a method combining conformational sampling using ClustENM—an elastic network‐based modeling procedure—with docking using HADDOCK, in a framework that incorporates conformational selection and induced‐fit effects upon binding. The extent of the applied deformation is estimated from its energetical costs, inspired from mechanical tensile testing on materials. We applied our pre‐ and post‐docking sampling of conformational changes to the flexible multidomain protein‐protein docking benchmark and a subset of the protein‐DNA docking benchmark. Our ClustENM‐HADDOCK approach produced acceptable to medium quality models in 7/11 and 5/6 cases for the protein‐protein and protein‐DNA complexes, respectively. The conformational selection (sampling prior to docking) has the highest impact on the quality of the docked models for the protein‐protein complexes. The induced‐fit stage of the pipeline (post‐sampling), however, improved the quality of the final models for the protein‐DNA complexes. Compared to previously described strategies to handle conformational changes, ClustENM‐HADDOCK performs better than two‐body docking in protein‐protein cases but worse than a flexible multidomain docking approach. However, it does show a better or similar performance compared to previous protein‐DNA docking approaches, which makes it a suitable alternative.

ART-RRT: As-Rigid-As-Possible search for protein conformational transition paths

The possible functions of a protein are strongly related to its structural rearrangements in the presence of other molecules or environmental changes. Hence, the evaluation of transition paths of proteins, which encodes conformational changes between stable states, is important since it may reveal the underlying mechanisms of the biochemical processes related to these motions. During the last few decades, different geometry-based methods have been proposed to predict such transition paths. However, in the cases where the solution requires complex motions, these methods, which typically constrain only locally the molecular structures, could produce physically irrelevant solutions involving self-intersection. Recently, we have proposed ART-RRT, an efficient method for finding ligand-unbinding pathways. It relies on the exploration of energy valleys in low-dimensional spaces, taking advantage of some mechanisms inspired from computer graphics to ensure the consistency of molecular structures. This article extends ART-RRT to the problem of finding probable conformational transition between two stable states for proteins. It relies on a bidirectional exploration rooted on the two end states and introduces an original strategy to attempt connections between the explored regions. The resulting method is able to produce at low computational cost biologically realistic paths free from self-intersection. These paths can serve as valuable input to other advanced methods for the study of proteins. A better understanding of conformational changes of proteins is important since it may reveal the underlying mechanisms of the biochemical processes related to such motions. Recently, the ART-RRT method has been introduced for finding ligand-unbinding pathways. This article presents an adaptation of the method for finding probable conformational transition between two stable states of a protein. The method is not only computationally cost-effective but also able to produce biologically realistic paths which are free from self-intersection.

DynOmics: dynamics of structural proteome and beyond

DynOmics (dynomics.pitt.edu) is a portal developed to leverage rapidly growing structural proteomics data by efficiently and accurately evaluating the dynamics of structurally resolved systems, from individual molecules to large complexes and assemblies, in the context of their physiological environment. At the core of the portal is a newly developed server, ENM 1.0, which permits users to efficiently generate information on the collective dynamics of any structure in PDB format, user-uploaded or database-retrieved. ENM 1.0 integrates two widely used elastic network models (ENMs)—the Gaussian Network Model (GNM) and the Anisotropic Network Model (ANM), extended to take account of molecular environment. It enables users to assess potentially functional sites, signal transduction or allosteric communication mechanisms, and protein–protein and protein–DNA interaction poses, in addition to delivering ensembles of accessible conformers reconstructed at atomic details based on the global modes of motions predicted by the ANM. The ‘environment’ is defined in a flexible manner, from lipid bilayer and crystal contacts, to substrate or ligands bound to a protein, or surrounding subunits in a multimeric structure or assembly. User-friendly interactive features permit users to easily visualize how the environment alter the intrinsic dynamics of the query systems. ENM 1.0 can be accessed at http://enm.pitt.edu/ or http://dyn.life.nthu.edu.tw/oENM/.

Structural and energetic evolution of fibrinogen toward to the betablocker interactions

We present a computational analysis coupled with experimental studies, focusing on the binding-interaction between beta-adrenoreceptor blocking agents (acebutolol and propranolol) with fibrinogen protein (E-region). Herein, computational modeling on structural validation and flexibility properties of fibrinogen E-region showed that the E-region interacting residues, which form the funnel-shaped hydrophobic cavity for ligand-binding, can be efficiently modeled. The obtained free energy of binding (FEB) values for the docking complexes, namely acebutolol/fibrinogen E-region and propranolol/fibrinogen E-region, were very close and amounted to - 6.9 kcal/mol and - 6.8 kcal/mol, respectively. They were supported by a high binding-accuracy (R.M.S.D < 2 Å) for the best crystallographic binding-poses in both cases. In this regard, we identify a docking-mechanism of interaction for the propranolol and acebutolol mainly based on non-covalent hydrophobic contacts with the fibrinogen E-region binding-site. Besides, the beta-adrenoreceptor blocking agents are able to induce local perturbations affecting particularly the fibrinogen E-region allosteric residues linked to significant changes in the inter-residue communication and flexibility properties of residue network. In this sense, we show that the key biophysical parameters like frequency and collectivity degree may be compromised in different ways by the interaction with acebutolol and propranolol. Isothermal titration calorimetry, zeta potential and small angle X-ray scattering (SAXS) measurements were performed to complete and corroborate computational analysis. The combined experimental results point out that acebutolol acts to a lesser extent to fibrinogen structure than propranolol.

Solution structure and functional investigation of human guanylate kinase reveals allosteric networking and a crucial role for the enzyme in cancer

Human guanylate kinase (hGMPK) is the only known enzyme responsible for cellular GDP production, making it essential for cellular viability and proliferation. Moreover, hGMPK has been assigned a critical role in metabolic activation of antiviral and antineoplastic nucleoside-analog prodrugs. Given that hGMPK is indispensable for producing the nucleotide building blocks of DNA, RNA, and cGMP and that cancer cells possess elevated GTP levels, it is surprising that a detailed structural and functional characterization of hGMPK is lacking. Here, we present the first high-resolution structure of hGMPK in the apo form, determined with NMR spectroscopy. The structure revealed that hGMPK consists of three distinct regions designated as the LID, GMP-binding (GMP-BD), and CORE domains and is in an open configuration that is nucleotide binding-competent. We also demonstrate that nonsynonymous single-nucleotide variants (nsSNVs) of the hGMPK CORE domain distant from the nucleotide-binding site of this domain modulate enzymatic activity without significantly affecting hGMPK's structure. Finally, we show that knocking down the hGMPK gene in lung adenocarcinoma cell lines decreases cellular viability, proliferation, and clonogenic potential while not altering the proliferation of immortalized, noncancerous human peripheral airway cells. Taken together, our results provide an important step toward establishing hGMPK as a potential biomolecular target, from both an orthosteric (ligand-binding sites) and allosteric (location of CORE domain-located nsSNVs) standpoint.

Analyzing Change in Protein Stability Associated with Single Point Deletions in a Newly Defined Protein Structure Database

Protein backbone alternation due to insertion/deletion or mutation operation often results in a change of fundamental biophysical properties of proteins. The proposed work intends to encode the protein stability changes associated with single point deletions (SPDs) of amino acids in proteins. The encoding will help in the primary screening of detrimental backbone modifications before opting for expensive in vitro experimentations. In the absence of any benchmark database documenting SPDs, we curate a data set containing SPDs that lead to both folded conformations and unfolded state. We differentiate these SPD instances with the help of simple structural and physicochemical features and eventually classify the foldability resulting out of SPDs using a Random Forest classifier and an Elliptic Envelope based outlier detector. Adhering to leave one out cross validation, the accuracy of the Random Forest classifier and the Elliptic Envelope is of 99.4% and 98.1%, respectively. The newly defined database and the delineation of SPD instances based on its resulting foldability provide a head start toward finding a solution to the given problem.

Interaction of the GTPase Elongation Factor Like-1 with the Shwachman-Diamond Syndrome Protein and Its Missense Mutations

The Shwachman-Diamond Syndrome (SDS) is a disorder arising from mutations in the genes encoding for the Shwachman-Bodian-Diamond Syndrome (SBDS) protein and the GTPase known as Elongation Factor Like-1 (EFL1). Together, these proteins remove the anti-association factor eIF6 from the surface of the pre-60S ribosomal subunit to promote the formation of mature ribosomes. SBDS missense mutations can either destabilize the protein fold or affect surface epitopes. The molecular alterations resulting from the latter remain largely unknown, although some evidence suggest that binding to EFL1 may be affected. We further explored the effect of these SBDS mutations on the interaction with EFL1, and showed that all tested mutations disrupted the binding to EFL1. Binding was either severely weakened or almost abolished, depending on the assessed mutation. In higher eukaryotes, SBDS is essential for development, and lack of the protein results in early lethality. The existence of patients whose only source of SBDS consists of that with surface missense mutations highlights the importance of the interaction with EFL1 for their function. Additionally, we studied the interaction mechanism of the proteins in solution and demonstrated that binding consists of two independent and cooperative events, with domains 2⁻3 of SBDS directing the initial interaction with EFL1, followed by docking of domain 1. In solution, both proteins exhibited large flexibility and consisted of an ensemble of conformations, as demonstrated by Small Angle X-ray Scattering (SAXS) experiments.

NAHAL-Flex: A Numerical and Alphabetical Hinge Detection Algorithm for Flexible Protein Structure Alignment

Flexible proteins are proteins that have conformational changes in their structures. Protein flexibility analysis is critical for classifying and understanding protein functionality. For that analysis, the hinge areas where proteins show flexibility must be detected. To detect the location of the hinges, previous methods have utilized the three-dimensional (3D) structure of proteins, which is highly computational. To reduce the computational complexity, this study proposes a novel text-based method using structural alphabets (SAs) for detecting the hinge position, called NAHAL-Flex. Protein structures were encoded to a particular type of SA called the protein folding shape code (PFSC), which remains unaffected by location, scale, and rotation. The flexible regions of the proteins are the only places in which letter sequences can be distorted. With this knowledge, it is possible to find the longest alignment path of two letter sequences using a dynamic programming (DP) algorithm. Then, the proposed method looks for regions where the alphabet sequence is distorted to find the most probable hinge positions. In order to reduce the number of hinge positions, a genetic algorithm (GA) was utilized to find the best candidate hinge points. To evaluate the method's effectiveness, four different flexible and rigid protein databases, including two small datasets and two large datasets, were utilized. For the small dataset, the NAHAL-Flex method was comparable to state-of-the-art structural flexible alignment methods. The result for the large datasets show that NAHAL-Flex outperforms some well-known alignment methods, e.g., DaliLite, Matt, DeepAlign, and TM-align; the speed of NAHAL-Flex was faster and its result was more accurate than the other methods.

SnapDock-template-based docking by Geometric Hashing

Motivation

A highly efficient template-based protein–protein docking algorithm, nicknamed SnapDock, is presented. It employs a Geometric Hashing-based structural alignment scheme to align the target proteins to the interfaces of non-redundant protein–protein interface libraries. Docking of a pair of proteins utilizing the 22 600 interface PIFACE library is performed in < 2 min on the average. A flexible version of the algorithm allowing hinge motion in one of the proteins is presented as well.

Results

To evaluate the performance of the algorithm a blind re-modelling of 3547 PDB complexes, which have been uploaded after the PIFACE publication has been performed with success ratio of about 35%. Interestingly, a similar experiment with the template free PatchDock docking algorithm yielded a success rate of about 23% with roughly 1/3 of the solutions different from those of SnapDock. Consequently, the combination of the two methods gave a 42% success ratio.

Availability and implementation

A web server of the application is under development.

An auto-inhibitory helix in CTP:phosphocholine cytidylyltransferase hijacks the catalytic residue and constrains a pliable, domain-bridging helix pair

The activity of CTP:phosphocholine cytidylyltransferase (CCT), a key enzyme in phosphatidylcholine synthesis, is regulated by reversible interactions of a lipid-inducible amphipathic helix (domain M) with membrane phospholipids. When dissociated from membranes, a portion of the M domain functions as an auto-inhibitory (AI) element to suppress catalysis. The AI helix from each subunit binds to a pair of α helices (αE) that extend from the base of the catalytic dimer to create a four-helix bundle. The bound AI helices make intimate contact with loop L2, housing a key catalytic residue, Lys¹²² The impacts of the AI helix on active-site dynamics and positioning of Lys¹²² are unknown. Extensive MD simulations with and without the AI helix revealed that backbone carbonyl oxygens at the point of contact between the AI helix and loop L2 can entrap the Lys¹²² side chain, effectively competing with the substrate, CTP. In silico, removal of the AI helices dramatically increased αE dynamics at a predicted break in the middle of these helices, enabling them to splay apart and forge new contacts with loop L2. In vitro cross-linking confirmed the reorganization of the αE element upon membrane binding of the AI helix. Moreover, when αE bending was prevented by disulfide engineering, CCT activation by membrane binding was thwarted. These findings suggest a novel two-part auto-inhibitory mechanism for CCT involving capture of Lys¹²² and restraint of the pliable αE helices. We propose that membrane binding enables bending of the αE helices, bringing the active site closer to the membrane surface.

Crystal structure of thermospermine synthase from Medicago truncatula and substrate discriminatory features of plant aminopropyltransferases

Polyamines are linear polycationic compounds that play a crucial role in the growth and development of higher plants. One triamine (spermidine, SPD) and two tetraamine isomers (spermine, SPM, and thermospermine, TSPM) are obtained by the transfer of the aminopropyl group from decarboxylated S-adenosylmethionine to putrescine and SPD. These reactions are catalyzed by the specialized aminopropyltransferases. In that respect, plants are unique eukaryotes that have independently evolved two enzymes, thermospermine synthase (TSPS), encoded by the gene ACAULIS5, and spermine synthase, which produce TSPM and SPM, respectively. In this work, we structurally characterize the ACAULIS5 gene product, TSPS, from the model legume plant Medicago truncatula (Mt). Six crystal structures of MtTSPS - one without ligands and five in complexes with either reaction substrate (SPD), reaction product (TSPM), or one of three cofactor analogs (5'-methylthioadenosine, S-adenosylthiopropylamine, and adenosine) - give detailed insights into the biosynthesis of TSPM. Combined with small-angle X-ray scattering data, the crystal structures show that MtTSPS is a symmetric homotetramer with an interdomain eight-stranded β-barrel. Such an assembly and the presence of a hinge-like feature between N-terminal and C-terminal domains give the protein additional flexibility which potentially improves loading substrates and discarding products after the catalytic event. We also discuss the sequence and structural features around the active site of the plant aminopropyltransferases that distinguish them from each other and determine their characteristic substrate discrimination.

Structural Architecture of the Nucleosome Remodeler ISWI Determined from Cross-Linking, Mass Spectrometry, SAXS, and Modeling

Chromatin remodeling factors assume critical roles by regulating access to nucleosomal DNA. To determine the architecture of the Drosophila ISWI remodeling enzyme, we developed an integrative structural approach that combines protein cross-linking, mass spectrometry, small-angle X-ray scattering, and computational modeling. The resulting structural model shows the ATPase module in a resting state with both ATPase lobes twisted against each other, providing support for a conformation that was recently trapped by crystallography. The autoinhibiting NegC region does not protrude from the ATPase module as suggested previously. The regulatory NTR domain is located near both ATPase lobes. The full-length enzyme is flexible and can adopt a compact structure in solution with the C-terminal HSS domain packing against the ATPase module. Our data imply a series of conformational changes upon activation of the enzyme and illustrate how the NTR, NegC, and HSS domains contribute to regulation of the ATPase module.

Modeling Structure and Dynamics of Protein Complexes with SAXS Profiles

Small-angle X-ray scattering (SAXS) is an increasingly common and useful technique for structural characterization of molecules in solution. A SAXS experiment determines the scattering intensity of a molecule as a function of spatial frequency, termed SAXS profile. SAXS profiles can be utilized in a variety of molecular modeling applications, such as comparing solution and crystal structures, structural characterization of flexible proteins, assembly of multi-protein complexes, and modeling of missing regions in the high-resolution structure. Here, we describe protocols for modeling atomic structures based on SAXS profiles. The first protocol is for comparing solution and crystal structures including modeling of missing regions and determination of the oligomeric state. The second protocol performs multi-state modeling by finding a set of conformations and their weights that fit the SAXS profile starting from a single-input structure. The third protocol is for protein-protein docking based on the SAXS profile of the complex. We describe the underlying software, followed by demonstrating their application on interleukin 33 (IL33) with its primary receptor ST2 and DNA ligase IV-XRCC4 complex.

Viral Capsid Assembly: A Quantified Uncertainty Approach

Most of the existing research in assembly pathway prediction/analysis of viral capsids makes the simplifying assumption that the configuration of the intermediate states can be extracted directly from the final configuration of the entire capsid. This assumption does not take into account the conformational changes of the constituent proteins as well as minor changes to the binding interfaces that continue throughout the assembly process until stabilization. This article presents a statistical-ensemble-based approach that samples the configurational space for each monomer with the relative local orientation between monomers, to capture the uncertainties in binding and conformations. Further, instead of using larger capsomers (trimers, pentamers) as building blocks, we allow all possible subassemblies to bind in all possible combinations. We represent the resulting assembly graph in two different ways: First, we use the Wilcoxon signed-rank measure to compare the distributions of binding free energy computed on the sampled conformations to predict likely pathways. Second, we represent chemical equilibrium aspects of the transitions as a Bayesian Factor graph where both associations and dissociations are modeled based on concentrations and the binding free energies. We applied these protocols on the feline panleukopenia virus and the Nudaurelia capensis virus. Results from these experiments showed a significant departure from those that one would obtain if only the static configurations of the proteins were considered. Hence, we establish the importance of an uncertainty-aware protocol for pathway analysis, and we provide a statistical framework as an important first step toward assembly pathway prediction with high statistical confidence.