Probing prothrombin structure by limited proteolysis

Prothrombin, or coagulation factor II, is a multidomain zymogen precursor of thrombin that undergoes an allosteric equilibrium between two alternative conformations, open and closed, that react differently with the physiological activator prothrombinase. Specifically, the dominant closed form promotes cleavage at R320 and initiates activation along the meizothrombin pathway, whilst the open form promotes cleavage at R271 and initiates activation along the alternative prethrombin-2 pathway. Here we report how key structural features of prothrombin can be monitored by limited proteolysis with chymotrypsin that attacks W468 in the flexible autolysis loop of the protease domain in the open but not the closed form. Perturbation of prothrombin by selective removal of its constituent Gla domain, kringles and linkers reveals their long-range communication and supports a scenario where stabilization of the open form switches the pathway of activation from meizothrombin to prethrombin-2. We also identify R296 in the A chain of the protease domain as a critical link between the allosteric open-closed equilibrium and exposure of the sites of cleavage at R271 and R320. These findings reveal important new details on the molecular basis of prothrombin functio

The emergence of waves in random discrete systems

Essential criteria for the emergence of wave-like manifestations occurring in an entirely discrete system are identified using a simple model for the movement of particles through a network. The dynamics are entirely stochastic and memoryless involving a birth-death-migration process. The requirements are that the network should have at least three nodes, that migration should have a directional bias, and that the particle dynamics have a non-local dependence. Well defined bifurcations mark transitions between amorphous, wave-like and collapsed states with an intermittent regime between the latter two

Random, blocky and alternating ordering in supramolecular polymers of chemically bidisperse monomers

As a first step to understanding the role of molecular or chemical polydispersity in self-assembly, we put forward a coarse-grained model that describes the spontaneous formation of quasi-linear polymers in solutions containing two self-assembling species. Our theoretical framework is based on a two-component self-assembled Ising model in which the bidispersity is parameterized in terms of the strengths of the binding free energies that depend on the monomer species involved in the pairing interaction. Depending upon the relative values of the binding free energies involved, different morphologies of assemblies that include both components are formed, exhibiting paramagnetic-, ferromagnetic- or anti ferromagnetic-like order,i.e., random, blocky or alternating ordering of the two components in the assemblies. Analyzing the model for the case of ferromagnetic ordering, which is of most practical interest, we find that the transition from conditions of minimal assembly to those characterized by strong polymerization can be described by a critical concentration that depends on the concentration ratio of the two species. Interestingly, the distribution of monomers in the assemblies is different from that in the original distribution, i.e., the ratio of the concentrations of the two components put into the system. The monomers with a smaller binding free energy are more abundant in short assemblies and monomers with a larger binding affinity are more abundant in longer assemblies. Under certain conditions the two components congregate into separate supramolecular polymeric species and in that sense phase separate. We find strong deviations from the expected growth law for supramolecular polymers even for modest amounts of a second component, provided it is chemically sufficiently distinct from the main one.Comment: Submitted to Macromolecules, 6 figures. arXiv admin note: substantial text overlap with arXiv:1111.176

Characterization of the 1st and 2nd EF-hands of NADPH oxidase 5 by fluorescence, isothermal titration calorimetry, and circular dichroism

<p>Abstract</p> <p>Background</p> <p>Superoxide generated by non-phagocytic NADPH oxidases (NOXs) is of growing importance for physiology and pathobiology. The calcium binding domain (CaBD) of NOX5 contains four EF-hands, each binding one calcium ion. To better understand the metal binding properties of the 1^stand 2^ndEF-hands, we characterized the N-terminal half of CaBD (NCaBD) and its calcium-binding knockout mutants.</p> <p>Results</p> <p>The isothermal titration calorimetry measurement for NCaBD reveals that the calcium binding of two EF-hands are loosely associated with each other and can be treated as independent binding events. However, the Ca²⁺binding studies on NCaBD(E31Q) and NCaBD(E63Q) showed their binding constants to be 6.5 × 10⁵and 5.0 × 10²M^-1with ΔHs of -14 and -4 kJ/mol, respectively, suggesting that intrinsic calcium binding for the 1^stnon-canonical EF-hand is largely enhanced by the binding of Ca²⁺to the 2^ndcanonical EF-hand. The fluorescence quenching and CD spectra support a conformational change upon Ca²⁺binding, which changes Trp residues toward a more non-polar and exposed environment and also increases its α-helix secondary structure content. All measurements exclude Mg²⁺-binding in NCaBD.</p> <p>Conclusions</p> <p>We demonstrated that the 1^stnon-canonical EF-hand of NOX5 has very weak Ca²⁺binding affinity compared with the 2^ndcanonical EF-hand. Both EF-hands interact with each other in a cooperative manner to enhance their Ca²⁺binding affinity. Our characterization reveals that the two EF-hands in the N-terminal NOX5 are Ca²⁺specific.</p> <p>Graphical abstract</p> <p><display-formula><graphic file="1752-153X-6-29-i1.gif"/></display-formula></p

Abrogation of Junctional Adhesion Molecule-A Expression Induces Cell Apoptosis and Reduces Breast Cancer Progression

Intercellular junctions promote homotypic cell to cell adhesion and transfer intracellular signals which control cell growth and apoptosis. Junctional adhesion molecule-A (JAM-A) is a transmembrane immunoglobulin located at tight junctions of normal epithelial cells of mammary ducts and glands. In the present paper we show that JAM-A acts as a survival factor for mammary carcinoma cells. JAM-A null mice expressing Polyoma Middle T under MMTV promoter develop significantly smaller mammary tumors than JAM-A positive mice. Angiogenesis and inflammatory or immune infiltrate were not statistically modified in absence of JAM-A but tumor cell apoptosis was significantly increased. Tumor cells isolated from JAM-A null mice or 4T1 cells incubated with JAM-A blocking antibodies showed reduced growth and increased apoptosis which paralleled altered junctional architecture and adhesive function. In a breast cancer clinical data set, tissue microarray data show that JAM-A expression correlates with poor prognosis. Gene expression analysis of mouse tumor samples showed a correlation between genes enriched in human G3 tumors and genes over expressed in JAM-A +/+ mammary tumors. Conversely, genes enriched in G1 human tumors correlate with genes overexpressed in JAM-A−/− tumors. We conclude that down regulation of JAM-A reduces tumor aggressive behavior by increasing cell susceptibility to apoptosis. JAM-A may be considered a negative prognostic factor and a potential therapeutic target

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Data Publication with the Structural Biology Data Grid Supports Live Analysis

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis