3did: interacting protein domains of known three-dimensional structure

The database of 3D Interacting Domains (3did) is a collection of domain–domain interactions in proteins for which high-resolution three-dimensional structures are known. 3did exploits structural information to provide critical molecular details necessary for understanding how interactions occur. It also offers an overview of how similar in structure are interactions between different members of the same protein family. The database also contains Gene Ontology-based functional annotations and interactions between yeast proteins from large-scale interaction discovery studies. A web-based tool to query 3did is available at http://3did.embl.de

Numerical simulations of the jetted tidal disruption event Swift J1644+57

In this work we focus on the technical details of the numerical simulations of the non-thermal transient Swift J1644+57, whose emission is probably produced by a two- component jet powered by a tidal disruption event. In this context we provide details of the coupling between the relativistic hydrodynamic simulations and the radiative transfer code. First, we consider the technical demands of one-dimensional simulations of a fast relativistic jet, and show to what extent (for the same physical parameters of the model) do the computed light curves depend on the numerical parameters of the different codes employed. In the second part we explain the difficulties of computing light curves from axisymmetric two dimensonal simulations and discuss a procedure that yields an acceptable tradeoff between the computational cost and the quality of the results

Relativistic Jets from Collapsars

We have studied the relativistic beamed outflow proposed to occur in the collapsar model of gamma-ray bursts. A jet forms as a consequence of an assumed energy deposition of $\sim 10^{50}- 10^{51}$ erg/s within a $30^{\circ}$ cone around the rotation axis of the progenitor star. The generated jet flow is strongly beamed (\la few degrees) and reaches the surface of the stellar progenitor (r $\approx 3 10^{10}$cm) intact. At break-out the maximum Lorentz factor of the jet flow is about 33. Simulations have been performed with the GENESIS multi-dimensional relativistic hydrodynamic code.Comment: 6 pages, 2 figures, to appear in the proceedings of the conference "Godunov methods: theory and applications", Oxford, October 199

Graph theoretic analysis of protein interaction networks of eukaryotes

Thanks to recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, have been assayed. The datasets are obtained mainly by using the yeast hybrid method, which contains false-positive and false-negative simultaneously. Accordingly, while it is desirable to test such datasets through further wet experiments, here we invoke recent developed network theory to test such high throughput datasets in a simple way. Based on the fact that the key biological processes indispensable to maintaining life are universal across eukaryotic species, and the comparison of structural properties of the protein interaction networks (PINs) of the two species with those of the yeast PIN, we find that while the worm and the yeast PIN datasets exhibit similar structural properties, the current fly dataset, though most comprehensively screened ever, does not reflect generic structural properties correctly as it is. The modularity is suppressed and the connectivity correlation is lacking. Addition of interlogs to the current fly dataset increases the modularity and enhances the occurrence of triangular motifs as well. The connectivity correlation function of the fly, however, remains distinct under such interlogs addition, for which we present a possible scenario through an in silico modeling.Comment: 7 pages, 6 figures, 2 table

Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows

We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.Fil: Goncearenco, Alexander. National Institutes of Health; Estados UnidosFil: Li, Minghui. Soochow University; China. National Institutes of Health; Estados UnidosFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Shoemaker, Benjamin A. National Institutes of Health; Estados UnidosFil: Panchenko, Anna R. National Institutes of Health; Estados Unido

Accurate evolutions of inspiralling neutron-star binaries: assessment of the truncation error

We have recently presented an investigation in full general relativity of the dynamics and gravitational-wave emission from binary neutron stars which inspiral and merge, producing a black hole surrounded by a torus (see arXiv:0804.0594). We here discuss in more detail the convergence properties of the results presented in arXiv:0804.0594 and, in particular, the deterioration of the convergence rate at the merger and during the survival of the merged object, when strong shocks are formed and turbulence develops. We also show that physically reasonable and numerically convergent results obtained at low-resolution suffer however from large truncation errors and hence are of little physical use. We summarize our findings in an "error budget", which includes the different sources of possible inaccuracies we have investigated and provides a first quantitative assessment of the precision in the modelling of compact fluid binaries.Comment: 13 pages, 5 figures. Minor changes to match published version. Added figure 5 right pane