1,353 research outputs found
DIMA 3.0: Domain Interaction Map
Domain Interaction MAp (DIMA, available at http://webclu.bio.wzw.tum.de/dima) is a database of predicted and known interactions between protein domains. It integrates 5807 structurally known interactions imported from the iPfam and 3did databases and 46 900 domain interactions predicted by four computational methods: domain phylogenetic profiling, domain pair exclusion algorithm correlated mutations and domain interaction prediction in a discriminative way. Additionally predictions are filtered to exclude those domain pairs that are reported as non-interacting by the Negatome database. The DIMA Web site allows to calculate domain interaction networks either for a domain of interest or for entire organisms, and to explore them interactively using the Flash-based Cytoscape Web software
Encounter complexes and dimensionality reduction in protein-protein association
An outstanding challenge has been to understand the mechanism whereby proteins associate. We report here the results of exhaustively sampling the conformational space in protein–protein association using a physics-based energy function. The agreement between experimental intermolecular paramagnetic relaxation enhancement (PRE) data and the PRE profiles calculated from the docked structures shows that the method captures both specific and non-specific encounter complexes. To explore the energy landscape in the vicinity of the native structure, the nonlinear manifold describing the relative orientation of two solid bodies is projected onto a Euclidean space in which the shape of low energy regions is studied by principal component analysis. Results show that the energy surface is canyon-like, with a smooth funnel within a two dimensional subspace capturing over 75% of the total motion. Thus, proteins tend to associate along preferred pathways, similar to sliding of a protein along DNA in the process of protein-DNA recognition
Electrostatics in the Stability and Misfolding of the Prion Protein: Salt Bridges, Self-Energy, and Solvation
Using a recently developed mesoscopic theory of protein dielectrics, we have
calculated the salt bridge energies, total residue electrostatic potential
energies, and transfer energies into a low dielectric amyloid-like phase for 12
species and mutants of the prion protein. Salt bridges and self energies play
key roles in stabilizing secondary and tertiary structural elements of the
prion protein. The total electrostatic potential energy of each residue was
found to be invariably stabilizing. Residues frequently found to be mutated in
familial prion disease were among those with the largest electrostatic
energies. The large barrier to charged group desolvation imposes regional
constraints on involvement of the prion protein in an amyloid aggregate,
resulting in an electrostatic amyloid recruitment profile that favours regions
of sequence between alpha helix 1 and beta strand 2, the middles of helices 2
and 3, and the region N-terminal to alpha helix 1. We found that the
stabilization due to salt bridges is minimal among the proteins studied for
disease-susceptible human mutants of prion protein
Size, shape, and flexibility of RNA structures
Determination of sizes and flexibilities of RNA molecules is important in
understanding the nature of packing in folded structures and in elucidating
interactions between RNA and DNA or proteins. Using the coordinates of the
structures of RNA in the Protein Data Bank we find that the size of the folded
RNA structures, measured using the radius of gyration, , follows the Flory
scaling law, namely, \AA where N is the number of
nucleotides. The shape of RNA molecules is characterized by the asphericity
and the shape parameters that are computed using the eigenvalues
of the moment of inertia tensor. From the distribution of , we find
that a large fraction of folded RNA structures are aspherical and the
distribution of values shows that RNA molecules are prolate (). The
flexibility of folded structures is characterized by the persistence length
. By fitting the distance distribution function to the worm-like
chain model we extracted the persistence length . We find that \AA. The dependence of on implies the average length of
helices should increases as the size of RNA grows. We also analyze packing in
the structures of ribosomes (30S, 50S, and 70S) in terms of , ,
, and . The 70S and the 50S subunits are more spherical compared to
most RNA molecules. The globularity in 50S is due to the presence of an
unusually large number (compared to 30S subunit) of small helices that are
stitched together by bulges and loops. Comparison of the shapes of the intact
70S ribosome and the constituent particles suggests that folding of the
individual molecules might occur prior to assembly.Comment: 28 pages, 8 figures, J. Chem. Phys. in pres
Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model
Folding of Ubiquitin (Ub) is investigated at low and neutral pH at different
temperatures using simulations of the coarse-grained Self-Organized-Polymer
model with side chains. The calculated radius of gyration, showing dramatic
variations with pH, is in excellent agreement with scattering experiments. At
Ub folds in a two-state manner at low and neutral pH. Clustering analysis
of the conformations sampled in equilibrium folding trajectories at , with
multiple transitions between the folded and unfolded states, show a network of
metastable states connecting the native and unfolded states. At low and neutral
pH, Ub folds with high probability through a preferred set of conformations
resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal
that Ub assembly at low pH occurs by multiple pathways involving a combination
of nucleation-collapse and diffusion collision mechanism. The mechanism by
which Ub folds is dictated by the stability of the key secondary structural
elements responsible for establishing long range contacts and collapse of Ub.
Nucleation collapse mechanism holds if the stability of these elements are
marginal, as would be the case at elevated temperatures. If the lifetimes
associated with these structured microdomains are on the order of hundreds of
then Ub folding follows the diffusion-collision mechanism with
intermediates many of which coincide with those found in equilibrium. Folding
at neutral pH is a sequential process with a populated intermediate resembling
that sampled at equilibrium. The transition state structures, obtained using a
analysis, are homogeneous and globular with most of the secondary
and tertiary structures being native-like. Many of our findings are not only in
agreement with experiments but also provide missing details not resolvable in
standard experiments
DOMINE: a database of protein domain interactions
DOMINE is a database of known and predicted protein domain interactions compiled from a variety of sources. The database contains domain–domain interactions observed in PDB entries, and those that were predicted by eight different computational approaches. DOMINE contains a total of 20 513 unique domain–domain interactions among 4036 Pfam domains, out of which 4349 are inferred from PDB entries and 17 781 were predicted by at least one computational approach. This database will serve as a valuable resource to those working in the field of protein and domain interactions. DOMINE may not only serve as a reference to experimentalists who test for new protein and domain interactions, but also offers a consolidated dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that control the topological structure of interaction networks. DOMINE is freely available at http://domine.utdallas.edu
Pocketome: an encyclopedia of small-molecule binding sites in 4D
The importance of binding site plasticity in protein–ligand interactions is well-recognized, and so are the difficulties in predicting the nature and the degree of this plasticity by computational means. To assist in understanding the flexible protein–ligand interactions, we constructed the Pocketome, an encyclopedia of about one thousand experimentally solved conformational ensembles of druggable binding sites in proteins, grouped by location and consistent chain/cofactor composition. The multiplicity of pockets within the ensembles adds an extra, fourth dimension to the Pocketome entry data. Within each ensemble, the pockets were carefully classified by the degree of their pairwise similarity and compatibility with different ligands. The core of the Pocketome is derived regularly and automatically from the current releases of the Protein Data Bank and the Uniprot Knowledgebase; this core is complemented by entries built from manually provided seed ligand locations. The Pocketome website (www.pocketome.org) allows searching for the sites of interest, analysis of conformational clusters, important residues, binding compatibility matrices and interactive visualization of the ensembles using the ActiveICM web browser plugin. The Pocketome collection can be used to build multi-conformational docking and 3D activity models as well as to design cross-docking and virtual ligand screening benchmarks
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