70 resultados para Interaction network


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We have identified strong topoisomerase sites (STS) for Mycobacteruim smegmatis topoisomerase I in double-stranded DNA context using electrophoretic mobility shift assay of enzyme-DNA covalent complexes; Mg2+, an essential component for DNA relaxation activity of the enzyme, is not required for binding to DNA, The enzyme makes single-stranded nicks, with transient covalent interaction at the 5'-end of the broken DNA strand, a characteristic akin to prokaryotic topoisomerases. More importantly, the enzyme binds to duplex DNA having a preferred site with high affinity, a. property similar to the eukaryotic type I topoisomerases, The preferred cleavage site is mapped on a 65 bp duplex DNA and found to be CG/TCTT. Thus, the enzyme resembles other prokaryotic type I topoisomerases in mechanistics of the reaction, but is similar to eukaryotic enzymes in DNA recognition properties.

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The structural stabilizing property of 2,2,2-trifluoroethanol (TFE) in peptides has been widely demonstrated, More recently, TFE has been shown to enhance secondary structure content in globular proteins, and to influence quaternary interactions in protein multimers. The molecular mechanisms by which TFE exerts its Influence on peptide and protein structures remain poorly understood. The present analysis integrates the known physical properties of TFE with a variety of experimental observations on the interaction of TFE with peptides and proteins and on the properties of fluorocarbons. Two features of TFE, namely the hydrophobicity of the trifluoromethyl group and the hydrogen bonding character (strong donor and poor acceptor), emerge as the most important factors for rationalising the observed effects of TFE. A model is proposed for TFE interaction with peptides which involves an initial replacement of the hydration shell by fluoroalcohol molecules, a process driven by apolar interactions and favourable entropy of dehydration. Subsequent bifurcated hydrogen-bond formation with peptide carbonyl groups, which leave intramolecular interactions unaffected, promotes secondary structure formation.

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On the basis of a more realistic tetrakaidecahedral structure of foam bubbles, a network model of static foam drainage has been developed. The model considers the foam to be made up of films and Plateau borders. The films drain into the adjacent Plateau borders, which in turn form a network through which the liquid moves from the foam to the liquid pool. From the structure, a unit flow cell was found, which constitutes the foam when stacked together both horizontally and vertically. Symmetry in the unit flow cell indicates that the flow analysis of a part of it can be employed to obtain the drainage for the whole foam. Material balance equations have been written for each segment of this subsection, ensuring connectivity, and solved with the appropriate boundary and initial conditions. The calculated rates of drainage, when compared with the available experimental results, indicate that the model predicts the experimental results well.

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In this paper, we present an improved load distribution strategy, for arbitrarily divisible processing loads, to minimize the processing time in a distributed linear network of communicating processors by an efficient utilization of their front-ends. Closed-form solutions are derived, with the processing load originating at the boundary and at the interior of the network, under some important conditions on the arrangement of processors and links in the network. Asymptotic analysis is carried out to explore the ultimate performance limits of such networks. Two important theorems are stated regarding the optimal load sequence and the optimal load origination point. Comparative study of this new strategy with an earlier strategy is also presented.

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Interaction between Paenibacillus polymyxa with minerals such as hematite, corundum, quartz and kaolinite brought about significant surface chemical changes on all the minerals. Quartz and kaolinite were rendered more hydrophobic, while hematite and corundum, became more hydrophilic after biotreatment. The predominance of bacterial polysaccharides on interacted hematite and corundum and of proteins on quartz and kaolinite was responsible for the above surface-chemical changes. Bio-pretreatment of the above iron ore mineral mixtures resulted in the selective separation of silica and alumina from iron oxide, through bioflotation and bioflocculation. The utility of bioprocessing in the beneficiation of iron ores is demonstrated.

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We analyse the fault-tolerant parameters and topological properties of a hierarchical network of hypercubes. We take a close look at the Extended Hypercube (EH) and the Hyperweave (HW) architectures and also compare them with other popular architectures. These two architectures have low diameter and constant degree of connectivity making it possible to expand these networks without affecting the existing configuration. A scheme for incrementally expanding this network is also presented. We also look at the performance of the ASCEND/DESCEND class of algorithms on these architectures.

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The interaction of Cibacron blue F3GA with ribosome inactivating proteins, ricin, ricin A-chain and momordin has been investigated using difference absorption spectroscopy. Ricin was found to bind the dye with a 20- and 2-fold lower affinity than ricin A-chain and momordin, respectively. A time dependent increase in the amplitude of Cibacron blue difference spectrum in the presence of ricin was observed on addition of beta-mercaptoethanol. Analysis of the kinetic profile of this increase showed a biphasic phenomenon and the observed rates were found to be independent of the concentration of beta-mercaptoethanol. Kinetics of reduction of the intersubunit disulphide bond in ricin by beta-mercaptoethanol showed that reduction pet se is a second order reaction. Therefore, the observed changes in the difference spectra of Cibacron blue probably indicate a slow change in the conformation of ricin, triggered by reduction of the intersubunit disulphide bond.

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In recent years there has been considerable interest in developing new types of gelators of organic solvents.1 Despite the recent advances, a priori design of a gelator for gelling a given solvent has remained a challenging task. Various noncovalent interactions like hydrogen-bonding,2 metal coordination3 etc. have been used as the driving force for the gelation process. A special class of cholesterol-based gelators were reported by Weiss,4 and by Shinkai.5 Gels derived from these molecules have been used for chiral recognition/sensing,6 for studying photo- and metal-responsive functions,7 and as templates to make hollow fiber silica.8 Other types of organogels have been used for designing polymerized 9 and reverse aerogels,10 and in molecular imprinting.11 Hanabusa’s group has recently reported organogels with a bile acid derivative.12 This has prompted us to disclose our results on a novel electron donor–acceptor (EDA) interaction mediated two-component13 gelator system based on the bile acid14 backbone.

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An understanding of the effect of specific solute-solvent interactions on the diffusion of a solute probe is a long standing problem of physical chemistry. In this paper a microscopic treatment of this effect is presented. The theory takes into account the modification of the solvent structure around the solute due to this specific interaction between them. It is found that for strong, attractive interaction, there is an enhanced coupling between the solute and the solvent dynamic modes (in particular, the density mode), which leads to a significant increase in the friction on the solute. The diffusion coefficient of the solute is found to depend strongly and nonlinearly on the magnitude of the attractive interaction. An interesting observation is that specific solute-solvent interaction can induce a crossover from a sliplike to a sticklike diffusion. In the limit of strong attractive interaction, we recover a dynamic version of the solvent-berg picture. On the other hand, for repulsive interaction, the diffusion coefficient of the solute increases. These results are in qualitative agreement with recent experimental observations.

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Intravenous immunoglobulin (IVIg) is widely used to treat autoimmune diseases. Several mutually nonexclusive mechanisms are proposed to explain the beneficial effects of IVIg in patients (1, 2). Lately, Ravetch and colleagues (3) demonstrate that anti-inflammatory activity of IVIg is mediated mainly by antibodies that contain terminal _2,6-sialic acid linkages at the Asn297-linked glycan of Fc region.

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RecJ exonuclease plays crucial roles in several DNA repair and recombination pathways, and its ubiquity in bacterial species points to its ancient origin and vital cellular function. RecJ exonuclease from Haemophilus influenzae is a 575-amino-acid protein that harbors the characteristic motifs conserved among RecJ homologs. The purified protein exhibits a process 5'-3' single-stranded-DNA-specific exonuclease activity. The exonuclease activity of H. influenzae RecJ (HiRecJ) was supported by Mg2+ or Mn2+ and inhibited by Cd2+ suggesting a different mode of metal binding in HiRecJ as compared to Escherichia coli RecJ (EcoRecJ). Site-directed mutagenesis of highly conserved residues in HiRecJ abolished enzymatic activity. Interestingly, substitution of alanine for aspartate 77 resulted in a catalytically inactive enzyme that bound to DNA with a significantly higher affinity as compared to the wild-type enzyme. Noticeably, steady-state kinetic studies showed that H. influenzae single-stranded DNA-binding protein (HiSSB) increased the affinity of HiRecJ for single-stranded DNA and stimulated its exonuclease activity. HiSSB, whose C-terminal tail had been deleted, failed to enhance RecJ exonuclease activity. More importantly, HiRecJ was found to directly associate with its cognate single-stranded DNA-binding protein (SSB), as demonstrated by various in vitro assays, Interaction studies carried out with the truncated variants of HiRecJ and HiSSB revealed that the two proteins interact via the C-terminus of SSB protein and the core-catalytic domain of RecJ. Taken together, these results emphasize direct interactio between RecJ and SSB, which confers functional cooperativity to these two proteins. In addition, these results implicate SSB as being involved in the recruitment of RecJ to DNA and provide insights into the interplay between these proteins in repair and recombination pathways.

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Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms. Results The protein structure networks (PSN) are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies. Conclusion The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the potential direction towards the design of inhibitors of LuxS and thus towards a wide range of antimicrobials.

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Pt ions-CeO2 interaction in Ce1-xPtxO2-delta (x=0.02) has been studied for the first time by electrochemical method combined with x-ray diffraction and x-ray photoelectron spectroscopy. Working electrodes made of CeO2 and Ce0.98Pt0.02O2-delta mixed with 30% carbon are treated electrochemically between 0.0-1.2 V in potentiostatic (chronoamperometry) and potentiodynamic (cyclic voltametry) mode with reference to saturated calomel electrode. Reversible oxidation of Pt-0 to Pt2+ and Pt4+ state due to the applied positive potential is coupled to simultaneous reversible reduction of Ce4+ to Ce3+ state. CeO2 reduces to CeO2-y (y=0.35) after applying 1.2 V, which is not reversible; Ce0.98Pt0.02O2-delta reaches a steady state with Pt2+:Pt4+ in the ratio of 0.60:0.40 and Ce4+:Ce3+ in the ratio of 0.55:0.45 giving a composition Ce0.98Pt0.02O1.74 at 1.2 V, which is reversible. Composition of Pt ion substituted compound is reversible between Ce0.98Pt0.02O1.95 to Ce0.98Pt0.02O1.74 within the potential range of 0.0-1.2 V. Thus, Ce0.98Pt0.02O2-delta forms a stable electrode for oxidation of H2O to O-2 unlike CeO2. A linear relation between oxidation of Pt2+ to Pt4+ with simultaneous reduction in Ce4+ to Ce3+ is observed demonstrating Pt-CeO2 metal support interaction is due to reversible Pt-0/Pt2+/Pt4+ interaction with Ce4+/Ce3+ redox couple.

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The nicotinic Acetylcholine Receptor (nAChR) is the major class of neurotransmitter receptors that is involved in many neurodegenerative conditions such as schizophrenia, Alzheimer's and Parkinson's diseases. The N-terminal region or Ligand Binding Domain (LBD) of nAChR is located at pre- and post-synaptic nervous system, which mediates synaptic transmission. nAChR acts as the drug target for agonist and competitive antagonist molecules that modulate signal transmission at the nerve terminals. Based on Acetylcholine Binding Protein (AChBP) from Lymnea stagnalis as the structural template, the homology modeling approach was carried out to build three dimensional model of the N-terminal region of human alpha(7)nAChR. This theoretical model is an assembly of five alpha(7) subunits with 5 fold axis symmetry, constituting a channel, with the binding picket present at the interface region of the subunits. alpha-netlrotoxin is a potent nAChR competitive antagonist that readily blocks the channel resulting in paralysis. The molecular interaction of alpha-Bungarotoxin, a long chain alpha-neurotoxin from (Bungarus multicinctus) and human alpha(7)nAChR seas studied. Agonists such as acetylcholine, nicotine, which are used in it diverse array of biological activities, such as enhancements of cognitive performances, were also docked with the theoretical model of human alpha(7)nAChR. These docked complexes were analyzed further for identifying the crucial residues involved i interaction. These results provide the details of interaction of agonists and competitive antagonists with three dimensional model of the N-terminal region of human alpha(7)nAChR and thereby point to the design of novel lead compounds.

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Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.