32 resultados para DNA-protein interactions

em CentAUR: Central Archive University of Reading - UK


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Caliciviruses are a major cause of gastroenteritis in humans and cause a wide variety of other diseases in animals. Here, the characterization of protein-protein interactions between the individual proteins of Feline calicivirus (FCV), a model system for other members of the family Caliciviridae, is reported. Using the yeast two-hybrid system combined with a number of other approaches, it is demonstrated that the p32 protein (the picornavirus 2B analogue) of FCV interacts with p39 (2C), p30 (3A) and p76 (3CD). The FCV protease/RNA polymerase (ProPol) p76 was found to form homo-oligomers, as well as to interact with VPg and ORF2, the region encoding the major capsid protein VP1. A weak interaction was also observed between p76 and the minor capsid protein encoded by ORF3 (VP2). ORF2 protein was found to interact with VPg, p76 and VP2. The potential roles of the interactions in calicivirus replication are discussed.

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Neoglycolipid technology is the basis of a microarray platform for assigning oligosaccharide ligands for carbohydrate-binding proteins. The strategy for generating the neoglycolipid probes by reductive amination results in ring opening of the core monosaccharides. This often limits applicability to short-chain saccharides, although the majority of recognition motifs are satisfactorily presented with neoglycolipids of longer oligosaccharides. Here, we describe neoglycolipids prepared by oxime ligation. We provide evidence from NMR studies that a significant proportion of the oxime-linked core monosaccharide is in the ring-closed form, and this form selectively interacts with a carbohydrate-binding protein. By microarray analyses we demonstrate the effective presentation with oxime-linked neoglycolipids of (1) Lewis(x) trisaccharide to antibodies to Lewisx, (2) sialyllactose analogs to the sialic acid-binding receptors, siglecs, and (3) N-glycans to a plant lectin that requires an intact N-acetylglucosamine core.

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The principal driver of nitrogen (N) losses from the body including excretion and secretion in milk is N intake. However, other covariates may also play a role in modifying the partitioning of N. This study tests the hypothesis that N partitioning in dairy cows is affected by energy and protein interactions. A database containing 470 dairy cow observations was collated from calorimetry experiments. The data include N and energy parameters of the diet and N utilization by the animal. Univariate and multivariate meta-analyses that considered both within and between study effects were conducted to generate prediction equations based on N intake alone or with an energy component. The univariate models showed that there was a strong positive linear relationships between N intake and N excretion in faeces, urine and milk. The slopes were 0.28 faeces N, 0.38 urine N and 0.20 milk N. Multivariate model analysis did not improve the fit. Metabolizable energy intake had a significant positive effect on the amount of milk N in proportion to faeces and urine N, which is also supported by other studies. Another measure of energy considered as a covariate to N intake was diet quality or metabolizability (the concentration of metabolizable energy relative to gross energy of the diet). Diet quality also had a positive linear relationship with the proportion of milk N relative to N excreted in faeces and urine. Metabolizability had the largest effect on faeces N due to lower protein digestibility of low quality diets. Urine N was also affected by diet quality and the magnitude of the effect was higher than for milk N. This research shows that including a measure of diet quality as a covariate with N intake in a model of N execration can enhance our understanding of the effects of diet composition on N losses from dairy cows. The new prediction equations developed in this study could be used to monitor N losses from dairy systems.

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Repair of both normal and reduced AP sites is activated by AP endonuclease, which recognizes and cleaves a phosphodiester bond 5' to the AP site. For a short period of time an incised AP site is occupied by poly(ADP-ribose) polymerase and then DNA polymerase beta adds one nucleotide into the repair gap and simultaneously removes the 5'-sugar phosphate. Finally, the DNA ligase III/XRCC1 complex accomplishes repair by sealing disrupted DNA ends. However, long-patch BER pathway, which is involved in the removal of reduced abasic sites, requires further DNA synthesis resulting in strand displacement and the generation of a damage-containing flap that is later removed by the flap endonuclease. Strand-displacement DNA synthesis is accomplished by DNA polymerase delta/epsilon and DNA ligase I restores DNA integrity. DNA synthesis by DNA polymerase delta/epsilon is dependent on proliferating cell nuclear antigen, which also stimulates the DNA ligase I and flap endonuclease. These repair events are supported by multiple protein-protein interactions. (C) 2003 Elsevier B.V. All rights reserved.

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Flagellate bacteria such as Escherichia coli and Salmonella enterica serovar Typhimurium typically express 5 to 12 flagellar filaments over their cell surface that rotate in clockwise (CW) and counterclockwise directions. These bacteria modulate their swimming direction towards favorable environments by biasing the direction of flagellar rotation in response to various stimuli. In contrast, Rhodobacter sphaeroides expresses a single subpolar flagellum that rotates only CW and responds tactically by a series of biased stops and starts. Rotor protein FliG transiently links the MotAB stators to the rotor, to power rotation and also has an essential function in flagellar export. In this study, we sought to determine whether the FliG protein confers directionality on flagellar motors by testing the functional properties of R. sphaeroides FliG and a chimeric FliG protein, EcRsFliG (N-terminal and central domains of E. coli FliG fused to an R. sphaeroides FliG C terminus), in an E. coli FliG null background. The EcRsFliG chimera supported flagellar synthesis and bidirectional rotation; bacteria swam and tumbled in a manner qualitatively similar to that of the wild type and showed chemotaxis to amino acids. Thus, the FliG C terminus alone does not confer the unidirectional stop-start character of the R. sphaeroides flagellar motor, and its conformation continues to support tactic, switch-protein interactions in a bidirectional motor, despite its evolutionary history in a bacterium with a unidirectional motor.

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The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.

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An important element of the developing field of proteomics is to understand protein-protein interactions and other functional links amongst genes. Across-species correlation methods for detecting functional links work on the premise that functionally linked proteins will tend to show a common pattern of presence and absence across a range of genomes. We describe a maximum likelihood statistical model for predicting functional gene linkages. The method detects independent instances of the correlated gain or loss of pairs of proteins on phylogenetic trees, reducing the high rates of false positives observed in conventional across-species methods that do not explicitly incorporate a phylogeny. We show, in a dataset of 10,551 protein pairs, that the phylogenetic method improves by up to 35% on across-species analyses at identifying known functionally linked proteins. The method shows that protein pairs with at least two to three correlated events of gain or loss are almost certainly functionally linked. Contingent evolution, in which one gene's presence or absence depends upon the presence of another, can also be detected phylogenetically, and may identify genes whose functional significance depends upon its interaction with other genes. Incorporating phylogenetic information improves the prediction of functional linkages. The improvement derives from having a lower rate of false positives and from detecting trends that across-species analyses miss. Phylogenetic methods can easily be incorporated into the screening of large-scale bioinformatics datasets to identify sets of protein links and to characterise gene networks.

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G-protein-coupled receptors (GPCRs) represent the largest family of receptors involved in transmembrane signaling. Although these receptors were generally believed to be monomeric entities, accumulating evidence supports the presence of GPCRs in multimeric forms. Here, using immunoprecipitation as well as time-resolved fluorescence resonance energy transfer to assess protein-protein interactions in living cells, we unambiguously demonstrate the occurrence of dimerization of the human histamine H-1 receptor. We also show the presence of domain-swapped H-1 receptor dimers in which there is the reciprocal exchange of transmembrane domain TM domains 6 and 7 between the receptors present in the dimer. Mutation of aspartate(107) in transmembrane (TM) 3 or phenylalanine(432) in TM6 to alanine results in two radioligand-binding-deficient mutant H-1 receptors. Coexpression of H-1 D(107)A and H-1 F(432)A, however, results in a reconstituted radioligand binding site that exhibits a pharmacological profile that corresponds to the wildtype H-1 receptor. Interestingly, the H-1 receptor radioligands [H-3] mepyramine and [H-3]-(-)- trans-1-phenyl-3-N, N-dimethylamino-1,2,3,4-tetrahydronaphthalene show differential saturation binding values (B-max) for wild-type H-1 receptors but not for the radioligand binding site that is formed upon coexpression of H-1 D(107)A and H-1 F(432)A receptors, suggesting the presence of different H-1 receptor populations.

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The completion of the Human Genome Project has revealed a multitude of potential avenues for the identification of therapeutic targets. Extensive sequence information enables the identification of novel genes but does not facilitate a thorough understanding of how changes in gene expression control the molecular mechanisms underlying the development and regulation of a cell or the progression of disease. Proteomics encompasses the study of proteins expressed by a population of cells, and evaluates changes in protein expression, post-translational modifications, protein interactions, protein structure and splice variants, all of which are imperative for a complete understanding of protein function within the cell. From the outset, proteomics has been used to compare the protein profiles of cells in healthy and diseased states and as such can be used to identify proteins associated with disease development and progression. These candidate proteins might provide novel targets for new therapeutic agents or aid the development of assays for disease biomarkers. This review provides an overview of the current proteomic techniques available and focuses on their application in the search for novel therapeutic targets for the treatment of disease.