20 resultados para protein analysis

em CentAUR: Central Archive University of Reading - UK


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It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.

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It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.

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DIGE is a protein labelling and separation technique allowing quantitative proteomics of two or more samples by optical fluorescence detection of differentially labelled proteins that are electrophoretically separated on the same gel. DIGE is an alternative to quantitation by MS-based methodologies and can circumvent their analytical limitations in areas such as intact protein analysis, (linear) detection over a wide range of protein abundances and, theoretically, applications where extreme sensitivity is needed. Thus, in quantitative proteomics DIGE is usually complementary to MS-based quantitation and has some distinct advantages. This review describes the basics of DIGE and its unique properties and compares it to MS-based methods in quantitative protein expression analysis.

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The yncE gene of Escherichia coli encodes a predicted periplasmic protein of unknown function. The gene is de-repressed under iron restriction through the action of the global iron regulator Fur. This suggests a role in iron acquisition, which is supported by the presence of the adjacent yncD gene encoding a potential TonB-dependent outer-membrane transporter. Here, the preliminary crystallographic structure of YncE is reported, revealing that it consists of a seven-bladed beta-propeller which resembles the corresponding domain of the `surface-layer protein' of Methanosarcina mazei. A full structure determination is under way in order to provide insight into the function of this protein.

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Motivation: Intrinsic protein disorder is functionally implicated in numerous biological roles and is, therefore, ubiquitous in proteins from all three kingdoms of life. Determining the disordered regions in proteins presents a challenge for experimental methods and so recently there has been much focus on the development of improved predictive methods. In this article, a novel technique for disorder prediction, called DISOclust, is described, which is based on the analysis of multiple protein fold recognition models. The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified. Results: The DISOclust method is shown to add the most value to a simple consensus of methods, even in the absence of target sequence homology to known structures. A simple consensus of methods that includes DISOclust can significantly outperform all of the previous individual methods tested.

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Severe acute respiratory syndrome (SARS) coronavirus infection and growth are dependent on initiating signaling and enzyme actions upon viral entry into the host cell. Proteins packaged during virus assembly may subsequently form the first line of attack and host manipulation upon infection. A complete characterization of virion components is therefore important to understanding the dynamics of early stages of infection. Mass spectrometry and kinase profiling techniques identified nearly 200 incorporated host and viral proteins. We used published interaction data to identify hubs of connectivity with potential significance for virion formation. Surprisingly, the hub with the most potential connections was not the viral M protein but the nonstructurall protein 3 (nsp3), which is one of the novel virion components identified by mass spectrometry. Based on new experimental data and a bioinformatics analysis across the Coronaviridae, we propose a higher-resolution functional domain architecture for nsp3 that determines the interaction capacity of this protein. Using recombinant protein domains expressed in Escherichia coli, we identified two additional RNA-binding domains of nsp3. One of these domains is located within the previously described SARS-unique domain, and there is a nucleic acid chaperone-like domain located immediately downstream of the papain-like proteinase domain. We also identified a novel cysteine-coordinated metal ion-binding domain. Analyses of interdomain interactions and provisional functional annotation of the remaining, so-far-uncharacterized domains are presented. Overall, the ensemble of data surveyed here paint a more complete picture of nsp3 as a conserved component of the viral protein processing machinery, which is intimately associated with viral RNA in its role as a virion component.

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Background: The hepatitis C virus (HCV) non-structural 5A protein (NS5A) contains a highly conserved C-terminal polyproline motif with the consensus sequence Pro-X-X- Pro-X-Arg that is able to interact with the Src-homology 3 (SH3) domains of a variety of cellular proteins. Results: To understand this interaction in more detail we have expressed two N-terminally truncated forms of NS5A in E. coli and examined their interactions with the SH3 domain of the Src-family tyrosine kinase, Fyn. Surface plasmon resonance analysis revealed that NS5A binds to the Fyn SH3 domain with what can be considered a high affinity SH3 domain-ligand interaction (629 nM), and this binding did not require the presence of domain I of NS5A (amino acid residues 32-250). Mutagenic analysis of the Fyn SH3 domain demonstrated the requirement for an acidic cluster at the C-terminus of the RT-Src loop of the SH3 domain, as well as several highly conserved residues previously shown to participate in SH3 domain peptide binding. Conclusion: We conclude that the NS5A: Fyn SH3 domain interaction occurs via a canonical SH3 domain binding site and the high affinity of the interaction suggests that NS5A would be able to compete with cognate Fyn ligands within the infected cell.

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YcdB is a periplasmic haem-containing protein from Escherichia coli that has a potential role in iron transport. It is currently the only reported haem-containing Tat-secreted substrate. Here, the overexpression, purification, crystallization and structure determination at 2.0 angstrom resolution are reported for the apo form of the protein. The apo-YcdB structure resembles those of members of the haem-dependent peroxidase family and thus confirms that YcdB is also a member of this family. Haem-soaking experiments with preformed apo-YcdB crystals have been optimized to successfully generate haem-containing YcdB crystals that diffract to 2.9 angstrom. Completion of model building and structure refinement are under way.

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Background: We report an analysis of a protein network of functionally linked proteins, identified from a phylogenetic statistical analysis of complete eukaryotic genomes. Phylogenetic methods identify pairs of proteins that co-evolve on a phylogenetic tree, and have been shown to have a high probability of correctly identifying known functional links. Results: The eukaryotic correlated evolution network we derive displays the familiar power law scaling of connectivity. We introduce the use of explicit phylogenetic methods to reconstruct the ancestral presence or absence of proteins at the interior nodes of a phylogeny of eukaryote species. We find that the connectivity distribution of proteins at the point they arise on the tree and join the network follows a power law, as does the connectivity distribution of proteins at the time they are lost from the network. Proteins resident in the network acquire connections over time, but we find no evidence that 'preferential attachment' - the phenomenon of newly acquired connections in the network being more likely to be made to proteins with large numbers of connections - influences the network structure. We derive a 'variable rate of attachment' model in which proteins vary in their propensity to form network interactions independently of how many connections they have or of the total number of connections in the network, and show how this model can produce apparent power-law scaling without preferential attachment. Conclusion: A few simple rules can explain the topological structure and evolutionary changes to protein-interaction networks: most change is concentrated in satellite proteins of low connectivity and small phenotypic effect, and proteins differ in their propensity to form attachments. Given these rules of assembly, power law scaled networks naturally emerge from simple principles of selection, yielding protein interaction networks that retain a high-degree of robustness on short time scales and evolvability on longer evolutionary time scales.

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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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Differences in the expression of cell surface proteins between a normal prostate epithelial (1542-NP2TX) and a prostate cancer cell line (1542-CP3TX) derived from the same patient were investigated. A combination of affinity chromatographic purification of biotin-tagged surface proteins with mass spectrometry analysis identified 26 integral membrane proteins and 14 peripheral surface proteins. The findings confirm earlier reports of altered expression in prostate cancer for several cell surface proteins, including ALCAM/CD166, the Ephrin type A receptor, EGFR and the prostaglandin F2 receptor regulatory protein. In addition, several novel findings of differential expression were made, including the voltage-dependent anion selective channel proteins Porin 1 and 2, ecto-5'-nucleotidase (CD73) and Scavenger receptor B1. Cell surface protein expression changed both qualitatively and quantitatively when the cells were grown in the presence of either or both interferon INFalpha and INFgamma. Costimulation with type I and II interferons had additive or synergistic effects on the membrane density of several, mainly peripherally attached surface proteins. Concerted upregulation of surface exposed antigens may be of benefit in immuno-adjuvant-based treatment of interferon-responsive prostate cancer. In conclusion, this study demonstrates that differences in the expression of membrane proteins between normal and prostate cancer cells are reproducibly detectable following vectorial labelling with biotin, and that detailed analysis of extracellular-induced surface changes can be achieved by combining surface-specific labelling with high-resolution two-dimensional gel electrophoresis and mass spectrometry.

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We have developed a new method for the analysis of voids in proteins (defined as empty cavities not accessible to solvent). This method combines analysis of individual discrete voids with analysis of packing quality. While these are different aspects of the same effect, they have traditionally been analysed using different approaches. The method has been applied to the calculation of total void volume and maximum void size in a non-redundant set of protein domains and has been used to examine correlations between thermal stability and void size. The tumour-suppressor protein p53 has then been compared with the non-redundant data set to determine whether its low thermal stability results from poor packing. We found that p53 has average packing, but the detrimental effects of some previously unexplained mutations to p53 observed in cancer can be explained by the creation of unusually large voids. (C) 2004 Elsevier Ltd. All rights reserved.

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A dopamine D-2Short receptor:G(alphao) fusion protein was expressed in Sf9 cells using the baculovirus expression system. [H-3]Spiperone bound to D-2Short:G(alphao) with a pK(d) approximate to 10. Dopamine stimulated the binding of [S-35]guanosine-5'-O-(3-thio)triphosphate (GTPgammaS) to D-2Short:G(alphao) expressed with Gbeta(1)gamma(2) (E-max > 460%; pEC(50) 5.43 +/- 0.06). Most of the putative D-2 antagonists behaved as inverse agonists (suppressing basal [S-35]GTPgammaS binding) at D-2Short:G(alphao)/Gbeta(1)gamma(2) although (-)-suipiride and ziprasidone were neutral antagonists. Competition of [H-3]spiperone binding by dopamine and 10,11-dihydroxy-N-n-propylnorapo-morphine revealed two, binding sites of different affinities, even in the presence of GTP (100 muM). The D-2Short:G(alphao) fusion protein is therefore a good model for characterising D-2 receptors. (C) 2003 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

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The human D-2short (D-2S) dopamine receptor has been expressed together with the G proteins Gi2 and Go in insect cells using the baculovirus system. Levels of receptor were determined using [H-3]spiperone binding. Levels of G protein heterotrimer were determined using quantitative Western blot and using [S-35]GTPgammaS saturation binding experiments. Levels of the receptor and G protein and the receptor/G protein ratio were similar in the two preparations. Stimulation of [S-35]GTPgammaS binding by a range of agonists occurred with higher relative efficacy and in some cases higher potency in the preparation expressing Go, indicating that interaction of the D-2S receptor is more efficient with this G protein. The effects of various G protein-selective agents on 10,11-dihydroxy-N-n-propylnorapomorphine ([H-3]NPA) binding were used to examine the receptor/G protein complex in the two preparations. Suramin inhibited [H-3]NPA binding with slightly higher potency in the Gi2 preparation, whereas GppNHp inhibited [H-3]NPA binding with greater potency (similar to6-fold) in the Go preparation. This may imply that the G protein is more readily activated in the D-2S/Go preparation. [H-3]Spiperone binding occurred with an increased B-max in the presence of suramin in the Go preparation but not in the Gi2 preparation, suggesting a higher affinity interaction between the free receptor and this G protein. It is concluded that the higher efficiency activation of Go by the D-2S receptor may be a function of higher affinity receptor/G protein interaction as well as a greater ability to activate the G protein. (C) 2003 Elsevier Science Inc. All rights reserved.