22 resultados para T-cell Epitope Prediction


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To ensure signalling fidelity, kinases must act only on a defined subset of cellular targets. Appreciating the basis for this substrate specificity is essential for understanding the role of an individual protein kinase in a particular cellular process. The specificity in the cell is determined by a combination of peptide specificity of the kinase (the molecular recognition of the sequence surrounding the phosphorylation site), substrate recruitment and phosphatase activity. Peptide specificity plays a crucial role and depends on the complementarity between the kinase and the substrate and therefore on their three-dimensional structures. Methods for experimental identification of kinase substrates and characterization of specificity are expensive and laborious, therefore, computational approaches are being developed to reduce the amount of experimental work required in substrate identification. We discuss the structural basis of substrate specificity of protein kinases and review the experimental and computational methods used to obtain specificity information. (c) 2005 Elsevier B.V. All rights reserved.

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Human metapneumovirus (hMPV) has emerged as an important human respiratory pathogen causing upper and lower respiratory tract infections in young children and older adults. In addition, hMPV infection is associated with asthma exacerbation in young children. Recent epidemiological evidence indicates that hMPV may cocircullate with human respiratory syncytial virus (hRSV) and mediate clinical disease similar to that seen with hRSV. Therefore, a vaccine for hMPV is highly desirable. In the present study, we used predictive bioinformatics, peptide immunization, and functional T-cell assays to define hMPV cytotoxic T-lymphocyte (CTL) epitopes recognized by mouse T cells restricted through several major histocompatibility complex class I alleles, including HILA-A*0201. We demonstrate that peptide immunization with hMPV CTL epitopes reduces viral load and immunopathollogy in the lungs of hMPV-challenged mice and enhances the expression of Th1-type cytokines (gamma interferon and interleukin-12 [IL-12]) in lungs and regional lymph nodes. In addition, we show that levels of Th2-type cytolkines (IL-10 and IL-4) are significantly lower in hMPV CTL epitope-vaccinated mice challenged with hMPV. These results demonstrate for the first time the efficacy of an hMPV CTL epitope vaccine in the control of hMPV infection in a murine model.

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The failure to mount effective immunity to virus variants in a previously virus-infected host is known as original antigenic sin. We have previously shown that prior immunity to a virus capsid protein inhibits induction by immunization of an IFN-gamma CD8(+) T cell response to an epitope linked to the capsid protein. We now demonstrate that capsid protein-primed CD4(+) T cells secrete IL-10 in response to capsid protein presented by dendritic cells, and deviate CD8+ T cells responding to a linked MHC class I-restricted epitope to reduce IFN-gamma production. Neutralizing IL-10 while delivering further linked epitope, either in vitro or in vivo, restores induction by immunization of an Ag-specific IFN-gamma response to the epitope. This finding demonstrates a strategy for overcoming inhibition of MHC class I epitopes upon immunization of a host already primed to Ag, which may facilitate immunotherapy for chronic viral infection or cancer.

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A modified UNIQUAC model has been extended to describe and predict the equilibrium relative humidity and moisture content for wood. The method is validated over a range of moisture content from oven-dried state to fiber saturation point, and over a temperature range of 20-70 degrees C. Adjustable parameters and binary interaction parameters of the UNIQUAC model were estimated from experimental data for Caribbean pine and Hoop pine as well as data available in the literature. The two group-interaction parameters for the wood-moisture system were consistent with using function group contributions for H2O, -OH and -CHO. The result reconfirms that the main contributors to water adsorption in cell walls are the hydroxyl groups of the carbohydrates in cellulose and hemicelluloses. This provides some physical insight into the intermolecular force and energy between bound water and the wood material. (c) 2006 Elsevier Ltd. All rights reserved.

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Background: Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results: In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER), peroxisome, and lysosome). The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion: No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE dataset and variable performance on individual subcellular localizations was observed. Proteins localized to the secretory pathway were the most difficult to predict, while nuclear and extracellular proteins were predicted with the highest sensitivity.