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Computational and Experimental Validation of B and TCell Epitopes of the In Vivo Immune Response to a Novel Malarial Antigen
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Computational and Experimental Validation of B and T- Cell ~ Computational and Experimental Validation of B and T-Cell Epitopes of the In Vivo Immune Response to a Novel Malarial Antigen 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)
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Computational and Experimental Validation of B and T-Cell ~ Computational and Experimental Validation of B and T-Cell Epitopes of the In Vivo Immune Response to a Novel Malarial Antigen. Elke S. Bergmann-Leitner, Sidhartha Chaudhury, Nicholas J. Steers, Mark Sabato, Vito Delvecchio, Anders S. Wallqvist, Christian F. Ockenhouse, Evelina Angov
Computational and Experimental Validation of B and T-Cell ~ Computational and Experimental Validation of B and T-Cell Epitopes of the In Vivo Immune Response to a Novel Malarial Antigen By Elke S. Bergmann-Leitner, Sidhartha Chaudhury, Nicholas J. Steers, Mark Sabato, Vito Delvecchio, Anders S. Wallqvist, Christian F. Ockenhouse and Evelina Angov
Computational analysis in designing T cell epitopes ~ In one recent study on malarial antigen, some epitopes predicted by ABCpred were found to match with experimentally identified epitopes in immune rabbit antiserum (Bergmann-Leitner et al., 2013). Hence, in the present study, identified peptides containing multiple T cell epitopes were looked for the presence of B cell epitopes and four out of .
Removing T-cell epitopes with computational protein design ~ Removing T-cell epitopes with computational protein design Chris Kinga,1, Esteban N. Garzab, Ronit Mazorc, Jonathan L. Linehand, Ira Pastanc, Marion Pepperb, and David Bakera aInstitute for Protein Design, Department of Biochemistry and bDepartment of Immunology, University of Washington, Seattle, WA 98195; and cNational Cancer Institute and dNational Institute of Allergy and Infectious .
Fundamentals and Methods for T- and B-Cell Epitope Prediction ~ Adaptive immunity is mediated by T- and B-cells, which are immune cells capable of developing pathogen-specific memory that confers immunological protection. Memory and effector functions of B- and T-cells are predicated on the recognition through specialized receptors of specific targets (antigens) in pathogens. More specifically, B- and T-cells recognize portions within their cognate .
Using a Combined Computational-Experimental Approach to ~ Introduction. B cell, or antibody (Ab), epitopes hold the key for understanding antigenic interactions. They are also instrumental in many applications such as vaccine design, disease prevention, diagnostics, and therapy (Yang and Yu, 2009).Correct identification of epitopes can reveal the molecular effect of Abs on their antigens (Ags).
Computational Design of Epitope-Specific Functional ~ Nimrod et al. present an approach to computational design of epitope-specific antibodies. Using in silico methods targeting a chosen epitope, a functional antibody to IL-17A was engineered. The antibody binds IL-17A at the targeted epitope. A machine learning classifier predicts functionally relevant contacts between antigen and antibody.
Current methods for the prediction of Tācell epitopes ~ Computational and Experimental Validation of B and T-Cell Epitopes of the In Vivo Immune Response to a Novel Malarial Antigen. Article. . predict the in vivo immune responses emphasizes the need .
Computational Peptide Vaccinology / SpringerLink ~ Bergmann-Leitner ES, Chaudhury S, Steers NJ et al (2013) Computational and experimental validation of B and T-cell epitopes of the in vivo immune response to a novel malarial antigen. PLoS One 8:e71610 PubMedCentral PubMed CrossRef Google Scholar
B Cell Epitope Prediction Tools - Immune Epitope Database ~ A collection of methods to predict linear B cell epitopes based on sequence characteristics of the antigen using amino acid scales and HMMs. Discotope - Prediction of epitopes from protein structure This method incorporates solvent-accessible surface area calculations, as well as contact distances into its prediction of B cell epitope potential .
T Cell Tools ~ The LYRA server predicts structures for either T-Cell Receptors (TCR) or B-Cell Receptors (BCR) using homology modelling. Framework templates are selected based on BLOSUM score, and complementary determining regions (CDR) are then selected if needed based on a canonical structure model and grafted onto the framework templates.
Computational Prediction of Conformational B-Cell Epitopes ~ The identification of conformational B-cell epitopes is of great importance to immunologists for facilitating the design of peptide-based vaccines. As an attempt to narrow the search for experimental validation, various computational models have been developed for the epitope prediction by using antigen structures.
Frontiers / A Review on T Cell Epitopes Identified Using ~ Paul S, Arlehamn CSL, Schulten V, Westernberg L, Sidney J, Peters B, et al. Experimental validation of the RATE tool for inferring HLA restrictions of T cell epitopes. BMC Immunol . (2017) 18(Suppl. 1):20. doi: 10.1186/s12865-017-0204-1
Reliable prediction of T-cell epitopes using neural ~ 2Department of Experimental Immunology, Institute of Medical Microbiology and Immunology, University of Copenhagen, Blegdamsvej 3C, DK-2200 Copenhagen, Denmark (RECEIVED November 14, 2002; ACCEPTED February 19, 2003) Abstract In this paper we describe an improved neural network method to predict T-cell class I epitopes. A novel
Predicting CD4 T-cell epitopes based on antigen cleavage ~ Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides on MHC class II (pMHCII), and T-cell receptor (TCR) recognition of pMHCII complexes.
Removing T-cell epitopes with computational protein design ~ Immune responses can make protein therapeutics ineffective or even dangerous. We describe a general computational protein design method for reducing immunogenicity by eliminating known and predicted T-cell epitopes and maximizing the content of human peptide sequences without disrupting protein structure and function.
Linear B cell epitope prediction for epitope vaccine ~ The interaction between an antibody and its antigen is at the heart of the humoral immune response. The detection of highly immunogenic regions within a given protein, specifically those that elicit a humoral immune response, i.e., B cell epitopes, is central to many immunodetection and immunotherapeutic applications (Irving et al. 2001).Antibodies bind to their corresponding antigens at .
Mutated BCR-ABL Generates Immunogenic T-cell Epitopes in ~ Purpose: Characterization of an approach to identify leukemia neoantigens arising in the context of drug resistance. Experimental Design: We assessed whether leukemia neoantigens could be generated from drug-resistant mutations in BCR-ABL after imatinib relapse in patients with chronic myelogenous leukemia (CML). Results: We computationally predicted that approximately 70 peptides derived from .
T-Cell Epitope Discovery for Therapeutic Cancer Vaccines ~ The success of recent immune checkpoint blockade trials in solid tumors has demonstrated the tremendous potential of immune-mediated treatment strategies for cancer therapy. These immune therapies activate preexisting cytotoxic CD8(+) T cells (CTL) to selectively target and eradicate malignant cells.In vitro models suggest that these therapies may be more effective in combination with priming .
Chapter 3. Antigens ~ -T and B cells recognize different epitopes on an antigen-Each different protein and glycoprotein of a virus (or bacterium or foreign cell) constitutes a different antigen-Each different antigen contains a number of different epitopes INCREASED COMPLEXITY Properties of B cell epitopes (Table 3-4)-Usually dependent on the native, tertiary .
An Introduction to B-Cell Epitope Mapping and In Silico ~ Identification of B-cell epitopes is a fundamental step for development of epitope-based vaccines, therapeutic antibodies, and diagnostic tools. Epitope-based antibodies are currently the most promising class of biopharmaceuticals. In the last decade, in-depth in silico analysis and categorization of the experimentally identified epitopes stimulated development of algorithms for epitope .
Prediction of continuous Bācell epitopes in an antigen ~ Bācell epitopes play a vital role in the development of peptide vaccines, in diagnosis of diseases, and also for allergy research. Experimental methods used for characterizing epitopes are time consuming and demand large resources. The availability of epitope prediction method(s) can rapidly aid experimenters in simplifying this problem.
Detection of T-cell epitopes and their application to ~ From genome to vaccine: in silico predictions, ex vivo verification De Groot et al. Vaccine (2001). Bioinformatics tools for identifying class I-restricted epitopes. Bill Martin, et al., Methods (2003) Modeling the immunogenicity of therapeutic proteins using T cell epitope mapping De Groot et al. Developments in Biologicals (2003)