About: Peptide-Based Vaccinology: Experimental and Computational Approaches to Target Hypervariable Viruses through the Fine Characterization of Protective Epitopes Recognized by Monoclonal Antibodies and the Identification of T-Cell-Activating Peptides

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About: Peptide-Based Vaccinology: Experimental and Computational Approaches to Target Hypervariable Viruses through the Fine Characterization of Protective Epitopes Recognized by Monoclonal Antibodies and the Identification of T-Cell-Activating Peptides Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Peptide-Based Vaccinology: Experimental and Computational Approaches to Target Hypervariable Viruses through the Fine Characterization of Protective Epitopes Recognized by Monoclonal Antibodies and the Identification of T-Cell-Activating Peptides
Creator	Criscuolo, Elena Cappelletti, Francesca Castelli, Matteo Clementi, Nicola Dal Peraro, Matteo Sautto, Giuseppe Diotti, Roberta
Source	PMC
abstract	Defining immunogenic domains of viral proteins capable of eliciting a protective immune response is crucial in the development of novel epitope-based prophylactic strategies. This is particularly important for the selective targeting of conserved regions shared among hypervariable viruses. Studying postinfection and postimmunization sera, as well as cloning and characterization of monoclonal antibodies (mAbs), still represents the best approach to identify protective epitopes. In particular, a protective mAb directed against conserved regions can play a key role in immunogen design and in human therapy as well. Experimental approaches aiming to characterize protective mAb epitopes or to identify T-cell-activating peptides are often burdened by technical limitations and can require long time to be correctly addressed. Thus, in the last decade many epitope predictive algorithms have been developed. These algorithms are continually evolving, and their use to address the empirical research is widely increasing. Here, we review several strategies based on experimental techniques alone or addressed by in silico analysis that are frequently used to predict immunogens to be included in novel epitope-based vaccine approaches. We will list the main strategies aiming to design a new vaccine preparation conferring the protection of a neutralizing mAb combined with an effective cell-mediated response.
has issue date	2013-06-26(xsd:dateTime)
bibo:doi	10.1155/2013/521231
bibo:pmid	23878584
has license	cc-by
sha1sum (hex)	5076cec908e9bc3ba685507e00ac19deab50b02e
schema:url	https://doi.org/10.1155/2013/521231
resource representing a document's title	Peptide-Based Vaccinology: Experimental and Computational Approaches to Target Hypervariable Viruses through the Fine Characterization of Protective Epitopes Recognized by Monoclonal Antibodies and the Identification of T-Cell-Activating Peptides
has PubMed Central identifier	PMC3710646
has PubMed identifier	23878584
schema:publication	Clin Dev Immunol
resource representing a document's body	covid:5076cec908e9bc3ba685507e00ac19deab50b02e#body_text
is schema:about of	named entity 'Vaccinology' named entity 'Antibodies' named entity 'Monoclonal' named entity 'IDENTIFICATION' named entity 'BASED' named entity 'VIRUSES' named entity 'T-CELL' named entity 'ACTIVATING' named entity 'MONOCLONAL ANTIBODIES' named entity 'EXPERIMENTAL' named entity 'CHARACTERIZATION' named entity 'PEPTIDE' named entity 'PEPTIDES' named entity 'FINE' named entity 'VACCINOLOGY' named entity 'TARGET' named entity 'COMPUTATIONAL' named entity 'APPROACHES' named entity 'EPITOPES' named entity 'Viruses' named entity '3D structure' named entity 'alanine scanning' named entity 'viruses' named entity 'peptides' named entity 'antigen' named entity 'HLA' named entity 'immunogens' named entity 'allelic diversity' named entity 'ellipsoid' named entity 'mimotope' named entity 'MHC' named entity 'synergistic' named entity 'mass spectrometry' named entity 'HLA' named entity 'T-cell' named entity 'epitope' named entity 'epitopes' named entity 'antigens' named entity 'physiochemical' named entity 'bioinformatics' named entity 'structure-based' named entity 'proteolytic digestion' named entity 'intracellular' named entity 'protein' named entity 'epitopes' named entity 'epitopic' named entity 'linear epitope' named entity 'epitope' named entity 'antigen' named entity 'Protein' named entity 'MHC' named entity 'peptide' named entity 'peptide' named entity 'protein' named entity 'viruses' named entity 'proteasomal' named entity 'amino acid' named entity 'T-cell' named entity 'pathogen' named entity 'protelytic' named entity 'random forest' named entity 'epitope' named entity 'antibodies' named entity 'physiochemical' named entity 'solvent' named entity 'MHC' named entity 'peptides' named entity 'antigen' named entity 'protein' named entity 'binding affinities' named entity 'epitope' named entity 'T-cell activation' named entity 'peptides' named entity 'antigenicity' named entity 'cytokines'

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