About: Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes

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About: Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes Goto Sponge NotDistinct Permalink

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes
Creator	Brusic, Vladimir Zhang, Lan August, J Guang, Email Guang, Lan Heiny, A Keong Kwoh, Chee Khan, Asif Lee, K Srinivasan, Kellathur Zhang,
Source	Medline; PMC
abstract	BACKGROUND: T-cell epitopes that promiscuously bind to multiple alleles of a human leukocyte antigen (HLA) supertype are prime targets for development of vaccines and immunotherapies because they are relevant to a large proportion of the human population. The presence of clusters of promiscuous T-cell epitopes, immunological hotspots, has been observed in several antigens. These clusters may be exploited to facilitate the development of epitope-based vaccines by selecting a small number of hotspots that can elicit all of the required T-cell activation functions. Given the large size of pathogen proteomes, including of variant strains, computational tools are necessary for automated screening and selection of immunological hotspots. RESULTS: Hotspot Hunter is a web-based computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes through analysis of antigenic diversity. It allows screening and selection of hotspots specific to four common HLA supertypes, namely HLA class I A2, A3, B7 and class II DR. The system uses Artificial Neural Network and Support Vector Machine methods as predictive engines. Soft computing principles were employed to integrate the prediction results produced by both methods for robust prediction performance. Experimental validation of the predictions showed that Hotspot Hunter can successfully identify majority of the real hotspots. Users can predict hotspots from a single protein sequence, or from a set of aligned protein sequences representing pathogen proteome. The latter feature provides a global view of the localizations of the hotspots in the proteome set, enabling analysis of antigenic diversity and shift of hotspots across protein variants. The system also allows the integration of prediction results of the four supertypes for identification of hotspots common across multiple supertypes. The target selection feature of the system shortlists candidate peptide hotspots for the formulation of an epitope-based vaccine that could be effective against multiple variants of the pathogen and applicable to a large proportion of the human population. CONCLUSION: Hotspot Hunter is publicly accessible at . It is a new generation computational tool aiding in epitope-based vaccine design.
has issue date	2008-02-13(xsd:dateTime)
bibo:doi	10.1186/1471-2105-9-s1-s19
bibo:pmid	18315850
has license	cc-by
sha1sum (hex)	d77dcb77a4a620fd1de81f309bff0e04e2578272
schema:url	https://doi.org/10.1186/1471-2105-9-s1-s19
resource representing a document's title	Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes
has PubMed Central identifier	PMC2259420
has PubMed identifier	18315850
schema:publication	BMC Bioinformatics
resource representing a document's body	covid:d77dcb77a4a620fd1de81f309bff0e04e2578272#body_text
is schema:about of	named entity 'HOTSPOT' named entity 'hotspots' named entity 'selection' named entity 'hotspots' named entity 'PROTEOMES' named entity 'IMMUNOLOGICAL' named entity 'CANDIDATE' named entity 'SCREENING' named entity 'SELECTION' named entity 'TOOLS' named entity 'BACKGROUND' named entity 'T-CELL' named entity 'TARGETS' named entity 'PATHOGEN' named entity 'REQUIRED' named entity 'INCLUDING' named entity 'AUTOMATED' named entity 'BIND' named entity 'VACCINES' named entity 'T-CELL ACTIVATION' named entity 'HUMAN POPULATION' named entity 'PROMISCUOUS' named entity 'EPITOPE' named entity 'COMPUTATIONAL' named entity 'STRAINS' named entity 'IMMUNOLOGICAL' named entity 'IMMUNOTHERAPIES' named entity 'SMALL' named entity 'ANTIGENS' named entity 'COMPUTATIONAL' named entity 'SCREENING' named entity 'PRESENCE OF' named entity 'ELICIT' named entity 'PROTEOMES' named entity 'GIVEN' named entity 'HUNTER' named entity 'LARGE' named entity 'DEVELOPMENT' named entity 'SYSTEM' named entity 'SELECTION' named entity 'PATHOGEN' named entity 'VARIANT' named entity 'SELECTING' named entity 'SIZE' named entity 'PROPORTION' named entity 'LARGE' named entity 'EPITOPES' named entity 'MAY BE' named entity 'NECESSARY' named entity 'MULTIPLE ALLELES' named entity 'HUMAN LEUKOCYTE ANTIGEN' named entity 'THESE' named entity 'SCALE' named entity 'CLUSTERS' named entity 'NUMBER OF' named entity 'RELEVANT' named entity 'OBSERVED' named entity 'BASED' named entity 'PRIME' named entity 'FUNCTIONS' named entity 'proportion' named entity 'epitopes' named entity 'human leukocyte antigen (HLA)' named entity 'prime' named entity 'proteomes' named entity 'activation' named entity 'Given' named entity 'immunotherapies' named entity 'Hotspot' named entity 'computational' named entity 'proteomes'

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