Hotspot Hunter

A computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes

Guang Lan Zhang, Asif M. Khan, Kellathur N Srinivasan, A. T. Heiny, K. X. Lee, Chee Keong Kwoh, J. Thomas August, Vladimir Brusic

Research output: Contribution to conferencePaper

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 http://antigen.i2r.a-star.edu.sg/hh/. It is a new generation computational tool aiding in epitope-based vaccine design.

Original languageEnglish
DOIs
Publication statusPublished - Dec 1 2007
Externally publishedYes
Event6th International Conference on Bioinformatics, InCoB 2007 - Hong Kong, Hong Kong
Duration: Dec 27 2007Dec 30 2007

Other

Other6th International Conference on Bioinformatics, InCoB 2007
CountryHong Kong
CityHong Kong
Period12/27/0712/30/07

Fingerprint

Pathogens
Proteome
proteome
Epitopes
epitopes
Screening
Vaccines
HLA Antigens
antigenic variation
Antigens
screening
Proteins
Antigenic Variation
T-Lymphocyte Epitopes
pathogens
T-cells
prediction
T-lymphocytes
vaccines
human population

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

Cite this

Zhang, G. L., Khan, A. M., N Srinivasan, K., Heiny, A. T., Lee, K. X., Kwoh, C. K., ... Brusic, V. (2007). Hotspot Hunter: A computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes. Paper presented at 6th International Conference on Bioinformatics, InCoB 2007, Hong Kong, Hong Kong. https://doi.org/10.1186/1471-2105-9-S1-S19

Hotspot Hunter : A computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes. / Zhang, Guang Lan; Khan, Asif M.; N Srinivasan, Kellathur; Heiny, A. T.; Lee, K. X.; Kwoh, Chee Keong; August, J. Thomas; Brusic, Vladimir.

2007. Paper presented at 6th International Conference on Bioinformatics, InCoB 2007, Hong Kong, Hong Kong.

Research output: Contribution to conferencePaper

Zhang, GL, Khan, AM, N Srinivasan, K, Heiny, AT, Lee, KX, Kwoh, CK, August, JT & Brusic, V 2007, 'Hotspot Hunter: A computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes' Paper presented at 6th International Conference on Bioinformatics, InCoB 2007, Hong Kong, Hong Kong, 12/27/07 - 12/30/07, . https://doi.org/10.1186/1471-2105-9-S1-S19
Zhang GL, Khan AM, N Srinivasan K, Heiny AT, Lee KX, Kwoh CK et al. Hotspot Hunter: A computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes. 2007. Paper presented at 6th International Conference on Bioinformatics, InCoB 2007, Hong Kong, Hong Kong. https://doi.org/10.1186/1471-2105-9-S1-S19
Zhang, Guang Lan ; Khan, Asif M. ; N Srinivasan, Kellathur ; Heiny, A. T. ; Lee, K. X. ; Kwoh, Chee Keong ; August, J. Thomas ; Brusic, Vladimir. / Hotspot Hunter : A computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes. Paper presented at 6th International Conference on Bioinformatics, InCoB 2007, Hong Kong, Hong Kong.
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