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Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes G.L. Zhang, A.M.

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Presentation on theme: "Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes G.L. Zhang, A.M."— Presentation transcript:

1 Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes G.L. Zhang, A.M. Khan, K.N. Srinivasan, A.T. Heiny, K.X. Lee, C.K. Kwoh, J.T. August and V. Brusic

2 2 Outline Background & Motivations System – Hotspot Hunter Discussion

3 3 HLA Peptide TCR Identification of T-cell epitopes for the study of vaccines and immunotherapies

4 4 T-cell epitope clusters (hotspots) for the development of epitope-based vaccines Promiscuous T-cell epitopes relevant to large proportion of the human population Presence of clusters of promiscuous T-cell epitopes (hotspots) in antigens H1 H4H3H2 P1 P2 P3 P4 Promiscuous epitopes One supertype

5 5 Mapping hotspots experimentally is a challenging task Large size of pathogen proteomes (sequence length versus sequence number) Low natural prevalence of T-cell epitopes (~1-5%) for a given HLA molecule High cost of peptide synthesis Limited access to human PBMC Time-consuming experimental assays HLA Peptide TCR

6 6 Limitations of existing promiscuous epitope prediction systems Single protein sequence per submission Do not predict for hotspots Impractical for large-scale systematic study of hotspots in large proteomes Existing prediction systems are not suitable for large-scale study of hotspots in pathogen proteomes

7 7 Outline Background & Motivations System – Hotspot Hunter Discussion

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9 9 Hotspot Hunter Screen and select of hotspots specific to four common HLA supertypes HLA class I A2, A3, B7  cover ~ 88% of human population HLA class II DR  cover ~100% of human population

10 10 Hotspot Hunter Implementation Predictive Engines  ANN and SVM methods Predictions results integrated using soft computing principles 10-fold cross-validation results showed that the system is of high accuracy

11 11 FP FN Hotspot Hunter can reliably identify real hotspots Hotspot Hunter predictions Experimental verified HLA-DR supertype specific hotspots for HCV Core protein sequence

12 12 Hotspot Hunter Functions Single sequence query Multiple sequence query Target selection Selection of common hotspot across more than one HLA supertype

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15 15 Khan et al. (2006) BMC Bioinformatics

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17 17 Outline Background & Motivations System – Hotspot Hunter Discussion

18 18 Allows prediction of immunological hotspots Combines the strengths of the ANN and SVM  robust prediction performance Multiple sequence query  suitable for large-scale study Provides a utility for selecting candidate hotspots and experimental targets Hotspot Hunter is a new generation computational tool aiding in epitope- based vaccine design

19 19 Our system can be customized and integrated into specialized databases Tumor Antigen Database: star.edu.sg/Templar/DB/cancer_antigen/ CandiVF - Candida albicans Virulence Factor Database Tongchusak et al., (2005) Int J Pep Res Ther. Application of Hotspot Hunter

20 20 Funding Agency NIH, USA Acknowledgment

21 21 Human pappilomavirus type 16 proteins E6 (Kast et al., 1994) E6 hot-spot regions HLA-A2 E (7-15, 18-26, and 26-34) HLA-A2 E (single peptide) HLA-A3 E (33-41, 42-50, and 59-67) E (75-83, 89-97, and ) E ( and ) Validation using experimental binders E6 HLA-A2 HLA-A3

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