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

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Outline

Background & Motivations

System – Hotspot Hunter

Discussion

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HLA

http://immuneweb.xxmc.edu.cn/Lymphoid%20System.files/UntiPCT8.jpeg

Peptide TCR

Identification of T-cell epitopes for the study of vaccines and immunotherapies

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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

P1P2P3P4

Promiscuous epitopes

One supertype

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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

C prM E NS1 NS2a NS2b NS3 NS4a NS4b NS5

DENV

100-900aa

>9000

C prM E NS1 NS2a NS2b NS3 NS4a NS4b NS5

DENV

100-900aa

>9000

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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

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Outline

Background & Motivations

System – Hotspot Hunter

Discussion

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http://antigen.i2r.a-star.edu.sg/hh/

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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

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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

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FPFN

Hotspot Hunter can reliably identify real hotspots

30-51 95-108 118-173

30-47 130-147

Hotspot Hunter predictions

Experimental verified

HLA-DR supertype specific hotspots for HCV Core protein sequence

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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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1515Khan et al. (2006) BMC Bioinformatics

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Outline

Background & Motivations

System – Hotspot Hunter

Discussion

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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

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Our system can be customized and integrated into specialized databases

Tumor Antigen Database: http://research.i2r.a-star.edu.sg/Templar/DB/cancer_antigen/

CandiVF - Candida albicans Virulence Factor DatabaseTongchusak et al., (2005) Int J Pep Res Ther.

Application of Hotspot Hunter

2020

Funding Agency

NIH, USA

Acknowledgment

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Human pappilomavirus type 16 proteins E6 (Kast et al., 1994)

E6 hot-spot regionsHLA-A2 E6 7-34 (7-15, 18-26, and 26-34)HLA-A2 E6 52-60 (single peptide)

HLA-A3 E6 33-67 (33-41, 42-50, and 59-67) E6 75-101 (75-83, 89-97, and 93-101)

E6 125-151 (125-133 and 143-151)

Validation using experimental binders

E6HLA-A2

HLA-A3

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