Novel bioinformatics tools for epitope-based peptide vaccine design

Whalley, Thomas 2022. Novel bioinformatics tools for epitope-based peptide vaccine design. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

BACKGROUND T-cells are essential in the mediation of immune responses, helping clear bacteria, viruses and cancerous cells. T-cells recognise anomalies in the cellular proteome associated with infection and neoplasms through the T-cell receptor (TCR). The most common TCRs in humans, αβ TCRs, engage processed peptide epitopes presented on the major histocompatibility complex (pMHC). TCR-pMHC interaction is critical to vaccination. In this thesis I will discuss three pieces of software and outcomes derived from them that contribute to epitope-based vaccine design. RESULTS Three pieces of software were developed to help scientists study and understand T-cell responses. The first, STACEI allows users to interrogate the TCR-pMHC crystal structures. The time consuming, error-prone analysis that previously would have to be ran manually, is replaced by a single, flexible package. The second development is the introduction of general-purpose computing on the GPU (GP-GPU) in aiding the prediction of T-cell epitopes by scanning protein datasets using data derived from combinatorial peptide libraries (CPLs). Finally, I introduce RECIPIENT, a reverse vaccinology tool (RV) that combines pangenomic and population genetics methods to predict good vaccine targets across multiple pathogen samples. CONCLUSION Across this thesis, I introduce three different methods that aid the study of T-cells that will hopefully improve future vaccine design. These methods range across data types and methodologies, with methods focusing on mechanistic understanding of the TCR-pMHC binding event; the application of GP-GPU to CPLs and using microbial genomics to aid the study and understanding of antigen-specific T-cell responses. These three methods have a significant potential for further integration, especially the structural methods.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Schools > Medicine
Date of First Compliant Deposit:	24 May 2022
Last Modified:	27 May 2022 14:03
URI:	https://orca.cardiff.ac.uk/id/eprint/149910

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