UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Dynamic modelling of the processing of peptides for presentation on major histocompatibility complex class I proteins

Parshotam, LE; (2017) Dynamic modelling of the processing of peptides for presentation on major histocompatibility complex class I proteins. Doctoral thesis , UCL (University College London). Green open access

[thumbnail of LP_thesis_approved.pdf]
Preview
Text
LP_thesis_approved.pdf - Accepted Version

Download (10MB) | Preview

Abstract

Antigen presentation is broadly implicated in disease and represents an important target for prophylactic and therapeutic treatments. A better understanding of the components of this system is fundamental to our understanding of disease path- ways and to treatment design. This thesis focuses on modelling the processing of peptides by enzymes in the cytosol and in the endoplasmic reticulum (ER) in the context of major histocompatibility complex class I (MHC) antigen presentation, and expounds upon current knowledge of the mechanistic details and specificity of both the proteasome and the endoplasmic reticulum aminopeptidase-1 (ERAP1). We use nonlinear ordinary differential equations to model the biochemical reaction pathways of amino-terminal peptide trimming by ERAP1 and distinguish parameter dependencies of two prevailing theories for the mechanism of ERAP1 trimming us- ing algebraic and numerical analysis. Importantly, we show that ERAP1 has a role in peptide optimisation when MHC acts as a template, but not when it trims free peptide using an internal molecular ruler. We present testable hypotheses that may elucidate the dominant trimming mechanism used by ERAP1 in vivo, which has been the subject of debate for more than 25 years. We show that all ERAP1 trimming mechanism hypotheses are able to predict the qualitative distribution of cell surface presentation of SIINFEKL derived from amino-terminally extended precursors. Notably, we find that the molecular ruler trimming mechanism is more robust than the MHC-as-template mechanism. Finally, we use neural networks to predict carboxyl-terminal cleavage by the proteasome, and demonstrate that we are able to distinguish between cleavage and non-cleavage sites on an unseen set of known peptide epitopes. Overall, this thesis contributes a more thorough quantitative and mechanistic understanding of the generation of peptides presented on MHC class I molecules.

Type: Thesis (Doctoral)
Title: Dynamic modelling of the processing of peptides for presentation on major histocompatibility complex class I proteins
Event: UCL
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Content from Chapters 2 and 3 is being adapted for a publication
Keywords: Antigen presentation, machine learning, neural networks, ODEs, chemical kinetic pathway models, proteasome, ERAP1, parameter optimisation
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1559176
Downloads since deposit
228Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item