Bunce, Samuel John (2018) Understanding the mechanism of peptide self-assembly. PhD thesis, University of Leeds.
Abstract
Understanding the molecular mechanism of peptide self-assembly is vital; both as a fundamental biological process but also to combat the pathological disease state known as amyloid. A wide range of techniques, including computer simulations and biophysical assays, will need to be employed to answer this question. The development of experimental techniques that can capture and isolate the fleeting states that occur during peptide self-assembly is thus essential in order to elucidate the underlying mechanism. In order to meet this need, Chapter 1 outlines key concepts that relate to peptide self-assembly by examining two key examples (diphenylalanine and the amyloid-β peptide). In Chapter 2, a combination of experiments (including photo-induced cross-linking and fluorescence quenching) and discontinuous molecular dynamics simulations were used to understand the self-assembly process of a small amyloid peptide, Aβ16-22, at the molecular level. In Chapter 3, both the experimental methods that have been developed and the understanding of the mechanism of Aβ16-22 self-assembly were extended to understand the mechanism by which Aβ16-22 interacts with, and influences the aggregation rate of, a related sequence, Aβ40. Together, the work presented here describes how it is possible to explore complex self-assembling systems, with temporal resolution, at the molecular level.
Metadata
Supervisors: | Wilson, Andy J. and Radford, Sheena E. and Ashcroft, Alison E. |
---|---|
Keywords: | amyloid, peptide self-assembly, photo cross-linking, diazirine, amyloid-beta |
Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Chemistry (Leeds) |
Identification Number/EthosID: | uk.bl.ethos.770058 |
Depositing User: | Mr Samuel John Bunce |
Date Deposited: | 13 Mar 2019 13:51 |
Last Modified: | 11 Apr 2022 09:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:23090 |
Download
Final eThesis - complete (pdf)
Filename: SJB_thesis_final.pdf
Licence:
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License
Export
Statistics
You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.