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University of Illinois at Urbana-Champaign

Automated protein NMR data analysis and its application to a-synuclein fibrils

Abstract

dc:description

In principle, nuclear magnetic resonance (NMR) spectroscopy provides structural and conformational information with sub-Angstrom precision and the ability to measure dynamics with timescales ranging from femtoseconds to years, all with atomic specificity. However, due to the relatively low sensitivity of NMR, fundamental limits on spectral resolution, and the complexity of the quantum mechanical phenomena NMR exploits, that wealth of information often remains out of reach. The highly varied presentation of molecular information in NMR spectra and the difficulty of numerical simulation of non-trivial systems has lead the majority of data analysis to be performed by trained experts, and because of its time-intensive nature, that analysis is rarely replicated by a third party or validated in an objective manner. In this dissertation I report my efforts to automate NMR data analysis in an objective and replicable manner and to provide tools for validation of resulting three-dimensional structures by direct comparison to raw spectral data. The first method, COMPASS, attempts to extract as much information as possible from a single 13C-13C two-dimensional spectrum for the determination of protein structure and successfully identified the true structure of 15 test proteins. The second method, GPS, predicts features of data that would be expected given a set of chemical shift assignments and possibly a three-dimensional structure and uses the presence or absence of those features in experimental spectra to refine or validate a given structure. I then report my application of these computational methods to the problems of refining an a-synuclein fibril structure with proton-detected NMR data, the analysis and characterization of a pair of interrelated a-synuclein fibril strains with distinct pathological properties, and to the general question of fibril polymorphism, a phenomenon that presents a substantial challenge to forming consistent conclusions about fibril properties and interactions across samples and research groups.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Chemistry
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Courtney, Joseph M
Contributors dc:contributor
  • Rienstra, Chad M.
  • Gruebele, Martin
  • Hammes-Schiffer, Sharon
  • Oldfield, Eric

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • Copyright 2017 Joseph Courtney
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/97595
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/97595

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Courtney, Joseph M. Automated protein NMR data analysis and its application to a-synuclein fibrils. Dissertation thesis, University of Illinois at Urbana-Champaign, 2017. http://hdl.handle.net/2142/97595