Dissertation
The effects of macromolecular crowding and system volume on protein aggregation
Doctor of Philosophy (Ph.D.), Drexel University
Sep 2020
DOI:
https://doi.org/10.17918/00000269
Abstract
Proteins in living cells perform an enormous variety of processes, among these is protein self-assembly or aggregation. While many proteins self-assemble as part of healthy biological function, malfunctioning proteins which pathologically self-assemble have been linked to numerous neurodegenerative diseases like Huntington's, Parkinson's, and Alzheimer's. We investigate the role of macromolecular crowders and system volume in the process of protein self-assembly. We present three major studies in this thesis: two on the role of macromolecular crowders in the self-assembly of actin and amyloid proteins using differential rate equations, and one utilizing a stochastic approach to study the effects of system volume and particle number on protein aggregation, as well as how crowders can change the microscopic details of reaction dynamics. We develop a model for the inclusion of crowding effects in kinetic rate constants and show remarkable fits to existing data for actin and nine amyloid-forming proteins in the presence of macromolecular crowders. We also show how fluctuations and overall dynamics change with system size and in the presence of crowders, and develop a stochastic method for determining the prevalence of individual reaction mechanisms and how they evolve over time. This reaction frequency method provides unique insight into the dynamics of the system and can be used to explain why certain aggregating systems behave as they do, and why their behavior changes in various conditions. Stochastic approaches, such as Gillespie's algorithm, may be necessary for studying the behavior of proteins in cells, as volumes of micelles and cellular compartments can be as small as 1pL, thus fluctuations in particle number become relevant and continuous rate approaches become less accurate. We also present a tool for user-friendly simulation and visualization of stochastic models of protein aggregation.
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Details
- Title
- The effects of macromolecular crowding and system volume on protein aggregation
- Creators
- John Erik Bridstrup
- Contributors
- Jian-Min Yuan (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xiii, 85 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- College of Arts and Sciences; Physics; Drexel University
- Other Identifier
- 991014695147804721