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dc.contributor.advisorCollin M. Stultz.en_US
dc.contributor.authorGurry, Thomasen_US
dc.contributor.otherMassachusetts Institute of Technology. Computational and Systems Biology Program.en_US
dc.date.accessioned2015-06-10T19:12:13Z
dc.date.available2015-06-10T19:12:13Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/97347
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2015.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 114-124).en_US
dc.description.abstractProtein aggregation underlies a number of human diseases. Most notably, it occurs widely in neurodegenerative diseases, including Alzheimer's and Parkinson's. At the molecular level, neurotoxicity is thought to originate from toxic gains of function in multimeric aggregates of proteins that are otherwise predominantly monomeric and disordered, fluctuating between a very large number of structurally dissimilar states on nano- and microsecond timescales. These proteins, termed Intrinsically Disordered Proteins (IDPs), are notoriously difficult to probe using traditional biophysical techniques. In order to obtain structural information pertaining to the aggregation of IDPs, it is often necessary to develop computational and modeling tools, both to leverage the full extent of the experimental data, and to generate testable predictions for future experiments. In this thesis, I present three separate computational studies studying the formation of multimeric aggregates in IDPs, spanning different aspects of the aggregation process, from early nucleation events to fibril elongation. In the first study, I present a conformational ensemble of a-synuclein, the culprit protein of Parkinson's disease, constructed using a Variational Bayesian Weighting algorithm in combination with NMR data collected by our collaborators. We find that the data fit a description in which the protein predominantly exists as a disordered monomer but contains small quantities of multimeric states containing both helical and strand-rich conformations. In the second study, I focus on the process of amyloid fibril elongation in the Amyloid-[beta] (A[beta]) peptide of Alzheimer's disease. I compute the free energy surface associated with the fibril elongation reaction, and find that elongation of both A[beta]40 and A[beta]42 experimental fibril structures occurs on a downhill free energy pathway, proceeding via an obligate, fibril-associated hairpin intermediate. The fibril-associated hairpin is significantly more stable (relative to the fibrillar, elongated state) in A[beta]42 compared with A[beta]40, suggesting a potential clinical target of interest. Finally, I present lengthy, all-atom molecular simulations that suggest that nucleation of the minimum aggregating fragment of c-synuclein proceeds via a helical intermediate, requiring a structural conversion into a strand-rich nucleating species via a stochastic process of individual helices unfolding and self-associating via backbone hydrogen bonds.en_US
dc.description.statementofresponsibilityby Thomas Gurry.en_US
dc.format.extent124 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectComputational and Systems Biology Program.en_US
dc.titleOrder, disorder, and protein aggregationen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Program
dc.identifier.oclc910560473en_US


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