Ensemble modeling of [beta]-sheet proteins
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/66458 |
| _version_ | 1811083470950105088 |
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| author | O'Donnell, Charles William |
| author2 | Srinivas Devadas, Bonnie Berger and Susan Lindquist. |
| author_facet | Srinivas Devadas, Bonnie Berger and Susan Lindquist. O'Donnell, Charles William |
| author_sort | O'Donnell, Charles William |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. |
| first_indexed | 2024-09-23T12:33:18Z |
| format | Thesis |
| id | mit-1721.1/66458 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:33:18Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/664582019-04-12T09:27:51Z Ensemble modeling of [beta]-sheet proteins O'Donnell, Charles William Srinivas Devadas, Bonnie Berger and Susan Lindquist. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. In title on title page, [beta] appears as lower case Greek letter. Cataloged from PDF version of thesis. Includes bibliographical references (p. 149-161). Our ability to characterize protein structure and dynamics is vastly outpaced by the speed of modern genetic sequencing, creating a growing divide between our knowledge of biological sequence and structure. Structural modeling algorithms offer the hope to bridge this gap through computational exploration of the sequence determinants of structure diversity. In this thesis, we introduce new algorithms that enable the efficient modeling of protein structure ensembles and their sequence variants. These statistical mechanics-based constructions enable the identification of all energetically likely sequence/structure states for a family of proteins. Beyond improved structure predictions, this approach enables a framework for thermodynamically-driven mutational and comparative analysis as well as the approximation of kinetic protein folding pathways. We have applied these techniques to two protein types that are notoriously difficult to characterize biochemically: transmembrane P-barrel proteins and amyloid fibrils. For these we advance the state-of-the-art in structure prediction, mutational analysis, and sequence alignment. Further, we have collaborated to apply these methods to open scientific questions about amyloid fibrils and bacterial biofilms. by Charles William O'Donnell. Ph.D. 2011-10-17T21:28:17Z 2011-10-17T21:28:17Z 2011 2011 Thesis http://hdl.handle.net/1721.1/66458 756041265 eng M.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. http://dspace.mit.edu/handle/1721.1/7582 161 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. O'Donnell, Charles William Ensemble modeling of [beta]-sheet proteins |
| title | Ensemble modeling of [beta]-sheet proteins |
| title_full | Ensemble modeling of [beta]-sheet proteins |
| title_fullStr | Ensemble modeling of [beta]-sheet proteins |
| title_full_unstemmed | Ensemble modeling of [beta]-sheet proteins |
| title_short | Ensemble modeling of [beta]-sheet proteins |
| title_sort | ensemble modeling of beta sheet proteins |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/66458 |
| work_keys_str_mv | AT odonnellcharleswilliam ensemblemodelingofbetasheetproteins |