De novo protein structure prediction is a challenge due to the sheer size of the search space. One can limit the set of potential models with long-range contact restraints (positions distant in the primary sequence but known to be in close proximity within the tertiary structure). Most available contact prediction methods achieve accuracies insufficient for de novo protein folding. Direct Information (DI), which finds the minimal set of correlations that explains all global correlation, is a notable exception. DI has been used to determine the structures of some membrane and soluble proteins with large numbers of homologous sequences compiled into large sequence alignments. However, DI has many limitations.
I have leveraged machine learning methods to predict contacts more accurately by combining DI with sequence information thereby improving protein structure prediction accuracy in the Biochemical Library (BCL). The BCL is a C++ library developed in the Meiler lab. This innovative resource will augment the elucidation of traditionally challenging membrane protein structures specifically larger proteins, which are computationally difficult to address.
| Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-06062014-110802 |
| Date | 26 June 2014 |
| Creators | Teixeira, Pedro Luis, Jr. |
| Contributors | Terry P. Lybrand Ph.D., Thomas A. Lasko M.D., Ph.D., Jens Meiler Ph.D. |
| Publisher | VANDERBILT |
| Source Sets | Vanderbilt University Theses |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.vanderbilt.edu/available/etd-06062014-110802/ |
| Rights | restrictone, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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