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Methods and applications in computational protein design

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dc.contributor.advisor Bruce Tidor. en_US
dc.contributor.author Biddle, Jason Charles en_US
dc.contributor.other Massachusetts Institute of Technology. Computation for Design and Optimization Program. en_US
dc.date.accessioned 2011-03-24T18:53:01Z
dc.date.available 2011-03-24T18:53:01Z
dc.date.copyright 2010 en_US
dc.date.issued 2010 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/61792
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010. en_US
dc.description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. en_US
dc.description Cataloged from student-submitted PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 107-111). en_US
dc.description.abstract In this thesis, we summarize our work on applications and methods for computational protein design. First, we apply computational protein design to address the problem of degradation in stored proteins. Specifically, we target cysteine, asparagine, glutamine, and methionine amino acid residues to reduce or eliminate a protein's susceptibility to degradation via aggregation, deamidation, and oxidation. We demonstrate this technique on a subset of degradation-prone amino acids in phosphotriesterase, an enzyme that hydrolyzes toxic organophosphates including pesticides and chemical warfare agents. Second, we introduce BroMAP/A*, an exhaustive branch-and- bound search technique with enumeration. We compare performance of BroMAP/A* to DEE/A*, the current standard for conformational search with enumeration in the protein design community. When limited computational resources are available, DEE/A* sometimes fails to find the global minimum energy conformation and/or enumerate the lowest-energy conformations for large designs. Given the same computational resources, we show how BroMAP/A* is able to solve large designs by efficiently dividing the search space into small, solvable subproblems. en_US
dc.description.statementofresponsibility by Jason Charles Biddle. en_US
dc.format.extent 111 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Computation for Design and Optimization Program. en_US
dc.title Methods and applications in computational protein design en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Computation for Design and Optimization Program. en_US
dc.identifier.oclc 706802883 en_US


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