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Bruce Tidor. Biddle, Jason Charles Massachusetts Institute of Technology. Computation for Design and Optimization Program. Massachusetts Institute of Technology. Computation for Design and Optimization Program 2011-03-24T18:53:01Z 2011-03-24T18:53:01Z 2010 2010 http://hdl.handle.net/1721.1/61792 706802883 Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (p. 107-111). 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. by Jason Charles Biddle. S.M. 111 p. eng Massachusetts Institute of Technology 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 Computation for Design and Optimization Program. Methods and applications in computational protein design Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="6bbc0548-ae2a-45a9-9380-355239e178c9"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Methods and applications in computational protein design</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2010</PublicationDate> <Authors> <Author> <DisplayName>Biddle, Jason Charles</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Computation for Design and Optimization Program.</Keyword> <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&apos;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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>