Optimization of predictive energy landscapes for membrane and globular protein structure prediction

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dc.contributor.advisorWolynes, Peter G.en_US
dc.contributor.committeeMemberOnuchic, José Nen_US
dc.contributor.committeeMemberClementi, Ceciliaen_US
dc.creatorKim, Bobby Leeen_US
dc.date.accessioned2016-02-03T21:37:51Zen_US
dc.date.available2016-02-03T21:37:51Zen_US
dc.date.created2015-12en_US
dc.date.issued2015-10-09en_US
dc.date.submittedDecember 2015en_US
dc.date.updated2016-02-03T21:37:51Zen_US
dc.description.abstractThis thesis discusses recent results using the Associative-memory, Water-mediated, Structure and Energy Model (AWSEM), an optimized, coarse-grained molecular dynamics model. AWSEM and its membrane protein extension, AWSEM-membrane, are capable of de novo protein structure prediction and through the use of statistical estimators, allow construction of free energy landscapes which can provide insight about the dynamics of protein systems. We review the origins of energy landscape theory and how one can learn energy functions using the results of spin glass-inspired statistical mechanics models. We explore the similarities and differences between the energy landscapes of proteins that have been selected by nature and those of some proteins designed by humans. We also study how robust the folding of these designs would be to the simplification of the sequences using fewer amino acid types. Using an optimized extension of AWSEM, AWSEM-membrane, we explore the hypothesis that the folding landscapes of membrane proteins are funneled once the proteins’ topology within the membrane is established. We also show that the AWSEM-membrane force field is able to sample near native binding interfaces of several oligomeric systems.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationKim, Bobby Lee. "Optimization of predictive energy landscapes for membrane and globular protein structure prediction." (2015) Diss., Rice University. <a href="https://hdl.handle.net/1911/88336">https://hdl.handle.net/1911/88336</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/88336en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectprotein foldingen_US
dc.subjectprotein structure predictionen_US
dc.subjectenergy landscape theoryen_US
dc.subjectmolecular dynamicsen_US
dc.titleOptimization of predictive energy landscapes for membrane and globular protein structure predictionen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentChemistryen_US
thesis.degree.disciplineNatural Sciencesen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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