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Local Minima Hopping along the Protein Energy Surface

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dc.contributor.advisor Shehu, Amarda
dc.contributor.author Olson, Brian
dc.creator Olson, Brian
dc.date 2011-12-02
dc.date.accessioned 2012-01-26T15:54:34Z
dc.date.available NO_RESTRICTION en_US
dc.date.available 2012-01-26T15:54:34Z
dc.date.issued 2012-01-26
dc.identifier.uri https://hdl.handle.net/1920/7479
dc.description.abstract Modeling of protein molecules in silico for the purpose of elucidating the three-dimensional structure where the protein is biologically active employs the knowledge that the protein conformational space has an underlying funnel-like energy surface. The biologically-active structure, also referred to as the native structure, resides at the basin or global minimum of the energy surface. A common approach among computational methods that seek the protein native structure is to search for local minima in the energy surface, with the hope that one of the local minima corresponds to the global minimum. Typical stochastic search methods, however, fail to explicitly sample local minima. This thesis proposes a novel algorithm to directly sample local minima at a coarse-grained level of detail. The Protein Local Optima Walk (PLOW) algorithm combines a memetic approach from evolutionary computation with cutting-edge structure prediction protocols in computational biophysics. PLOW explores the space of local minima by explicitly projecting each move at the global level to a nearby local minimum. This allows PLOW to jump over local energy barriers and more effectively sample near-native conformations. An additional contribution of this thesis is that the memetic approach in PLOW is applied to FeLTr, a tree-based search framework which ensures geometric diversity of computed conformations through projections of the conformational space. Analysis across a broad range of proteins shows that PLOW and memetic FeLTr outperform the original FeLTr framework and compare favorably against state-of-the-art ab-initio structure prediction algorithms.
dc.language.iso en_US en_US
dc.subject Native Structure en_US
dc.subject Near-Native Conformations en_US
dc.subject Local Minimum en_US
dc.subject Iterated Local Search en_US
dc.subject Fragment-Based Assembly en_US
dc.title Local Minima Hopping along the Protein Energy Surface en_US
dc.type Thesis en
thesis.degree.name Masters in Computer Science en_US
thesis.degree.level Master's en
thesis.degree.discipline Computer Science en
thesis.degree.grantor George Mason University en


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