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dc.rights.licenseRestricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.
dc.contributorGarcía, Angel E.
dc.contributorGiedt, Joel
dc.contributorMeunier, Vincent
dc.contributorGarde, Shekhar
dc.contributorMakhatadze, George I.
dc.contributor.authorJiménez Cruz, Camilo Andrés
dc.date.accessioned2021-11-03T08:05:04Z
dc.date.available2021-11-03T08:05:04Z
dc.date.created2014-01-17T14:39:32Z
dc.date.issued2013-08
dc.identifier.urihttps://hdl.handle.net/20.500.13015/981
dc.descriptionAugust 2013
dc.descriptionSchool of Science
dc.description.abstractProteins undergo fluctuations spanning a wide range of timescales. Atom oscillations and bond vibration happen in femtoseconds, while the timescales of non-local contacts and domain rearrangements range from miliseconds to seconds to occur. As a result of this hierarchy of processes, protein folding is a rare event, and thus, the dwelling times in local metastable states are much longer than the transition times between such states. Since the function of proteins is determined by their atomic motions, a detailed understanding of protein folding can result in significant advances in biology and medicine. Molecular Dynamics (MD) simulations of biomolecular systems, based on physical models of the interactions, provide atomic-level description of these processes. While MD directly samples temporal and spatial resolutions not available to experiments, it presents new challenges in the generation, validation and analysis of datasets. In this thesis, we focus on the characterization of folding/unfolding equilibrium and kinetic properties of a beta hairpin and globular mini protein. We use extensive all-atom, explicit solvent, Replica Exchange Molecular Dynamics (REMD) simulations, to generate the equilibrium ensemble of configurations of the systems studied and selected mutants. Our results high- light the importance of non-native interactions in the relative stability of the folded state. Kinetic networks for the systems were generated by constructing Markov State Models (MSMs), using thousands of independent MD simulations. We provide new approaches to solve some of the challenges of building MSMs. Specifically, we develop novel strategies for the discretization of the configurational space, and apply them to the model systems.
dc.language.isoENG
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectPhysics
dc.titleDetermination of thermodynamic and kinetic properties of proteins from atomistic computer simulations
dc.typeElectronic thesis
dc.typeThesis
dc.digitool.pid170141
dc.digitool.pid170142
dc.digitool.pid170143
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
dc.description.degreePhD
dc.relation.departmentDept. of Physics, Applied Physics, and Astronomy


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