Development of accurate and efficient models for biological molecules

dc.contributor.advisorRen, Pengyu
dc.creatorWu, Johnny Chungen
dc.date.accessioned2013-07-08T19:26:27Zen
dc.date.accessioned2017-05-11T22:33:10Z
dc.date.available2017-05-11T22:33:10Z
dc.date.issued2011-12en
dc.date.submittedDecember 2011en
dc.date.updated2013-07-08T19:26:27Zen
dc.descriptiontexten
dc.description.abstractThe abnormal expression or function of biological molecules, such as nucleic acids, proteins, or other small organic molecules, lead to the majority of diseases. Consequently, understanding the structure and function of these molecules through modeling can provide insight and perhaps suggest treatment for diseases. However, biologically relevant molecular phenomenon can vary vastly in the nature of their interactions and different classes of models are required to accommodate for this diversity. The objective of this thesis is to develop models for small molecules, amino acid peptides, and nucleic acids. A physical polarizable molecular mechanics model is described to accurately represent small molecules and single atom ions and applied to predict experimentally measurable thermodynamic properties such as hydration and binding free energies. A novel physical coarse-grain model based on Gay-Berne potentials and electrostatic multipoles has been developed for short peptides. The fraction of residues that adopt the alpha-helix conformation agrees with all-atom molecule dynamics results. Finally, a statistically-derived model based on sequence comparative sequence alignments is developed and applied to improve folding accuracy of RNA molecules.en
dc.description.departmentBiomedical Engineeringen
dc.embargo.lift12/1/2012en
dc.embargo.terms12/1/2012en
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2011-12-4783en
dc.identifier.urihttp://hdl.handle.net/2152/20671en
dc.language.isoen_USen
dc.subjectComputational chemistryen
dc.subjectBiophysicsen
dc.subjectMolecular modelingen
dc.titleDevelopment of accurate and efficient models for biological moleculesen

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