Kavraki, Lydia E.2018-12-032018-12-032008Shehu, Amarda. "Molecules in motion: Computing structural flexibility." (2008) Diss., Rice University. <a href="https://hdl.handle.net/1911/103599">https://hdl.handle.net/1911/103599</a>.https://hdl.handle.net/1911/103599Growing databases of protein sequences in the post-genomic era call for computational methods to extract structure and function from a protein sequence. In flexible molecules like proteins, function cannot be reliably extracted from a few structures. The amino-acid chain assumes various spatial arrangements (conformations) to modulate biological function. Characterizing the flexibility of a protein under physiological (native) conditions remains an open problem in computational biology. This thesis addresses the problem of characterizing the native flexibility of a protein by computing conformations populated under native conditions. Such computation involves locating free-energy minima in a high-dimensional conformational space. The methods proposed in this thesis search for native conformations using systematically less information from experiment: first employing an experimental structure, then using only a closure constraint in cyclic cysteine-rich peptides, and finally employing only the amino-acid sequence of small- to medium-size proteins. A novel method is proposed to compute structural fluctuations of a protein around an experimental structure. The method combines a robotics-inspired exploration of the conformational space with a statistical mechanics formulation. Thermodynamic quantities measured over generated conformations reproduce experimental data of broad time scales on small (∼ 100 amino acids) proteins with non-concerted motions. Capturing concerted motions motivates the development of the next methods. A second method is proposed that employs a closure constraint to generate native conformations of cyclic cysteine-rich peptides. The method first explores the entire conformational space, then explores in present energy minima until no lower-energy minima emerge. The method captures relevant features of the native state also observed in experiment for 20–30 amino-acid long peptides. A final method is proposed that implements a similar exploration but for longer proteins and employing only amino-acid sequence. In its first stage, the method explores the entire conformational space at a coarse-grained level of detail. A second stage focuses the exploration to low-energy regions in more detail. All-atom conformational ensembles are obtained for proteins that populate various functional states through large-scale concerted motions. These ensembles capture well the populated functional states of proteins up to 214 amino-acids long.239 ppengCopyright 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.BioinformaticsBiophysicsComputer scienceApplied sciencesBiological sciencesEquilibrium ensembleMultiscale explorationNative stateProtein conformationsRobotics-inspiredStatistical mechanicsThesis304510187THESIS COMP.SCI. 2009 SHEHU