{"id":{"repo_id":"rice","oai_identifier":"oai:repository.rice.edu:1911/103654"},"canonical_url":"https://search.dev.ndltd.org/etd/rice/oai:repository.rice.edu:1911/103654","repository":{"repo_id":"rice","name":"Rice University","base_url":"https://repository.rice.edu/server/oai/request"},"display":{"title":"Simulating, refining and modeling protein structures with multi-scale methods","abstract":"We have developed different computational methods for refining, modeling and simulating protein structures in multi-scale resolution. Combining with experimental information from different structural biological method such as Fiber Diffraction, cryo-Electron Microscopy (cryo-EM), Small Angle X-ray Scattering (SAXS) and X-ray Crystallography, we show that our methods can be employed to improve the study of protein structures. In detail, the atomic structure of actin filament was refined against fiber diffraction data by our long-range normal mode based refinement protocol, which for the first time demonstrate that, for any fiber diffraction data, a substantial amount of refinement error is due to the deformations of the filaments. A geometry-based loop motif filter was then constructed followed up with an energetic ensemble optimization, in order to detect higher resolution structural information from intermediate-resolution cryo-EM experimental data. The results also imply that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well. We further introduced a new Monte-Carlo simulation technique, which combines elastic network model and a Hamiltonian at a different scale to study the protein folding problem assisted by the small angle X-ray scattering (SAXS) profiles. It was shown that our approach was effective for deriving the topology of small, globular helical proteins or protein domains. Finally, a new knowledge-based potential that only requires the Ca positions as input was built, which is expected to adds a new tool for protein structural modeling.","abstract_html":"We have developed different computational methods for refining, modeling and simulating protein structures in multi-scale resolution. Combining with experimental information from different structural biological method such as Fiber Diffraction, cryo-Electron Microscopy (cryo-EM), Small Angle X-ray Scattering (SAXS) and X-ray Crystallography, we show that our methods can be employed to improve the study of protein structures. In detail, the atomic structure of actin filament was refined against fiber diffraction data by our long-range normal mode based refinement protocol, which for the first time demonstrate that, for any fiber diffraction data, a substantial amount of refinement error is due to the deformations of the filaments. A geometry-based loop motif filter was then constructed followed up with an energetic ensemble optimization, in order to detect higher resolution structural information from intermediate-resolution cryo-EM experimental data. The results also imply that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well. We further introduced a new Monte-Carlo simulation technique, which combines elastic network model and a Hamiltonian at a different scale to study the protein folding problem assisted by the small angle X-ray scattering (SAXS) profiles. It was shown that our approach was effective for deriving the topology of small, globular helical proteins or protein domains. Finally, a new knowledge-based potential that only requires the Ca positions as input was built, which is expected to adds a new tool for protein structural modeling.","abstract_has_math":false,"creators":["Wu, Yinghao"],"institution":"Rice University","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Ma, Jianpeng"],"committee_chairs":[],"committee_members":[],"year":2007,"date_issued":"2007","date_published":"2007","updated_at":"2026-07-24T04:10:15Z","subjects":["Bioinformatics","Biophysics","Biological sciences","Actin filament","Computational modeling","Molecular dynamics simulation","Multiscale methods Protein structure"],"languages":["eng"],"rights":["Copyright 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."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1911/103654","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Ma, Jianpeng"]},{"key":"dc:creator","label":"Author","values":["Wu, Yinghao"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-12-03T18:32:15Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-12-03T18:32:15Z"]},{"key":"dc:date.issued","label":"Date","values":["2007"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Rice University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Bioinformatics","Biophysics","Biological sciences","Actin filament","Computational modeling","Molecular dynamics simulation","Multiscale methods Protein structure"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 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."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1911/103654"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["We have developed different computational methods for refining, modeling and simulating protein structures in multi-scale resolution. Combining with experimental information from different structural biological method such as Fiber Diffraction, cryo-Electron Microscopy (cryo-EM), Small Angle X-ray Scattering (SAXS) and X-ray Crystallography, we show that our methods can be employed to improve the study of protein structures. In detail, the atomic structure of actin filament was refined against fiber diffraction data by our long-range normal mode based refinement protocol, which for the first time demonstrate that, for any fiber diffraction data, a substantial amount of refinement error is due to the deformations of the filaments. A geometry-based loop motif filter was then constructed followed up with an energetic ensemble optimization, in order to detect higher resolution structural information from intermediate-resolution cryo-EM experimental data. The results also imply that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well. We further introduced a new Monte-Carlo simulation technique, which combines elastic network model and a Hamiltonian at a different scale to study the protein folding problem assisted by the small angle X-ray scattering (SAXS) profiles. It was shown that our approach was effective for deriving the topology of small, globular helical proteins or protein domains. Finally, a new knowledge-based potential that only requires the Ca positions as input was built, which is expected to adds a new tool for protein structural modeling."]},{"key":"dc:title","label":"Title","values":["Simulating, refining and modeling protein structures with multi-scale methods"]}]}],"canonical_facts":{"dc:contributor.advisor":["Ma, Jianpeng"],"dc:creator":["Wu, Yinghao"],"dc:date.accessioned":["2018-12-03T18:32:15Z"],"dc:date.available":["2018-12-03T18:32:15Z"],"dc:date.issued":["2007"],"dc:description.abstract":["We have developed different computational methods for refining, modeling and simulating protein structures in multi-scale resolution. Combining with experimental information from different structural biological method such as Fiber Diffraction, cryo-Electron Microscopy (cryo-EM), Small Angle X-ray Scattering (SAXS) and X-ray Crystallography, we show that our methods can be employed to improve the study of protein structures. In detail, the atomic structure of actin filament was refined against fiber diffraction data by our long-range normal mode based refinement protocol, which for the first time demonstrate that, for any fiber diffraction data, a substantial amount of refinement error is due to the deformations of the filaments. A geometry-based loop motif filter was then constructed followed up with an energetic ensemble optimization, in order to detect higher resolution structural information from intermediate-resolution cryo-EM experimental data. The results also imply that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well. We further introduced a new Monte-Carlo simulation technique, which combines elastic network model and a Hamiltonian at a different scale to study the protein folding problem assisted by the small angle X-ray scattering (SAXS) profiles. It was shown that our approach was effective for deriving the topology of small, globular helical proteins or protein domains. Finally, a new knowledge-based potential that only requires the Ca positions as input was built, which is expected to adds a new tool for protein structural modeling."],"dc:identifier.uri":["https://hdl.handle.net/1911/103654"],"dc:language.iso":["eng"],"dc:rights":["Copyright 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."],"dc:subject":["Bioinformatics","Biophysics","Biological sciences","Actin filament","Computational modeling","Molecular dynamics simulation","Multiscale methods Protein structure"],"dc:title":["Simulating, refining and modeling protein structures with multi-scale methods"],"dc:type":["Thesis"],"thesis:degree_discipline":["Engineering"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["Rice University"]},"updated_at":"2026-07-24T04:10:15Z"}