Advancing Techniques of Structural Mass Spectrometry for Integrative Structural Modelling
dc.contributor.advisor | Schriemer, David C. | |
dc.contributor.author | Ziemianowicz, Daniel S. | |
dc.contributor.committeemember | Goodarzi, Aaron A. | |
dc.contributor.committeemember | MacCallum, Justin L. | |
dc.contributor.committeemember | Fraser, Marie Elizabeth | |
dc.date | 2020-11 | |
dc.date.accessioned | 2020-04-22T15:11:37Z | |
dc.date.available | 2020-04-22T15:11:37Z | |
dc.date.issued | 2020-04-20 | |
dc.description.abstract | Proteins are the fundamental functional units underlying all cellular activities. Protein function emerges from structure. To understand cellular activity and the diseases that arise from protein dysfunction we require knowledge of protein structure and structural dynamics. The toolbox offered by mass spectrometry (MS) allows a wide range of perspectives on protein structure, enabled by the application of chemical reagents that can encode structural properties. Improvements in the performance of labelling chemistries in turn can enhance the data returned and the structural models that are ultimately produced. Photogenerated carbenes are one such high-performance chemistry that offer unbiased sampling of protein structure at timescales relevant to protein dynamics. On the other hand, no single method can offer the breadth of data necessary to produce a comprehensive model of protein structure and dynamics—protein systems span broad spatial and temporal scales that exceed the scope of any single technique. To resolve large and complex protein systems, the integration of multiple data sets from orthogonal techniques is necessary. Here, I evaluate and advance structural MS methods with the goal of improving the accuracy and precision of structural models produced by MS-driven integrative structural modelling. Of particular interest is the application of carbene-based crosslinking and covalent labelling reagents which are shown to produce data with greater sequence coverage and improved accuracy in representing the equilibrated conformational state. Novel analytical software routines are developed to overcome the complications that arise from the labelling of proteins with a non-specific chemistry such as ambiguity in localizing modifications. Structural models are produced with integrative modelling workflows, including the development of a novel modelling restraint based on crosslinking and hydrogen/deuterium exchange data. MS-driven integrative modelling is demonstrated on multiple systems, including large complexes and systems with substantial disorder. | en_US |
dc.identifier.citation | Ziemianowicz, D. S. (2020). Advancing Techniques of Structural Mass Spectrometry for Integrative Structural Modelling (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | en_US |
dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/37709 | |
dc.identifier.uri | http://hdl.handle.net/1880/111844 | |
dc.language.iso | eng | en_US |
dc.publisher.faculty | Cumming School of Medicine | en_US |
dc.publisher.institution | University of Calgary | en |
dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | en_US |
dc.subject | structural biology | en_US |
dc.subject | mass spectrometry | en_US |
dc.subject | integrative modelling | en_US |
dc.subject | analytical chemistry | en_US |
dc.subject.classification | Biology--Molecular | en_US |
dc.subject.classification | Biochemistry | en_US |
dc.title | Advancing Techniques of Structural Mass Spectrometry for Integrative Structural Modelling | en_US |
dc.type | doctoral thesis | en_US |
thesis.degree.discipline | Medicine – Biochemistry and Molecular Biology | en_US |
thesis.degree.grantor | University of Calgary | en_US |
thesis.degree.name | Doctor of Philosophy (PhD) | en_US |
ucalgary.item.requestcopy | true | en_US |
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