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Toward Biologically Realistic Computational Membrane Protein Structure Prediction and Design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Toward Biologically Realistic Computational Membrane Protein Structure Prediction and Design./
作者:	Alford, Rebecca F.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	263 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-10, Section: B.
Contained By:	Dissertations Abstracts International82-10B.
標題:	Chemical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28378638
ISBN:	9798569912551

Toward Biologically Realistic Computational Membrane Protein Structure Prediction and Design.
Alford, Rebecca F.

Toward Biologically Realistic Computational Membrane Protein Structure Prediction and Design. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 263 p.

Source: Dissertations Abstracts International, Volume: 82-10, Section: B.

Thesis (Ph.D.)--The Johns Hopkins University, 2020.

This item must not be sold to any third party vendors.

Membrane proteins function as gates and checkpoints that control the transit of molecules and information across the lipid bilayer. Understanding their structures will provide mechanistic insights in how to keep cells healthy and defend against disease. However, experimental difficulties have slowed the progress of structure determination. Previous work has demonstrated the promise of computational modeling for elucidating membrane protein structures. A remaining challenge is to model proteins coupled with the heterogeneous cell membrane environment. In the first half of this dissertation, I detail the development, testing and integration of a biologically realistic implicit lipid bilayer model in Rosetta. First, I describe the initial iteration of the implicit model that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. Second, I explain my approach to energy function benchmarking and optimization given the challenge of sparse and low-quality experimental data. Third, I outline the second generation that incorporates a new electrostatics and pH model. All of these developments have advanced the accuracy of Rosetta membrane protein structure prediction and design. In the second half of this dissertation, I investigate three challenging biological and engineering applications involving membrane proteins. In the first application, I examine mutation-induced stability changes in the integral membrane zinc metalloprotease ZMPSTE24: a protein with a large voluminous chamber that is not captured by current implicit models. In the second application, I model interactions between the SERCA2a calcium pump and the regulatory transmembrane protein phospholamban: a key membrane protein-protein interaction implicated in the heart's response to adrenaline. Finally, I explore the challenge of membrane protein design to engineer a self-assembling transmembrane protein pore for nanotechnology applications. These applications highlight the next steps required to improve computational membrane protein modeling tools. Taken together, my work in both methods development and applications has advanced our understanding and ability to model and design membrane protein structures.

ISBN: 9798569912551Subjects--Topical Terms:

560457
Chemical engineering.
Subjects--Index Terms:

Membrane proteins

Toward Biologically Realistic Computational Membrane Protein Structure Prediction and Design.
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500 $a Source: Dissertations Abstracts International, Volume: 82-10, Section: B.
500 $a Advisor: Gray, Jeffrey J.
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506 $a This item must not be sold to any third party vendors.
520 $a Membrane proteins function as gates and checkpoints that control the transit of molecules and information across the lipid bilayer. Understanding their structures will provide mechanistic insights in how to keep cells healthy and defend against disease. However, experimental difficulties have slowed the progress of structure determination. Previous work has demonstrated the promise of computational modeling for elucidating membrane protein structures. A remaining challenge is to model proteins coupled with the heterogeneous cell membrane environment. In the first half of this dissertation, I detail the development, testing and integration of a biologically realistic implicit lipid bilayer model in Rosetta. First, I describe the initial iteration of the implicit model that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. Second, I explain my approach to energy function benchmarking and optimization given the challenge of sparse and low-quality experimental data. Third, I outline the second generation that incorporates a new electrostatics and pH model. All of these developments have advanced the accuracy of Rosetta membrane protein structure prediction and design. In the second half of this dissertation, I investigate three challenging biological and engineering applications involving membrane proteins. In the first application, I examine mutation-induced stability changes in the integral membrane zinc metalloprotease ZMPSTE24: a protein with a large voluminous chamber that is not captured by current implicit models. In the second application, I model interactions between the SERCA2a calcium pump and the regulatory transmembrane protein phospholamban: a key membrane protein-protein interaction implicated in the heart's response to adrenaline. Finally, I explore the challenge of membrane protein design to engineer a self-assembling transmembrane protein pore for nanotechnology applications. These applications highlight the next steps required to improve computational membrane protein modeling tools. Taken together, my work in both methods development and applications has advanced our understanding and ability to model and design membrane protein structures.
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653 $a Design
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653 $a Structural biology
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