+publisher:"University of Washington" +contributor:("Baker, David")

University of Washington

1. Vulovic, Ivan. Software Algorithms for Design of Symmetric Protein Complexes Applied to Cryo-Electron Microscopy Scaffolds and Antibody Nanoparticles.

Degree: PhD, 2020, University of Washington

URL: http://hdl.handle.net/1773/45809

► Innovation in the symmetric assembly and protein material design space has the potential to – eventually – reinvent medicine and nanotechnology. One leading strategy for… (more)

Subjects/Keywords: genetic fusion; protein design; Biochemistry; Molecular engineering

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APA (6^th Edition):

Vulovic, I. (2020). Software Algorithms for Design of Symmetric Protein Complexes Applied to Cryo-Electron Microscopy Scaffolds and Antibody Nanoparticles. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/45809

Chicago Manual of Style (16^th Edition):

Vulovic, Ivan. “Software Algorithms for Design of Symmetric Protein Complexes Applied to Cryo-Electron Microscopy Scaffolds and Antibody Nanoparticles.” 2020. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/45809.

MLA Handbook (7^th Edition):

Vulovic, Ivan. “Software Algorithms for Design of Symmetric Protein Complexes Applied to Cryo-Electron Microscopy Scaffolds and Antibody Nanoparticles.” 2020. Web. 20 Jan 2021.

Vancouver:

Vulovic I. Software Algorithms for Design of Symmetric Protein Complexes Applied to Cryo-Electron Microscopy Scaffolds and Antibody Nanoparticles. [Internet] [Doctoral dissertation]. University of Washington; 2020. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/45809.

Council of Science Editors:

Vulovic I. Software Algorithms for Design of Symmetric Protein Complexes Applied to Cryo-Electron Microscopy Scaffolds and Antibody Nanoparticles. [Doctoral Dissertation]. University of Washington; 2020. Available from: http://hdl.handle.net/1773/45809

University of Washington

2. Dou, Jiayi. Exploring the Molecular Design of Ligand Binding Sites by Computational Protein Design.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/39951

► Ligand binding sites in natural proteins, with diverse structural details, provide the foundation for enzymatic activity, antibody-antigen recognition, ligand-induced pathway activation and drug discovery in… (more)

Subjects/Keywords: computational protein design; de novo proteins; DFHBI; ligand binding proteins; small molecule binding; steroid; Biochemistry; Molecular biology; Biophysics; Bioengineering

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APA (6^th Edition):

Dou, J. (2017). Exploring the Molecular Design of Ligand Binding Sites by Computational Protein Design. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/39951

Chicago Manual of Style (16^th Edition):

Dou, Jiayi. “Exploring the Molecular Design of Ligand Binding Sites by Computational Protein Design.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/39951.

MLA Handbook (7^th Edition):

Dou, Jiayi. “Exploring the Molecular Design of Ligand Binding Sites by Computational Protein Design.” 2017. Web. 20 Jan 2021.

Vancouver:

Dou J. Exploring the Molecular Design of Ligand Binding Sites by Computational Protein Design. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/39951.

Council of Science Editors:

Dou J. Exploring the Molecular Design of Ligand Binding Sites by Computational Protein Design. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/39951

University of Washington

3. Lin, Yu-Ru. Insight from designing ideal αβ monomers and homo-oligomers.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/39956

► Previously, general principles relating secondary structure patterns to tertiary packing motifs enable design of different protein topologies stabilized by consistent local and non-local interactions. With… (more)

▼ Previously, general principles relating secondary structure patterns to tertiary packing motifs enable design of different protein topologies stabilized by consistent local and non-local interactions. With the goal to achieve fine control over protein shape and size within a particular topology, the first part of my thesis extended the design rules by systematically analyzing the co-dependencies between the lengths and packing geometry of successive secondary structure elements and the backbone torsion angles of the loop linking them. I then demonstrated the fine control by the applying the extended set of rules to design series of proteins with the same fold but considerable variation in secondary structure length, loop geometry, registry between β-strands and overall shape. Solution NMR structures of four designed proteins for two different folds showed that protein shape and size can be precisely controlled within a given protein fold. These extended design principles can provide the foundation for custom design of protein structures performing desired functions. The second part of my thesis focused on homo-oligomer design. Proteins in cells often form oligomers through non-covalent interaction to execute various biological properties. Natural oligomeric proteins involve scaffold support, enzymatic reactions, signaling transduction, etc. Moreover, the intrinsic protein flexibility often facilitates protein structural changes upon oligomerization. To understand how αβ- proteins interact to form oligomers and to enable future de novo protein applications in biomaterial or molecular machinery, the second part of my thesis investigated the design of cyclic homo-oligomers using de novo proteins as building blocks and experimented with introducing flexible backbone design strategies to oligomer design process. The results suggested that de novo proteins undergo structural change for oligomerization and for homo-oligomers formed from globular building blocks, pre-organized hydrogen bonds between amines and carbonyl groups of beta strands are more effective in achieving protein interaction and shape complementarity between subunits with higher specificity. Advisors/Committee Members: Baker, David (advisor).

Subjects/Keywords: De novo protein; Protein Design; Rosetta Design; Biochemistry; Molecular biology; Nanoscience; Biological chemistry

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APA (6^th Edition):

Lin, Y. (2017). Insight from designing ideal αβ monomers and homo-oligomers. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/39956

Chicago Manual of Style (16^th Edition):

Lin, Yu-Ru. “Insight from designing ideal αβ monomers and homo-oligomers.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/39956.

MLA Handbook (7^th Edition):

Lin, Yu-Ru. “Insight from designing ideal αβ monomers and homo-oligomers.” 2017. Web. 20 Jan 2021.

Vancouver:

Lin Y. Insight from designing ideal αβ monomers and homo-oligomers. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/39956.

Council of Science Editors:

Lin Y. Insight from designing ideal αβ monomers and homo-oligomers. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/39956

University of Washington

4. Dang, Luke Thomas. Computational Design and Optimization of Novel Subtype Specific Frizzled Binding Proteins for Modulation of Wnt Signaling.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/40260

► Wnt signaling is essential to a range of critical biologic processes including embryonic development, mature tissue maintenance, and cell proliferation. Dysregulation of the Wnt signaling… (more)

Subjects/Keywords: Ankyrin Repeat Protein; Computational Protein Design; Frizzled; Protein Engineering; Rosetta; Wnt Signaling; Molecular biology; Biochemistry; Biomedical engineering; Molecular and cellular biology

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APA (6^th Edition):

Dang, L. T. (2017). Computational Design and Optimization of Novel Subtype Specific Frizzled Binding Proteins for Modulation of Wnt Signaling. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40260

Chicago Manual of Style (16^th Edition):

Dang, Luke Thomas. “Computational Design and Optimization of Novel Subtype Specific Frizzled Binding Proteins for Modulation of Wnt Signaling.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/40260.

MLA Handbook (7^th Edition):

Dang, Luke Thomas. “Computational Design and Optimization of Novel Subtype Specific Frizzled Binding Proteins for Modulation of Wnt Signaling.” 2017. Web. 20 Jan 2021.

Vancouver:

Dang LT. Computational Design and Optimization of Novel Subtype Specific Frizzled Binding Proteins for Modulation of Wnt Signaling. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/40260.

Council of Science Editors:

Dang LT. Computational Design and Optimization of Novel Subtype Specific Frizzled Binding Proteins for Modulation of Wnt Signaling. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40260

University of Washington

5. Hsia, Yang. Design of a hyperstable 60-subunit icosahedral nanocage.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/40491

► The icosahedron is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport1,2. There has… (more)

Subjects/Keywords:

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APA (6^th Edition):

Hsia, Y. (2017). Design of a hyperstable 60-subunit icosahedral nanocage. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40491

Chicago Manual of Style (16^th Edition):

Hsia, Yang. “Design of a hyperstable 60-subunit icosahedral nanocage.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/40491.

MLA Handbook (7^th Edition):

Hsia, Yang. “Design of a hyperstable 60-subunit icosahedral nanocage.” 2017. Web. 20 Jan 2021.

Vancouver:

Hsia Y. Design of a hyperstable 60-subunit icosahedral nanocage. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/40491.

Council of Science Editors:

Hsia Y. Design of a hyperstable 60-subunit icosahedral nanocage. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40491

University of Washington

6. Ovchinnikov, Sergey. Protein structure determination using evolutionary information.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/40652

► For billions of years, nature has been conducting the greatest experiment of all time. Imagine one day gaining access to the detailed notes from these… (more)

Subjects/Keywords: Coevolution; GREMLIN; Protein; ROSETTA; Structure prediction; Biochemistry; Bioinformatics; Biology; Molecular and cellular biology

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APA (6^th Edition):

Ovchinnikov, S. (2017). Protein structure determination using evolutionary information. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40652

Chicago Manual of Style (16^th Edition):

Ovchinnikov, Sergey. “Protein structure determination using evolutionary information.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/40652.

MLA Handbook (7^th Edition):

Ovchinnikov, Sergey. “Protein structure determination using evolutionary information.” 2017. Web. 20 Jan 2021.

Vancouver:

Ovchinnikov S. Protein structure determination using evolutionary information. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/40652.

Council of Science Editors:

Ovchinnikov S. Protein structure determination using evolutionary information. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40652

University of Washington

7. Bryan, Cassie Marie. Computational Design of Hyperstable, De Novo Miniproteins Targeting PD-1.

Degree: PhD, 2018, University of Washington

URL: http://hdl.handle.net/1773/40848

► Computational protein design has recently advanced to a new era with the de novo design of stable proteins targeting native protein ligands. In this dissertation,… (more)

▼ Computational protein design has recently advanced to a new era with the de novo design of stable proteins targeting native protein ligands. In this dissertation, I will present the first de novo protein binder with an all beta interface targeting the T cell receptor, programmed cell death protein 1 (PD-1). Expressed on activated T cells, PD-1 inhibits T cell function and proliferation to prevent an excessive immune response. Tumor cells often take advantage of this pathway by over-expressing one of the ligands of PD-1, PD-L1 or PD-L2, to evade immune destruction. Additionally, impairment of the PD-1 pathway through a variety of mechanisms can lead to autoimmunity. Using a combination of computational design and experimental approaches, we have developed a de novo miniprotein that specifically binds PD-1 at the ligand interface. This protein binds murine PD-1 at a Kd of approximately 1 µM on yeast. The apo crystal structure shows that the binder folds as designed with a backbone RMSD of 1.3 Å to the design model. The 4.5 kDa protein proved to be very stable by chemical denaturation in GuHCl likely due to its three disulfide bonds. Over the years, I have identified several other binders using the canonical method of yeast surface display that ultimately had to be abandoned because of their inability to be produced as soluble proteins. I hypothesize this results from the use of the highly expressed native yeast protein Aga2p for display of the protein-of-interest (POI) on the cell surface. Here, I present a new method that replaces the Aga2p fusion with a minimal tag for covalent capture of the secreted protein and takes advantage of the natural yeast quality control pathways to discriminate between misfolded and well-folded proteins. This novel secretion capture system is a powerful tool for the screening, optimization, and production of well-expressed, functional proteins. Improved high-throughput methods for screening and optimizing stable, functional proteins enable generation of de novo binders that are more readily amenable to a variety of applications. The small, hyperstable PD-1 binding domain presented here has potential use in a variety of cancer and autoimmune therapy platforms. Advisors/Committee Members: Baker, David (advisor).

Subjects/Keywords: Computational Design; PD-1; Protein Design; Protein Engineering; Yeast Display; Biochemistry; Bioengineering; Biological chemistry

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APA (6^th Edition):

Bryan, C. M. (2018). Computational Design of Hyperstable, De Novo Miniproteins Targeting PD-1. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40848

Chicago Manual of Style (16^th Edition):

Bryan, Cassie Marie. “Computational Design of Hyperstable, De Novo Miniproteins Targeting PD-1.” 2018. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/40848.

MLA Handbook (7^th Edition):

Bryan, Cassie Marie. “Computational Design of Hyperstable, De Novo Miniproteins Targeting PD-1.” 2018. Web. 20 Jan 2021.

Vancouver:

Bryan CM. Computational Design of Hyperstable, De Novo Miniproteins Targeting PD-1. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/40848.

Council of Science Editors:

Bryan CM. Computational Design of Hyperstable, De Novo Miniproteins Targeting PD-1. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/40848

University of Washington

8. Ford, Alexander. Nonparametric Structure Models in Local Protein Conformation Sampling and Design.

Degree: PhD, 2018, University of Washington

URL: http://hdl.handle.net/1773/41742

► Protein design relies of the identification of a sequence that specifically encodes a target conformation as a folded native state. This native states is encoded… (more)

Subjects/Keywords:

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APA (6^th Edition):

Ford, A. (2018). Nonparametric Structure Models in Local Protein Conformation Sampling and Design. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/41742

Chicago Manual of Style (16^th Edition):

Ford, Alexander. “Nonparametric Structure Models in Local Protein Conformation Sampling and Design.” 2018. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/41742.

MLA Handbook (7^th Edition):

Ford, Alexander. “Nonparametric Structure Models in Local Protein Conformation Sampling and Design.” 2018. Web. 20 Jan 2021.

Vancouver:

Ford A. Nonparametric Structure Models in Local Protein Conformation Sampling and Design. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/41742.

Council of Science Editors:

Ford A. Nonparametric Structure Models in Local Protein Conformation Sampling and Design. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/41742

University of Washington

9. Nelson, Jorgen. Directed evolution and de novo design for improved pathogen-targeting protein drugs.

Degree: PhD, 2018, University of Washington

URL: http://hdl.handle.net/1773/42368

► Infectious diseases continue to claim millions of lives, and protein design with Rosetta is quickly becoming a contributor to the fight against these diseases. My… (more)

Subjects/Keywords: malaria; rosetta; Biochemistry; Bioengineering; Genetics

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APA (6^th Edition):

Nelson, J. (2018). Directed evolution and de novo design for improved pathogen-targeting protein drugs. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/42368

Chicago Manual of Style (16^th Edition):

Nelson, Jorgen. “Directed evolution and de novo design for improved pathogen-targeting protein drugs.” 2018. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/42368.

MLA Handbook (7^th Edition):

Nelson, Jorgen. “Directed evolution and de novo design for improved pathogen-targeting protein drugs.” 2018. Web. 20 Jan 2021.

Vancouver:

Nelson J. Directed evolution and de novo design for improved pathogen-targeting protein drugs. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/42368.

Council of Science Editors:

Nelson J. Directed evolution and de novo design for improved pathogen-targeting protein drugs. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/42368

University of Washington

10. Chevalier, Aaron. Computational design and optimization of protein-protein interactions to engineer novel binders of Influenza Hemagglutinin.

Degree: PhD, 2015, University of Washington

URL: http://hdl.handle.net/1773/33101

► Influenza is a serious public health concern and new therapeutics that protect against this highly adaptable virus are urgently needed. For this dissertation my efforts… (more)

Subjects/Keywords: Biomedical engineering; bioengineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chevalier, A. (2015). Computational design and optimization of protein-protein interactions to engineer novel binders of Influenza Hemagglutinin. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/33101

Chicago Manual of Style (16^th Edition):

Chevalier, Aaron. “Computational design and optimization of protein-protein interactions to engineer novel binders of Influenza Hemagglutinin.” 2015. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/33101.

MLA Handbook (7^th Edition):

Chevalier, Aaron. “Computational design and optimization of protein-protein interactions to engineer novel binders of Influenza Hemagglutinin.” 2015. Web. 20 Jan 2021.

Vancouver:

Chevalier A. Computational design and optimization of protein-protein interactions to engineer novel binders of Influenza Hemagglutinin. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/33101.

Council of Science Editors:

Chevalier A. Computational design and optimization of protein-protein interactions to engineer novel binders of Influenza Hemagglutinin. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/33101

University of Washington

11. Day, Austin L. Computational Design of Small Molecule Binding Proteins.

Degree: PhD, 2015, University of Washington

URL: http://hdl.handle.net/1773/33592

► Protein design is still in its infancy, yet there have been many impressive examples of success in designing proteins to fold into a predictable structure,… (more)

▼ Protein design is still in its infancy, yet there have been many impressive examples of success in designing proteins to fold into a predictable structure, to catalyse enzymatic reactions, or to bind a specific protein, DNA sequence , or small molecule target . Each of these successes in the field is a major milestone, but protein design still lacks a generalized solution for reliably repeating these successes on future targets. The design of proteins capable of binding small molecules is particularly challenging due to the necessity to accurately understand and computationally model atomic scale physiochemical principles. We work towards this goal because being able to reliably design small molecule binders would allow for faster, and more efficient creation of detection elements for biosensors, sequestration proteins to aid in dialysis, and orthogonal binding tags for use in biotechnology applications. Even a modest advantage gained through computational design would allow for faster results when using more traditional directed evolution search methods. Since control of molecular specificity at the atomic level is essential for diagnostic applications in which multiple similar molecules are present and require discrimination from each other, computational modelling can be especially useful because the desired molecular specificity can be explicitly incorporated into the design. Such cases exist with the detection of tetrahydrocannabinol (THC) from the non-psychoactive cannabidiol and downstream metabolites present in users of marijuana, and in the detection of 25-hydroxycholecaliferol from 25-hydroxyergocalciferol, a clinically important distinction of vitamin D3 metabolites where the two compounds differ by a single methyl group. With this particular goal in mind, we have developed a computational protocol, using the Rosetta software package, capable of designing protein models with good shape complementarity, favorable chemical environments, and designed molecular specificity for a target protein-ligand interaction. This protocol was optimized over many iterations and incremental successes into a final revision that is capable of creating protein binders for the ligands 25-hydroxycholecaliferol, the hormonally active form of vitamin D3, and tetrahydrocannabinol, the primary psychoactive ingredient in cannabis. In addition to learning how to make successful protein binding designs, we also attempted to recover non-functional designs through stabilization. Using an algorithm for inserting proline substitutions into failed designs, we believe we have identified a lack of stability as one potential cause for failed binding protein designs. The protocol improvements learned from both our successful and recovered function binders should move us towards a more generalizable and reliable method for designing future protein-ligand interactions. Advisors/Committee Members: Baker, David (advisor).

Subjects/Keywords: Computational; Ligand; Methods; Protein Design; Protein Engineering; Small Molecule; Biomedical engineering; Biochemistry; bioengineering

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APA (6^th Edition):

Day, A. L. (2015). Computational Design of Small Molecule Binding Proteins. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/33592

Chicago Manual of Style (16^th Edition):

Day, Austin L. “Computational Design of Small Molecule Binding Proteins.” 2015. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/33592.

MLA Handbook (7^th Edition):

Day, Austin L. “Computational Design of Small Molecule Binding Proteins.” 2015. Web. 20 Jan 2021.

Vancouver:

Day AL. Computational Design of Small Molecule Binding Proteins. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/33592.

Council of Science Editors:

Day AL. Computational Design of Small Molecule Binding Proteins. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/33592

University of Washington

12. Yu, Shawn. Computational design of interleukin-2 mimetics.

Degree: PhD, 2015, University of Washington

URL: http://hdl.handle.net/1773/33593

► Interleukin-2 is a cytokine that plays a central role in immune system homeostasis, exerting paradoxical immunostimulatory and immunoregulatory effects based on its interactions with various… (more)

Subjects/Keywords: computational design; interleukin-2; protein design; protein engineering; Rosetta; Biochemistry; Immunology; bioengineering

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APA (6^th Edition):

Yu, S. (2015). Computational design of interleukin-2 mimetics. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/33593

Chicago Manual of Style (16^th Edition):

Yu, Shawn. “Computational design of interleukin-2 mimetics.” 2015. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/33593.

MLA Handbook (7^th Edition):

Yu, Shawn. “Computational design of interleukin-2 mimetics.” 2015. Web. 20 Jan 2021.

Vancouver:

Yu S. Computational design of interleukin-2 mimetics. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/33593.

Council of Science Editors:

Yu S. Computational design of interleukin-2 mimetics. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/33593

University of Washington

13. Wang, Yu-Ruei. Protein Structure Determination from Cryo-electron Microscopy Density Maps.

Degree: PhD, 2015, University of Washington

URL: http://hdl.handle.net/1773/33597

► Single-particle cryo-electron microscopy (cryo-EM) has emerged as a powerful tool in structure determination of macromolecular complexes that are not suitable for crystallographic studies. Recent advances… (more)

Subjects/Keywords: Cryo-EM; electron density map; Model building; Rosetta; Structure determination; Structure prediction; Biochemistry; Bioinformatics; biological chemistry

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APA (6^th Edition):

Wang, Y. (2015). Protein Structure Determination from Cryo-electron Microscopy Density Maps. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/33597

Chicago Manual of Style (16^th Edition):

Wang, Yu-Ruei. “Protein Structure Determination from Cryo-electron Microscopy Density Maps.” 2015. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/33597.

MLA Handbook (7^th Edition):

Wang, Yu-Ruei. “Protein Structure Determination from Cryo-electron Microscopy Density Maps.” 2015. Web. 20 Jan 2021.

Vancouver:

Wang Y. Protein Structure Determination from Cryo-electron Microscopy Density Maps. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/33597.

Council of Science Editors:

Wang Y. Protein Structure Determination from Cryo-electron Microscopy Density Maps. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/33597

University of Washington

14. Bale, Jacob Barile. Computational design of co-assembling multi-component protein nanomaterials.

Degree: PhD, 2016, University of Washington

URL: http://hdl.handle.net/1773/35263

► Molecular self- and co-assembly of proteins into highly ordered symmetric complexes is an elegant and powerful means of patterning matter at the atomic scale and… (more)

Subjects/Keywords: co-assembly; computational protein design; nanomaterials; polyhedra; self-assembly; structural biology; Biochemistry; Nanoscience; Engineering; molecular and cellular biology

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APA (6^th Edition):

Bale, J. B. (2016). Computational design of co-assembling multi-component protein nanomaterials. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/35263

Chicago Manual of Style (16^th Edition):

Bale, Jacob Barile. “Computational design of co-assembling multi-component protein nanomaterials.” 2016. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/35263.

MLA Handbook (7^th Edition):

Bale, Jacob Barile. “Computational design of co-assembling multi-component protein nanomaterials.” 2016. Web. 20 Jan 2021.

Vancouver:

Bale JB. Computational design of co-assembling multi-component protein nanomaterials. [Internet] [Doctoral dissertation]. University of Washington; 2016. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/35263.

Council of Science Editors:

Bale JB. Computational design of co-assembling multi-component protein nanomaterials. [Doctoral Dissertation]. University of Washington; 2016. Available from: http://hdl.handle.net/1773/35263

University of Washington

15. Butterfield, Gabriel Lang. Evolution of Synthetic Nucleocapsids Encapsulating their own RNA genome.

Degree: PhD, 2018, University of Washington

URL: http://hdl.handle.net/1773/43109

► Viruses are the simplest example of a fundamental feature of biology— they maintain genotype phenotype linkage in complex biochemical environments by encapsulating and protecting a… (more)

▼ Viruses are the simplest example of a fundamental feature of biology— they maintain genotype phenotype linkage in complex biochemical environments by encapsulating and protecting a nucleic acid genome. This allows evolution to improve the functional properties required to complete their life cycle and deliver their genome into the host cells matching their tropism. While these naturally occurring systems have been modified to change their tropism1 and to display proteins or peptides2-4, billions of years of evolution have favored efficiency at the expense of modularity, making viral capsids difficult to engineer. Synthetic systems composed of non-viral proteins could provide a blank slate to evolve desired properties for drug delivery and other biomedical applications, while avoiding the safety risks and engineering challenges associated with viruses. Here we create synthetic nucleocapsids—computationally designed icosahedral protein assemblies5,6 with positively charged inner surfaces capable of packaging their own full-length mRNA genomes—and explore their ability to evolve virus-like properties by generating diversified populations using Escherichia coli as an expression host. Several generations of evolution resulted in drastically improved genome packaging (>133-fold), stability in whole murine blood (from less than 3.7% to 71% of packaged RNA protected after 6 hours of treatment), and in vivo circulation time (from less than 5 minutes to 4.5 hours). The resulting synthetic nucleocapsids package one full-length RNA genome for every 11 icosahedral assemblies, similar to the best recombinant adeno-associated virus (AAV) vectors7,8. Our results show that there are simple evolutionary paths through which protein assemblies can acquire virus-like genome packaging and protection. Considerable effort has been directed at “top-down” modification of viruses to be safe and effective for drug delivery and vaccine applications1,9,10; the ability to computationally design synthetic nanomaterials and to optimize them through evolution now enables a complementary “bottom-up” approach with considerable advantages in programmability and control. Advisors/Committee Members: Baker, David (advisor).

Subjects/Keywords:

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APA (6^th Edition):

Butterfield, G. L. (2018). Evolution of Synthetic Nucleocapsids Encapsulating their own RNA genome. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43109

Chicago Manual of Style (16^th Edition):

Butterfield, Gabriel Lang. “Evolution of Synthetic Nucleocapsids Encapsulating their own RNA genome.” 2018. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/43109.

MLA Handbook (7^th Edition):

Butterfield, Gabriel Lang. “Evolution of Synthetic Nucleocapsids Encapsulating their own RNA genome.” 2018. Web. 20 Jan 2021.

Vancouver:

Butterfield GL. Evolution of Synthetic Nucleocapsids Encapsulating their own RNA genome. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/43109.

Council of Science Editors:

Butterfield GL. Evolution of Synthetic Nucleocapsids Encapsulating their own RNA genome. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/43109

University of Washington

16. Ueda, George Thomas. Computational Design of Symmetric Protein Complexes with Implications for Vaccine and Biotherapeutic Development.

Degree: PhD, 2019, University of Washington

URL: http://hdl.handle.net/1773/43303

► Using a newly developed computational docking and scoring method combined with Rosetta two-sided interface design, we demonstrated accurate design of self-assembling oligomeric proteins that exhibit… (more)

Subjects/Keywords: Biotherapeutic; Computational; Design; Engineering; Protein; Vaccine; Biochemistry; Bioengineering; Computational chemistry; Biological chemistry

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APA (6^th Edition):

Ueda, G. T. (2019). Computational Design of Symmetric Protein Complexes with Implications for Vaccine and Biotherapeutic Development. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43303

Chicago Manual of Style (16^th Edition):

Ueda, George Thomas. “Computational Design of Symmetric Protein Complexes with Implications for Vaccine and Biotherapeutic Development.” 2019. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/43303.

MLA Handbook (7^th Edition):

Ueda, George Thomas. “Computational Design of Symmetric Protein Complexes with Implications for Vaccine and Biotherapeutic Development.” 2019. Web. 20 Jan 2021.

Vancouver:

Ueda GT. Computational Design of Symmetric Protein Complexes with Implications for Vaccine and Biotherapeutic Development. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/43303.

Council of Science Editors:

Ueda GT. Computational Design of Symmetric Protein Complexes with Implications for Vaccine and Biotherapeutic Development. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43303

University of Washington

17. Haydon, Ian. De novo protein fusions as platforms for enzyme design.

Degree: 2019, University of Washington

URL: http://hdl.handle.net/1773/43305

► Control over enzymatic catalysis is a central goal of biotechnology. Recent advances in computational protein design are beginning to allow for the de novo creation… (more)

Subjects/Keywords: computational biology; enzymes; protein design; protein engineering; Biochemistry; Bioengineering; Biophysics; Biological chemistry

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APA (6^th Edition):

Haydon, I. (2019). De novo protein fusions as platforms for enzyme design. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/43305

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Haydon, Ian. “De novo protein fusions as platforms for enzyme design.” 2019. Thesis, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/43305.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Haydon, Ian. “De novo protein fusions as platforms for enzyme design.” 2019. Web. 20 Jan 2021.

Vancouver:

Haydon I. De novo protein fusions as platforms for enzyme design. [Internet] [Thesis]. University of Washington; 2019. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/43305.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Haydon I. De novo protein fusions as platforms for enzyme design. [Thesis]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43305

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Washington

18. Basanta, Benjamin. Beyond single-protein de novo design: A generative algorithm for the NTF2-like superfamily.

Degree: PhD, 2019, University of Washington

URL: http://hdl.handle.net/1773/43640

► Natural proteins evolved over billions of years to regulate cellular growth, ward off infection and capture and store solar energy. Proteins thus serve as the… (more)

▼ Natural proteins evolved over billions of years to regulate cellular growth, ward off infection and capture and store solar energy. Proteins thus serve as the molecular basis for life. The promise of protein design is to use nature’s favorite toolbox to solve modern human problems without having to wait for the long and meandering path of natural selection. Protein structure determines function, so it is not surprising proteins sample a great variety of structures. Thus, it is reasonable to expect that designing proteins with functions not seen in nature would require access to comparable structural diversity, more specifically, diversity of active site structure. Despite the advances in de novo protein design, the systematic generation of proteins containing pockets that can harbor substrates has been lacking. The use of a natural small alpha-beta fold, the Nuclear Transport Factor 2-like (NTF2-like) fold, to design a high affinity small-molecule binding protein, and the diversity observed in that family, have posed the idea that significant pocket structural diversity could be derived from this relatively simple, small, alpha-beta fold. To explore this idea, we analyzed the structures of proteins belonging to the NTF2-like superfamily and other proteins with similar characteristics to understand the determinants of their structural diversity. The most salient feature of the NTF2-like superfamily is the curved beta-sheet that forms most of their pockets in its concave face. Curved beta sheets depart from the classic beta pleated structure displaying bulges, tight kinks and irregular bending and twisting. The first step towards de novo design of a large variety of NTF2-like proteins is devising principles for designing curved beta sheets. In this work, we demonstrate we can generate a number of different curved sheets in the context of NTF2-like proteins. We then use these principles, along with additional information from native NTF2-like proteins, to create a generative algorithm that can widely sample structural diversity while still producing physically realistic models. We show this algorithm can produce a large variety of NTF2-like proteins, and through cycles of large-scale design and validation, we increase the diversity and success rate of its output. As a proof of principle, we design a binder of the mycotoxin aflatoxin B1, which could serve as starting material for devising aflatoxin-chelating or degrading materials. Advisors/Committee Members: Baker, David (advisor).

Subjects/Keywords: Computational Biology; generative algorithm; generative design; High-throughput screening; Protein design; Biochemistry; Biological chemistry

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APA (6^th Edition):

Basanta, B. (2019). Beyond single-protein de novo design: A generative algorithm for the NTF2-like superfamily. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43640

Chicago Manual of Style (16^th Edition):

Basanta, Benjamin. “Beyond single-protein de novo design: A generative algorithm for the NTF2-like superfamily.” 2019. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/43640.

MLA Handbook (7^th Edition):

Basanta, Benjamin. “Beyond single-protein de novo design: A generative algorithm for the NTF2-like superfamily.” 2019. Web. 20 Jan 2021.

Vancouver:

Basanta B. Beyond single-protein de novo design: A generative algorithm for the NTF2-like superfamily. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/43640.

Council of Science Editors:

Basanta B. Beyond single-protein de novo design: A generative algorithm for the NTF2-like superfamily. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43640

University of Washington

19. Koepnick, Brian. Protein design by citizen scientists.

Degree: PhD, 2019, University of Washington

URL: http://hdl.handle.net/1773/43642

► Proteins are a class of molecule best known for their tendency to fold into well-defined 3-dimensional structures. The structure of a protein is determined by… (more)

Subjects/Keywords: citizen science; crowdsource; Foldit; protein design; Bioengineering; Biological chemistry

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APA (6^th Edition):

Koepnick, B. (2019). Protein design by citizen scientists. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43642

Chicago Manual of Style (16^th Edition):

Koepnick, Brian. “Protein design by citizen scientists.” 2019. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/43642.

MLA Handbook (7^th Edition):

Koepnick, Brian. “Protein design by citizen scientists.” 2019. Web. 20 Jan 2021.

Vancouver:

Koepnick B. Protein design by citizen scientists. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/43642.

Council of Science Editors:

Koepnick B. Protein design by citizen scientists. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43642

University of Washington

20. Smith, Matthew. Computational Design and Directed Evolution of Novel Enzymes.

Degree: PhD, 2013, University of Washington

URL: http://hdl.handle.net/1773/24224

► Enzymes are the most specific and active catalysts found in nature, and offer unique chemical properties suited to solving important industrial, medical, and environmental problems.… (more)

Subjects/Keywords: alkyltransferase; computational design; directed evolution; enzymes; esterase; Biochemistry; molecular and cellular biology

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APA (6^th Edition):

Smith, M. (2013). Computational Design and Directed Evolution of Novel Enzymes. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/24224

Chicago Manual of Style (16^th Edition):

Smith, Matthew. “Computational Design and Directed Evolution of Novel Enzymes.” 2013. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/24224.

MLA Handbook (7^th Edition):

Smith, Matthew. “Computational Design and Directed Evolution of Novel Enzymes.” 2013. Web. 20 Jan 2021.

Vancouver:

Smith M. Computational Design and Directed Evolution of Novel Enzymes. [Internet] [Doctoral dissertation]. University of Washington; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/24224.

Council of Science Editors:

Smith M. Computational Design and Directed Evolution of Novel Enzymes. [Doctoral Dissertation]. University of Washington; 2013. Available from: http://hdl.handle.net/1773/24224

University of Washington

21. Moody, James. Computational design of protein-protein interactions to engineer novel inhibitors of the p53 pathway and the polycomb repressive complex.

Degree: PhD, 2014, University of Washington

URL: http://hdl.handle.net/1773/26172

► Here I present 2 examples of the application of the Rosetta macromolecular modeling software suite to the successful development of novel protein-based inhibitors with the… (more)

Subjects/Keywords: Biotechnology; Computational; Design; Mdmx; PRC2; Protein; Biochemistry; molecular and cellular biology

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APA (6^th Edition):

Moody, J. (2014). Computational design of protein-protein interactions to engineer novel inhibitors of the p53 pathway and the polycomb repressive complex. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/26172

Chicago Manual of Style (16^th Edition):

Moody, James. “Computational design of protein-protein interactions to engineer novel inhibitors of the p53 pathway and the polycomb repressive complex.” 2014. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/26172.

MLA Handbook (7^th Edition):

Moody, James. “Computational design of protein-protein interactions to engineer novel inhibitors of the p53 pathway and the polycomb repressive complex.” 2014. Web. 20 Jan 2021.

Vancouver:

Moody J. Computational design of protein-protein interactions to engineer novel inhibitors of the p53 pathway and the polycomb repressive complex. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/26172.

Council of Science Editors:

Moody J. Computational design of protein-protein interactions to engineer novel inhibitors of the p53 pathway and the polycomb repressive complex. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/26172

University of Washington

22. Richter, Florian. Computational de-novo design of ester hydrolases.

Degree: PhD, 2013, University of Washington

URL: http://hdl.handle.net/1773/21829

► Computational protein design is a relatively new technique used to devise amino acid sequences to fold into proteins having novel structures or functions. Here, we… (more)

Subjects/Keywords: catalysis; computational protein design; enzyme design; hydrolysis; synthetic biology; Biochemistry; Chemistry; Biological chemistry

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APA (6^th Edition):

Richter, F. (2013). Computational de-novo design of ester hydrolases. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/21829

Chicago Manual of Style (16^th Edition):

Richter, Florian. “Computational de-novo design of ester hydrolases.” 2013. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/21829.

MLA Handbook (7^th Edition):

Richter, Florian. “Computational de-novo design of ester hydrolases.” 2013. Web. 20 Jan 2021.

Vancouver:

Richter F. Computational de-novo design of ester hydrolases. [Internet] [Doctoral dissertation]. University of Washington; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/21829.

Council of Science Editors:

Richter F. Computational de-novo design of ester hydrolases. [Doctoral Dissertation]. University of Washington; 2013. Available from: http://hdl.handle.net/1773/21829

University of Washington

23. Kellogg, Elizabeth Hua-Mei. Assessing and Improving Computational Models of Protein Thermodynamics and Kinetics.

Degree: PhD, 2013, University of Washington

URL: http://hdl.handle.net/1773/22430

► The purpose of this thesis is to rigorously assess and improve computational models of protein thermodynamics and kinetics. The first part consists of computational ddG… (more)

Subjects/Keywords: ddG prediction; markov state model; protein structure; Rosetta; Biochemistry; Biophysics; biological chemistry

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APA (6^th Edition):

Kellogg, E. H. (2013). Assessing and Improving Computational Models of Protein Thermodynamics and Kinetics. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/22430

Chicago Manual of Style (16^th Edition):

Kellogg, Elizabeth Hua-Mei. “Assessing and Improving Computational Models of Protein Thermodynamics and Kinetics.” 2013. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/22430.

MLA Handbook (7^th Edition):

Kellogg, Elizabeth Hua-Mei. “Assessing and Improving Computational Models of Protein Thermodynamics and Kinetics.” 2013. Web. 20 Jan 2021.

Vancouver:

Kellogg EH. Assessing and Improving Computational Models of Protein Thermodynamics and Kinetics. [Internet] [Doctoral dissertation]. University of Washington; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/22430.

Council of Science Editors:

Kellogg EH. Assessing and Improving Computational Models of Protein Thermodynamics and Kinetics. [Doctoral Dissertation]. University of Washington; 2013. Available from: http://hdl.handle.net/1773/22430

University of Washington

24. Berger, Stephanie. Controlling apoptosis with computationally designed inhibitors targeting pro-survival and pro-apoptosis BCL2 family members.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/39947

► BCL2 family proteins regulate apoptosis and thus play a critical role in tissue homeostasis and development in healthy cells. A number of pathologies exploit the… (more)

Subjects/Keywords: apoptosis; BCL2; cancer; computational protein design; Molecular biology; Biomedical engineering; Biochemistry; Bioengineering

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APA (6^th Edition):

Berger, S. (2017). Controlling apoptosis with computationally designed inhibitors targeting pro-survival and pro-apoptosis BCL2 family members. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/39947

Chicago Manual of Style (16^th Edition):

Berger, Stephanie. “Controlling apoptosis with computationally designed inhibitors targeting pro-survival and pro-apoptosis BCL2 family members.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/39947.

MLA Handbook (7^th Edition):

Berger, Stephanie. “Controlling apoptosis with computationally designed inhibitors targeting pro-survival and pro-apoptosis BCL2 family members.” 2017. Web. 20 Jan 2021.

Vancouver:

Berger S. Controlling apoptosis with computationally designed inhibitors targeting pro-survival and pro-apoptosis BCL2 family members. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/39947.

Council of Science Editors:

Berger S. Controlling apoptosis with computationally designed inhibitors targeting pro-survival and pro-apoptosis BCL2 family members. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/39947

University of Washington

25. Younger, David Aaron. High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating.

Degree: PhD, 2017, University of Washington

URL: http://hdl.handle.net/1773/40488

► High-throughput methods for screening protein-protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative… (more)

Subjects/Keywords: High-throughput screening; Protein Engineering; Protein-protein interaction networks; Synthetic Biology; Yeast Mating; Biomedical engineering; Biochemistry; Cellular biology; Bioengineering

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APA (6^th Edition):

Younger, D. A. (2017). High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40488

Chicago Manual of Style (16^th Edition):

Younger, David Aaron. “High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating.” 2017. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/40488.

MLA Handbook (7^th Edition):

Younger, David Aaron. “High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating.” 2017. Web. 20 Jan 2021.

Vancouver:

Younger DA. High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/40488.

Council of Science Editors:

Younger DA. High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40488

University of Washington

26. Chen, Zibo. Programmable Design of Protein Interaction Specificity and Logic Gates.

Degree: PhD, 2019, University of Washington

URL: http://hdl.handle.net/1773/43306

► The binding specificity of DNA molecules is straightforward: adenine binds thymine, and cytosine binds guanine. This simple encoding of specificity enables the binding between two… (more)

Subjects/Keywords: Biophysics; Computational biology; Structural biology; Biochemistry; Biological chemistry

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APA (6^th Edition):

Chen, Z. (2019). Programmable Design of Protein Interaction Specificity and Logic Gates. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43306

Chicago Manual of Style (16^th Edition):

Chen, Zibo. “Programmable Design of Protein Interaction Specificity and Logic Gates.” 2019. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/43306.

MLA Handbook (7^th Edition):

Chen, Zibo. “Programmable Design of Protein Interaction Specificity and Logic Gates.” 2019. Web. 20 Jan 2021.

Vancouver:

Chen Z. Programmable Design of Protein Interaction Specificity and Logic Gates. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/43306.

Council of Science Editors:

Chen Z. Programmable Design of Protein Interaction Specificity and Logic Gates. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43306

27. Conway, Patrick. Improving The Energy Function Used In Rosetta For Protein Structure Prediction and Design.

Degree: PhD, 2015, University of Washington

URL: http://hdl.handle.net/1773/27414

► Protein structure prediction and design relies on conformational sampling and scoring to uncover a global energy minimum. While it is critical to have an accurate… (more)

Subjects/Keywords: Biochemistry; biological chemistry

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APA (6^th Edition):

Conway, P. (2015). Improving The Energy Function Used In Rosetta For Protein Structure Prediction and Design. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/27414

Chicago Manual of Style (16^th Edition):

Conway, Patrick. “Improving The Energy Function Used In Rosetta For Protein Structure Prediction and Design.” 2015. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/27414.

MLA Handbook (7^th Edition):

Conway, Patrick. “Improving The Energy Function Used In Rosetta For Protein Structure Prediction and Design.” 2015. Web. 20 Jan 2021.

Vancouver:

Conway P. Improving The Energy Function Used In Rosetta For Protein Structure Prediction and Design. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/27414.

Council of Science Editors:

Conway P. Improving The Energy Function Used In Rosetta For Protein Structure Prediction and Design. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/27414

28. Castellanos, Javier Ignacio. Iterative Multistate Negative Design of protein folds.

Degree: PhD, 2014, University of Washington

URL: http://hdl.handle.net/1773/25971

Subjects/Keywords: Protein Design; Biochemistry; biological chemistry

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APA (6^th Edition):

Castellanos, J. I. (2014). Iterative Multistate Negative Design of protein folds. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/25971

Chicago Manual of Style (16^th Edition):

Castellanos, Javier Ignacio. “Iterative Multistate Negative Design of protein folds.” 2014. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/25971.

MLA Handbook (7^th Edition):

Castellanos, Javier Ignacio. “Iterative Multistate Negative Design of protein folds.” 2014. Web. 20 Jan 2021.

Vancouver:

Castellanos JI. Iterative Multistate Negative Design of protein folds. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/25971.

Council of Science Editors:

Castellanos JI. Iterative Multistate Negative Design of protein folds. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/25971

29. King, Chris. Computational Design of Protein Therapeutics with Reduced Immunogenicity through Structural Modeling of Protein Interactions.

Degree: PhD, 2014, University of Washington

URL: http://hdl.handle.net/1773/25382

► Proteins possess huge potential as therapeutic agents for the control and modulation of human physiology. Protein interactions regulate most physiological processes, mediating the connection between… (more)

Subjects/Keywords: biotherapeutics; deimmunization; machine learning; molecular modeling; protein design; Biochemistry; Bioinformatics; Biophysics; biological chemistry

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APA (6^th Edition):

King, C. (2014). Computational Design of Protein Therapeutics with Reduced Immunogenicity through Structural Modeling of Protein Interactions. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/25382

Chicago Manual of Style (16^th Edition):

King, Chris. “Computational Design of Protein Therapeutics with Reduced Immunogenicity through Structural Modeling of Protein Interactions.” 2014. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/25382.

MLA Handbook (7^th Edition):

King, Chris. “Computational Design of Protein Therapeutics with Reduced Immunogenicity through Structural Modeling of Protein Interactions.” 2014. Web. 20 Jan 2021.

Vancouver:

King C. Computational Design of Protein Therapeutics with Reduced Immunogenicity through Structural Modeling of Protein Interactions. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/25382.

Council of Science Editors:

King C. Computational Design of Protein Therapeutics with Reduced Immunogenicity through Structural Modeling of Protein Interactions. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/25382

30. Boissel, Sandrine. megaTALs: a novel rare-cleaving nuclease platform for therapeutic genome engineering.

Degree: PhD, 2014, University of Washington

URL: http://hdl.handle.net/1773/25103

► Rare-cleaving endonucleases have emerged as important tools for making targeted genome modifications. While multiple platforms are now available to generate reagents for research applications, each… (more)

Subjects/Keywords: genome engineering; megaTAL; nuclease; Molecular biology; molecular and cellular biology

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APA (6^th Edition):

Boissel, S. (2014). megaTALs: a novel rare-cleaving nuclease platform for therapeutic genome engineering. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/25103

Chicago Manual of Style (16^th Edition):

Boissel, Sandrine. “megaTALs: a novel rare-cleaving nuclease platform for therapeutic genome engineering.” 2014. Doctoral Dissertation, University of Washington. Accessed January 20, 2021. http://hdl.handle.net/1773/25103.

MLA Handbook (7^th Edition):

Boissel, Sandrine. “megaTALs: a novel rare-cleaving nuclease platform for therapeutic genome engineering.” 2014. Web. 20 Jan 2021.

Vancouver:

Boissel S. megaTALs: a novel rare-cleaving nuclease platform for therapeutic genome engineering. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1773/25103.

Council of Science Editors:

Boissel S. megaTALs: a novel rare-cleaving nuclease platform for therapeutic genome engineering. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/25103

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