Computational Protein Interface Design and Prediction with Experimental Constraints
Public Deposited- Last Modified
- March 22, 2019
- Creator
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Lewis, Steven Morgan
- Affiliation: School of Medicine, Department of Biochemistry and Biophysics
- Abstract
- Computational modeling is a powerful companion to direct experimental testing, because it allows researchers to answer questions that are too expensive to test in the lab or insurmountable with existing techniques. The development of algorithms and a computational framework in which to use them form an upfront cost of modeling. The Rosetta software suite is one such framework. Our recent rewrite of Rosetta using modular, reusable, object-oriented code allows Rosetta developers to rapidly and easily create modeling protocols to address new biological questions, reducing the investment needed to use computer modeling and enabling easier biologist-modeler collaborations. One such Rosetta protocol, AnchoredDesign, performs single-sided flexible-backbone protein-protein interface design. It borrows information from known partners of some protein target to help redesign arbitrary scaffolds into protein affinity reagents against that target. Benchmarking results indicate that the protocol performs well, and we used the protocol in combination with library display selections to generate fibronectin monobody binders to the Keap1 β-propeller domain with dissociation constants in the single nanomolar range. We also modeled the interaction between monobody 1F11 and cSrc-SH3. 1F11 has been functionalized with a solvent-sensitive fluorophore to allow it to report when and where in a cell Src-family kinases are active, and we used AnchoredDesign models to support structural hypotheses explaining this sensing ability. We developed two other new Rosetta protocols, FloppyTail and UBQ_E2_thioester, to address a biologist's hypotheses about particular protein structures. In the first set of experiments, collaborators suggested that a long, acidic C-terminal tail in a protein Cdc34 bound a basic cleft on its partner Cul1. We created FloppyTail by repurposing code Rosetta normally uses for ab initio structure prediction and loop modeling, and were able to use FloppyTail models to predict experimentally-verified protein contacts. In a second set of experiments, mutational data indicated that ubiquitin's interface with Cdc34 is critically important for ubiquitin transfer catalysis, despite the general opinion of the field. UBQ_E2_thioester was written to model the thioester-linked bound complex of ubiquitin and Cdc34, and again its results successfully predicted experimentally-verified protein contacts.
- Date of publication
- August 2012
- DOI
- Resource type
- Rights statement
- In Copyright
- Advisor
- Kuhlman, Brian
- Degree
- Doctor of Philosophy
- Graduation year
- 2012
- Language
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