The confluence of the fields of site-specific incorporation of unnatural amino acids and computational protein design represents a currently unexplored but promising avenue of biochemical research. While computational methods have been developed for naturally occurring proteins, the ability to treat non-natural amino acids with these techniques has yet to be fully explored. The research proposed seeks to develop a computational method that allows design of proteins containing unnatural amino acids, with the ultimate goal of generating novel unnatural amino acid dependent enzymes with therapeutic potential. The Rosetta suite of software developed by members of the Baker lab at the University of Washington will first be used to design iron binding proteins that utilize the metal binding unnatural amino acid bipyridyl alanine - first incorporated into proteins by Schultz and co-workers at The Scripps Research Institute. As this unnatural amino acid has inherent affinity for iron, the difficult problem of designing a metal binding site within a protein should be rendered more computationally tractable. As a second goal, a binding site for dopamine (which will provide two oxygen ligands for the iron) will be concurrently engineered. Catechols like dopamine have inherently high affinities for iron suggesting the engineered proteins could serve as sensors for this important class of small molecules. Finally, the catechol binding proteins will be further designed computationally with the goal of creating a non-natural amino acid dependent extradiol dioxygenase like enzyme. Such an enzyme could have a far-reaching impact with respect to bioremediation of persistent anthropomorphic toxins such as polychlorinated biphenyl compounds. The designed unnatural amino acid containing proteins will be produced in a bacterial expression system using techniques developed by members of the Schultz laboratory. Purified proteins will then be analyzed using a host of bioanalytical techniques that will examine metal or catechol binding abilities, or enzymatic activity depending on the specific aim. Data collected in the course of experimentation will be used for future design of other unnatural amino acid containing proteins both within the scope of this project, and beyond. Consequently, this research should have far reaching impacts within the biological sciences that will extend beyond the projects described above. As both of the scientific fields explored in this proposal are currently in a state of rapid growth, any information gleaned in the course of this research will guide further computational design efforts involving other currently available, genetically encoded non-natural amino acids, as well as those developed in the future.

Public Health Relevance

This research ultimately seeks to engineer unnatural amino acid containing proteins that possess the ability to catalytically degrade polychlorinated biphenyl environmental toxins. Additionally, the computational methods developed in the course of the research will provide vital information that will guide future efforts for the design of unnatural amino acid containing proteins with therapeutic and other useful functions.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F04B-D (20))
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Flicker, Paula F
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University of Washington
Schools of Medicine
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Mills, Jeremy H; Sheffler, William; Ener, Maraia E et al. (2016) Computational design of a homotrimeric metalloprotein with a trisbipyridyl core. Proc Natl Acad Sci U S A 113:15012-15017
Pearson, Aaron D; Mills, Jeremy H; Song, Yifan et al. (2015) Transition states. Trapping a transition state in a computationally designed protein bottle. Science 347:863-867
Mills, Jeremy H; Khare, Sagar D; Bolduc, Jill M et al. (2013) Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy. J Am Chem Soc 135:13393-9