The ability to genetically incorporate non-canonical amino acids (ncAAs) in a site-specific manner has revolutionized the field of protein biochemistry by providing novel tools for studying and engineering proteins and has had a pronounced influence in several biomedical fields including regulating protein function, in vivo imaging of proteins, and designing novel therapeutics. In this technology an orthogonal amino acyl-tRNA synthetase and tRNA pair (RS/tRNA) that is evolved for new ncAA structure is added to the cell. Despite the advantages offered by ncAA incorporation, the practical limits on the size of the libraries for RS evolution restrict the number of residues that can be mutated at each round. Hence, several beneficial interactions in the first shell and all second shell interactions are overlooked. Therefore, selected ncAA-RSs don't match the catalytic constants of wild type translation resulting in low ncAA-protein expression yield and lack of selectivity under many protein expression conditions. Rosetta computational design program offers an exciting novel option for overcoming this key limitation in genetic code expansion. Tetrazine-based amino acids (Tet-ncAAs) offer extremely fast and robust bioorthogonal chemistry for site specific labeling of proteins and therefore will be an ideal model system for Rosetta based optimization. Fast protein bioorthogonal ligations are being implemented in biomedical research and material science for many applications including in vivo imaging, probing protein function, drug delivery, and protein-polymer hybrids. Engineering Tet-ncAA-RSs is uniquely challenging in addition to the above-mentioned reasons because the more reactive Tet-ncAAs add additional stress to selection methods. In this proposal, I will use Rosetta to design better Tet-RSs and to obtain structural insights into the residues important for binding. This information guides the generation of ?smart libraries? with a higher chance of success via screening lesser variants to overcome the size limitation. In parallel, I will also improve upon current functionalities in Rosetta by designing novel protocols and enhancing score functions. This enhancements and additions will be publicly available. The design of superior sets of RSs for efficient and selective incorporation of Tet-ncAAs provides scientists with an ideal tool for site-specific labeling of proteins in vivo in a fast and bioorthogonal manner. This ability is of unequivocal importance for many applications in biomedical research. The proposed strategy can be generalized to other ncAAs or to address other issues in the field of genetic code expansion. It will also lay the foundations of a lasting collaboration between the fields of computational protein design and genetic code expansion.

Public Health Relevance

The goal of this proposal is to advance the field of genetic code expansion using a novel application of computational protein design. Specifically, I will use Rosetta to engineer tRNA/tRNA synthetase orthogonal pairs with superior yields of incorporation of a series of tetrazine-based amino acids for fast and clean in vivo bioorthogonal reactions that can be used in several health related applications such as imaging, fluorescent labeling, and targeted drug delivery. The computational strategy can be generalized to other non-canonical amino acids or to address other challenges in the field of genetic code expansion.

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)
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Ravichandran, Veerasamy
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University of Washington
Schools of Medicine
United States
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Hosseinzadeh, Parisa; Bhardwaj, Gaurav; Mulligan, Vikram Khipple et al. (2017) Comprehensive computational design of ordered peptide macrocycles. Science 358:1461-1466