Rewiring Translation for Photocontrol and Haptens, and Computational Analysis

The objective of my Ph.D. study is to expand the unnatural amino acid (unAA) toolbox to genetically encode additional photocaging functional groups to achieve a precise control of proteins with light, to site-specifically label proteins with hapten moieties, and to further explore computational methods with an ultimate goal of using computers to design specific orthogonal aminoacyl-tRNA synthetases (aaRSes) for given unAAs.In this thesis, we show that cellular biochemical processes can be spatiotemporally manipulated by light-activatable protein-splicing inteins. We genetically encoded a photocaged cysteine and introduced the photocaged cysteine into a highly efficient Nostoc punctiforme (Npu) DnaE intein, which is capable of excising itself and subsequently splicing adjacent N- and C-terminal extein flanks to form a new truncated peptide. The resulting photocaged intein was inserted into a red fluorescent protein (RFP) mCherry and a human Src tyrosine kinase, and a light-induced photochemical reaction was able to reactivate the intein and trigger protein splicing. The genetically encoded photocaged intein is a general optogenetic tool, allowing effective photocontrol of primary structures and functions of proteins.Haptens, such as dinitrophenyl (DNP), are small molecules that induce strong immune responses when attached to proteins or peptides and, as such, have been exploited for diverse applications. In this thesis, we engineered a Methanosarcina barkeri pyrrolysyl-tRNA synthetase (mbPylRS) to genetically encode a DNP-containing unAA, N6-(2-(2,4-dinitrophenyl)acetyl)lysine (DnpK). This technique is a promising strategy for biological preparation of proteins containing site-specific DNP. This new capability is expected to find broad applications in biosensing, immunology, and therapeutics.The experimental procedure to derive orthogonal aaRSes/aminoacyl tRNAs, which typically involves several rounds of positive and negative selection, is laborious and time-consuming, and requires considerable expertise. It is often not trivial to derive orthogonal aaRSes for unAA substrates that are very different from the enzymes’ native substrates. In this thesis, we compared several computational algorithms to evaluate the binding energies of unAA and previously developed orthogonal aaRSes. We hope to use these results to guide future designing and development of new aaRSes, and to extend the capability of the genetic code expansion technology to many new unAAs