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Abstract
Proteins function by interacting with biomolecules ranging from small molecules, nucleic acids, and other proteins to control nearly all biological processes. Uncovering how sequence changes perturb the specificity and stability of these interactions is essential to understand how proteins naturally evolve function and how we can redesign proteins for synthetic applications. Tools to explore sequence-function landscapes include computational tools, such as ancestral sequence reconstruction and Rosetta design, and deep mutational scanning. Resurrecting ancient proteins with ancestral sequence reconstruction advantageously narrows the sequence space search to important functional transitions, overcomes unpredictable epistatic interactions, and allows protein sequence-function relationships to be assayed through natural evolutionary time scales. Here, we reconstruct and characterize the comprehensive phylogenic tree of the LacI/GalR family, including all ancestral intermediates dating back across a 3-billionyear history, to uncover how DNA recognition evolved within this family. We combine results from this evolutionary screen with a systematic exploration of the local sequence space surrounding the lac repressor using deep mutational scanning to uncover the role of every position of the DNA-binding domain for lac operator recognition. Our results reveal a rugged DNA-binding landscape that disfavors potentially adverse regulatory crosstalk. While ancestral protein reconstruction and deep mutational scanning are powerful tools to map sequence-function relationships of natural proteins, computational design enables the design of new functions. Using computational design, I developed a strategy grounded in fundamental protein biophysics to tune the strength of protein-protein interactions to optimize the reconstitution propensity of split proteins, redesigned protein-DNA specificity of a global transcription regulator, sigma70, to activate transcription from 5 orthogonal promoter targets, and redesigned ligand specificity of the lac repressor through computational design of the binding pocket for small molecule biosensing.
