Engineered regulatory proteins enable customized genetic selections and permit targeted gene transcription for applications in metabolic engineering and biosensing. Use of regulatory proteins for reporting or controlling metabolic pathways in response to specific metabolites requires a highly selective protein-effector interaction that is not influenced by similar compounds, such as metabolic precursors or undesired co-products. We have developed dual selection strains and FACS-based screens to engineer the effector specificity of AraC regulatory protein, which naturally regulates the ara operon in response to L-arabinose in E. coli. L-Arabinose-producing enzymes and enzyme libraries were tested to validate the use of this system for reporting in vivo metabolite production and identifying strains with improved activity.

A computational framework was also developed to guide the redesign of the AraC binding pocket. Our binding models accurately reflect the relative strengths with which wild-type AraC binds various compounds, and optimization methods have predicted mutagenesis strategies resulting in improved binding selectivity for unnatural ligands such as D-arabinose and cis-verbenol. Mutations that minimize the binding energy with the desired ligand are identified, while at the same time explicit constraints are introduced that maintain the binding energy for all decoy ligands above a threshold necessary for successful binding. This poster will highlight the construction and evaluation of our selection and screening systems, computational results, and experimental progress toward the design of AraC variants with novel effector specificity.

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