In this article we extend the Iterative Protein Redesign and Optimization (IPRO) framework for the design of protein libraries with targeted ligand specificity. Mutations that minimize the binding energy with the desired ligand are identified. At the same time explicit constraints are introduced that maintain the binding energy for all decoy ligands above a threshold necessary for successful binding. The proposed framework is demonstrated by computationally altering the effector binding specificity of the bacterial transcriptional regulatory protein AraC, belonging to the AraC/XylS family of transcriptional regulators for different unnatural ligands. The obtained results demonstrate the importance of systematically suppressing the binding energy for competing ligands. Pinpointing a small set of mutations within the binding pocket greatly improves the difference in binding energies between targeted and decoy ligands, even when they are very similar.
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