Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions

Xian-Li Jiang, Rey P. Dimas, Clement T. Y. Chan () and Faruck Morcos ()
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Xian-Li Jiang: The University of Texas at Dallas
Rey P. Dimas: The University of Texas at Tyler
Clement T. Y. Chan: University of North Texas
Faruck Morcos: The University of Texas at Dallas

Nature Communications, 2021, vol. 12, issue 1, 1-8

Abstract: Abstract Genetic sensors with unique combinations of DNA recognition and allosteric response can be created by hybridizing DNA-binding modules (DBMs) and ligand-binding modules (LBMs) from distinct transcriptional repressors. This module swapping approach is limited by incompatibility between DBMs and LBMs from different proteins, due to the loss of critical module-module interactions after hybridization. We determine a design strategy for restoring key interactions between DBMs and LBMs by using a computational model informed by coevolutionary traits in the LacI family. This model predicts the influence of proposed mutations on protein structure and function, quantifying the feasibility of each mutation for rescuing hybrid repressors. We accurately predict which hybrid repressors can be rescued by mutating residues to reinstall relevant module-module interactions. Experimental results confirm that dynamic ranges of gene expression induction were improved significantly in these mutants. This approach enhances the molecular and mechanistic understanding of LacI family proteins, and advances the ability to design modular genetic parts.

Date: 2021
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DOI: 10.1038/s41467-021-25851-6

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