Computational redesign of metalloenzymes for catalyzing new reactions

Abstract

The ability to design novel activities in existing metalloenzyme active sites is a stringent test of our understanding of enzyme mechanisms, sheds light on enzyme evolution, and would have many practical applications. Here, we describe a computational method in the context of the macromolecular modeling suite Rosetta to repurpose active sites containing metal ions for reactions of choice. The required inputs for the method are a model of the transition state(s) for the reaction and a set of crystallographic structures of proteins containing metal ions. The coordination geometry associated with the metal ion (Zn(2+), for example) is automatically detected and the transition state model is aligned to the open metal coordination site(s) in the protein. Additional interactions to the transition state model are made using RosettaMatch and the surrounding amino acid side chain identities are optimized for transition state stabilization using RosettaDesign. Validation of the design is performed using docking and molecular dynamics simulations, and candidate designs are generated for experimental validation. Computational metalloenzyme repurposing is complementary to directed evolution approaches for enzyme engineering and allows large jumps in sequence space to make concerted sequence and structural changes for introducing novel enzymatic activities and specificities.