Using turnover dynamics to redesign KARI for improved catalytic activity.

Abstract

Enzymes represent some of the most efficient and precise catalysts known. However, their adoption for specific applications can be hampered by our limited ability to rationally tune and tailor catalytic function, particularly when seeking increased activity, but also when modifying specificity and selectivity. One example of this challenge is in the redesign of ketol-acid reductoisomerase (KARI), whose activity on a native substrate is sometimes the rate-limiting step in proposed industrial isobutanol production pathways. While traditional structure-based computational enzyme redesign strategies would typically focus on the enzyme-bound ground state and transition state, we postulated that additionally treating the underlying dynamics of complete turnover events that connect and pass through both states could further elucidate the structural properties affecting catalysis and help identify mutations that lead to increased catalytic activity.