Enhancing a de novo enzyme activity by computationally-focused ultra-low-throughput screening.

ABSTRACT: Directed evolution has revolutionized protein engineering. Still, enzyme optimization by random library screening remains sluggish, in large part due to futile probing of mutations that are catalytically neutral and/or impair stability and folding. FuncLib is a novel approach which uses phylogenetic analysis and Rosetta design to rank enzyme variants with multiple mutations, on the basis of predicted stability. Here, we use it to target the active site region of a minimalist-designed, de novo Kemp eliminase. The similarity between the Michaelis complex and transition state for the enzymatic reaction makes this system particularly challenging to optimize. Yet, experimental screening of a small number of active-site variants at the top of the predicted stability ranking leads to catal

SUBMITTER: Risso VA 

PROVIDER: S-EPMC7407621 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature