Computational Optimization of Electric Fields for Improving Catalysis of a Designed Kemp Eliminase

Abstract

Here we report a computational method to improve efficiency of a de novo designed Kemp eliminase enzyme KE15, by identifying mutations that enhance electric fields and chemical positioning of the substrate that contribute to free energy stabilization of the transition state. Starting from the design that has a kcat/KM of 27 M–1 s–1, the most improved variant introduced four computationally targeted mutations to yield a kcat/KM of 403 M–1 s–1, with almost all of the enzyme improvement realized through a 43-fold improvement in kcat, indicative of a direct impact on the chemical step. This work raises the prospect of computationally designing enzymes that achieve better efficiency with more minimal experimental intervention using electric field optimization as guidance.