Computational library design for increasing haloalkane dehalogenase stability

Abstract

We explored the use of a computational design framework for the stabilization of the haloalkane dehalogenase LinB. Energy calculations, disulfide bond design, molecular dynamics simulations, and rational inspection of mutant structures predicted many stabilizing mutations. Screening of these in small mutant libraries led to the discovery of seventeen point mutations and one disulfide bond that enhanced thermostability. Mutations located in or contacting flexible regions of the protein had a larger stabilizing effect than mutations outside such regions. The combined introduction of twelve stabilizing mutations resulted in a LinB mutant with a 23 °C increase in apparent melting temperature (Tm,app , 72.5 °C) and an over 200-fold longer half-life at 60 °C. The most stable LinB variants also displayed increased compatibility with co-solvents, thus allowing substrate conversion and kinetic resolution at much higher concentrations than with the wild-type enzyme.

Keywords: co-solvents; computational design; dehalogenases; directed evolution; thermostability; virtual screening.