posted on 2023-09-11, 04:51authored byAntonin Kunka, Sérgio M. Marques, Martin Havlasek, Michal Vasina, Nikola Velatova, Lucia Cengelova, David Kovar, Jiri Damborsky, Martin Marek, David Bednar, Zbynek Prokop
Thermostability is
an essential requirement for the use of enzymes
in the bioindustry. Here, we compare different protein stabilization
strategies using a challenging target, a stable haloalkane dehalogenase
DhaA115. We observe better performance of automated stabilization
platforms FireProt and PROSS in designing multiple-point mutations
over the introduction of disulfide bonds and strengthening the intra-
and the inter-domain contacts by in silico saturation
mutagenesis. We reveal that the performance of automated stabilization
platforms was still compromised due to the introduction of some destabilizing
mutations. Notably, we show that their prediction accuracy can be
improved by applying manual curation or machine learning for the removal
of potentially destabilizing mutations, yielding highly stable haloalkane
dehalogenases with enhanced catalytic properties. A comparison of
crystallographic structures revealed that current stabilization rounds
were not accompanied by large backbone re-arrangements previously
observed during the engineering stability of DhaA115. Stabilization
was achieved by improving local contacts including protein–water
interactions. Our study provides guidance for further improvement
of automated structure-based computational tools for protein stabilization.