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@ARTICLE{ElHarrar:894012,
author = {El Harrar, Till and Frieg, Benedikt and Davari, Mehdi D.
and Jaeger, Karl-Erich and Schwaneberg, Ulrich and Gohlke,
Holger},
title = {{A}queous ionic liquids redistribute local enzyme stability
via long-range perturbation pathways},
journal = {Computational and structural biotechnology journal},
volume = {19},
issn = {2001-0370},
address = {Gotenburg},
publisher = {Research Network of Computational and Structural
Biotechnology (RNCSB)},
reportid = {FZJ-2021-02979},
pages = {4248-4264},
year = {2021},
abstract = {Ionic liquids (IL) and aqueous ionic liquids (aIL) are
attractive (co-)solvents for biocatalysis due to their
unique properties. On the other hand, the incubation of
enzymes in IL or aIL often reduces enzyme activity. Recent
studies proposed various aIL-induced effects to explain the
reduction, classified as direct effects, e.g., local
dehydration or competitive inhibition, and indirect effects,
e.g., structural perturbations or disturbed catalytic site
integrity. However, the molecular origin of indirect effects
has largely remained elusive. Here we show by multi-μs long
molecular dynamics simulations, free energy computations,
and rigidity analyses that aIL favorably interact with
specific residues of Bacillus subtilis Lipase A (BsLipA) and
modify the local structural stability of this model enzyme
by inducing long-range perturbations of noncovalent
interactions. The perturbations percolate over neighboring
residues and eventually affect the catalytic site and the
buried protein core. Validation against a complete
experimental site saturation mutagenesis library of BsLipA
(3620 variants) reveals that the residues of the
perturbation pathways are distinguished sequence positions
where substitutions highly likely yield significantly
improved residual activity. Our results demonstrate that
identifying these perturbation pathways and specific IL
ion-residue interactions there effectively predicts focused
variant libraries with improved aIL tolerance.},
cin = {JSC / IBI-7 / IMET / IBG-4 / NIC},
ddc = {570},
cid = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IBI-7-20200312 /
I:(DE-Juel1)IMET-20090612 / I:(DE-Juel1)IBG-4-20200403 /
I:(DE-Juel1)NIC-20090406},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / 2171 - Biological
and environmental resources for sustainable use (POF4-217) /
Forschergruppe Gohlke $(hkf7_20200501)$ / CSD-SSD - Center
for Simulation and Data Science (CSD) - School for
Simulation and Data Science (SSD) (CSD-SSD-20190612)},
pid = {G:(DE-HGF)POF4-5111 / G:(DE-HGF)POF4-2171 /
$G:(DE-Juel1)hkf7_20200501$ / G:(DE-Juel1)CSD-SSD-20190612},
typ = {PUB:(DE-HGF)16},
pubmed = {34429845},
UT = {WOS:000692610700009},
doi = {10.1016/j.csbj.2021.07.001},
url = {https://juser.fz-juelich.de/record/894012},
}