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@article{1632601,
author = {Marques, Sérgio Manuel and Bednář, David and Damborský, Jiří},
article_location = {LAUSANNE},
article_number = {JAN 2019},
doi = {http://dx.doi.org/10.3389/fchem.2018.00650},
keywords = {unbinding kinetics; protein engineering; molecular dynamics; metadynamics; adaptive sampling; CaverDock},
language = {eng},
issn = {2296-2646},
journal = {FRONTIERS IN CHEMISTRY},
title = {Computational Study of Protein-Ligand Unbinding for Enzyme Engineering},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331733/},
volume = {6},
year = {2019}
}
TY - JOUR
ID - 1632601
AU - Marques, Sérgio Manuel - Bednář, David - Damborský, Jiří
PY - 2019
TI - Computational Study of Protein-Ligand Unbinding for Enzyme Engineering
JF - FRONTIERS IN CHEMISTRY
VL - 6
IS - JAN 2019
SP - 1-15
EP - 1-15
PB - FRONTIERS MEDIA SA
SN - 22962646
KW - unbinding kinetics
KW - protein engineering
KW - molecular dynamics
KW - metadynamics
KW - adaptive sampling
KW - CaverDock
UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331733/
L2 - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331733/
N2 - The computational prediction of unbinding rate constants is presently an emerging topic in drug design. However, the importance of predicting kinetic rates is not restricted to pharmaceutical applications. Many biotechnologically relevant enzymes have their efficiency limited by the binding of the substrates or the release of products. While aiming at improving the ability of our model enzyme haloalkane dehalogenase DhaA to degrade the persistent anthropogenic pollutant 1,2,3-trichloropropane (TCP), the DhaA31 mutant was discovered. This variant had a 32-fold improvement of the catalytic rate toward TCP, but the catalysis became rate-limited by the release of the 2,3-dichloropropan-1-ol (DCP) product from its buried active site. Here we present a computational study to estimate the unbinding rates of the products from DhaA and DhaA31. The metadynamics and adaptive sampling methods were used to predict the relative order of kinetic rates in the different systems, while the absolute values depended significantly on the conditions used (method, force field, and water model). Free energy calculations provided the energetic landscape of the unbinding process. A detailed analysis of the structural and energetic bottlenecks allowed the identification of the residues playing a key role during the release of DCP from DhaA31 via the main access tunnel. Some of these hot-spots could also be identified by the fast CaverDock tool for predicting the transport of ligands through tunnels. Targeting those hot-spots by mutagenesis should improve the unbinding rates of the DCP product and the overall catalytic efficiency with TCP.
ER -
MARQUES, Sérgio Manuel, David BEDNÁŘ and Jiří DAMBORSKÝ. Computational Study of Protein-Ligand Unbinding for Enzyme Engineering. \textit{FRONTIERS IN CHEMISTRY}. LAUSANNE: FRONTIERS MEDIA SA, 2019, vol.~6, JAN 2019, p.~1-15. ISSN~2296-2646. Available from: https://dx.doi.org/10.3389/fchem.2018.00650.
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