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Comparative QM/MM study on the inhibition mechanism of β-Hydroxynorvaline to Threonyl-tRNA synthetase.

Authors :
Aboelnga MM
Gauld JW
Source :
Journal of molecular graphics & modelling [J Mol Graph Model] 2022 Sep; Vol. 115, pp. 108224. Date of Electronic Publication: 2022 May 23.
Publication Year :
2022

Abstract

β-Hydroxynorvaline (βHNV) is unnatural amino acid structurally identical to the threonine amino acid with branched ethyl group instead of threonine's methyl. It is a known competitive inhibitor that readily bind to Threonyl-tRNA synthetase's (ThrRS) catalytic site and blocks its function. In this work, we utilized a combination of Molecular Dynamics simulation (MD) and Quantum Mechanics/Molecular Mechanics (QM/MM) methodologies to provide mechanistic insights into its inhibition reaction for ThrRS. Due to the presence of Zn(II) with its Lewis acidity character, only the ionized form of βHNV gives an enzymatically feasible energy barrier. Furthermore, in consistence with the homochirality behavior of this active site, we observed only one conformation of βHNV that could be acylated in the active site of ThrRS. Considering these new findings together with the recent search for new antibacterial agents, our findings should guide pharmaceutical scientists with further knowledge regarding the chemical nature of this drug. Moreover, benchmarking analysis of the utilized DFT functional has also been performed to identify the impact of various DFT functionals on representing the geometry and kinetics of our system. Notably, our Zn(II) containing chemical models are found to be responsive to the %HF contribution included together with the dispersion correction. Importantly, the BP86(0%HF)-D3 functional is found to display the greatest impact on the rate-limiting step kinetically. The crucial role played by Zn(II) is further enriched when its mutation with the chemically similar Cd(II) led to dramatic difference via obtaining less feasible reaction mechanism from thermodynamic and kinetic perspectives.<br /> (Copyright © 2022 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1873-4243
Volume :
115
Database :
MEDLINE
Journal :
Journal of molecular graphics & modelling
Publication Type :
Academic Journal
Accession number :
35636339
Full Text :
https://doi.org/10.1016/j.jmgm.2022.108224