Refined models of coordination between Al3+/Mg2+ and enzyme in molecular dynamics simulation in terms of ABEEM polarizable force field.
J Mol Graph Model
; 114: 108190, 2022 07.
Article
en En
| MEDLINE
| ID: mdl-35468452
ABSTRACT
MFX (AlF30, AlF4- and MgF3-) as transition state analogues of phosphoryl transfer enzymes (enzyme-MFX-TSAs) is of great significance for study of the catalytic mechanism of phosphoryl transfer enzymes. Bonded model and non-bonded model based on the ABEEM polarizable force field (ABEEM PFF) are developed and applied to study the coordination of enzyme-MFX-TSAs. The bond stretching of the bond containing metal is simulated by Morse potential energy function, because the change of chemical bond is described more accurately in a large range. The charge distribution of the system is distributed to multiple-charge-sites, including atomic site, σ bond site, π bond site and lone pair electron site. Partial charge can fluctuate according to the surrounding environment and molecular conformation. The reasonable charge distribution of 68 model molecules can be obtained, and the energy minimizations are performed in vacuum. Then, with the same parameters the charge distribution and the charge transfer of four complexes are obtained, and the energy minimization and molecular dynamics simulation in NVT ensemble are carried out in vacuum and explicit water solution. The results verify the correctness, rationality and transferability of the new parameters of ABEEM PFF, and the bonded model simulates more reasonable charge distribution and geometry. The parameters determined in this paper make up the blank of the parameters of MFX and phosophoryl transfer enzymes containing Mg2+. The development of ABEEM PFF provides a refined tool for MFX-TSAs to study the catalytic mechanism of phosphoryl transfer enzymes.
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Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Electrones
/
Simulación de Dinámica Molecular
Idioma:
En
Revista:
J Mol Graph Model
Asunto de la revista:
BIOLOGIA MOLECULAR
Año:
2022
Tipo del documento:
Article