Login / Signup

Molecular Dynamics Studies of the Ho(III) Aqua-tris(dibenzoylmethane) Complex: Role of Water Dynamics.

Takahiro OhkuboNao KomiyamaHyuma MasuKeiki KishikawaMichinari Kohri
Published in: Inorganic chemistry (2023)
The seven-coordinate Ho(III) aqua-tris(dibenzoylmethane)(DBM) complex, referred to as Ho-(DBM) 3 ·H 2 O, was first reported in the late 1960s. It has a threefold symmetric structure, with Ho at the center of three dibenzoylmethane ligands and hydrogen-bonded water to ligands. It is considered that the hydrogen bonds between the water molecule and the ligands surrounding Ho play an important role in the formation of its symmetrical structure. In this work, we developed new force-field parameters for classical molecular dynamics (CMD) simulations to theoretically elucidate the structure and dynamics of Ho-(DBM) 3 ·H 2 O. To develop the force field, structural optimization and molecular dynamics were performed on the basis of ab initio calculations using the plane-wave pseudopotential method. The force-field parameters for CMD were then optimized to reproduce the data obtained from ab initio calculations. Validation of the developed force field showed good agreement with the experimental crystalline structure and ab initio data. The vibrational properties of water in Ho-(DBM) 3 ·H 2 O were investigated by comparison with bulk liquid water. The vibrational motion of water was found to have a characteristic mode originating from stationary rotational motion along the c -axis of Ho(III) aqua-tris(dibenzoylmethane). Contrary to expectations, the hydrogen-bond dynamics of water in Ho-(DBM) 3 ·H 2 O were found to be almost equivalent to those of bulk liquid water except for librational motion. This development route for force-field parameters for CMD and the establishment of water dynamics can advance the understanding of water-coordinated metal complexes with high coordination numbers such as Ho-(DBM) 3 ·H 2 O.
Keyphrases
  • molecular dynamics
  • density functional theory
  • pi k akt
  • single molecule
  • molecular dynamics simulations
  • electronic health record
  • machine learning
  • cell proliferation
  • deep learning
  • data analysis