Molecular Dynamics Simulation of Zinc Ion in Water with an ab Initio Based Neural Network Potential

Mingyuan Xu, Tong Zhu, John Zhang

Research output: Contribution to journalArticle

Abstract

An artificial neural network provides the possibility to develop molecular potentials with both the efficiency of the classical molecular mechanics and the accuracy of the quantum chemical methods. Here, we develop an ab initio based neural network potential (NN/MM-RESP) to perform molecular dynamics study of zinc ion in liquid water. In this approach, the interaction energy, atomic forces, and atomic charges of zinc ion and water molecules in the first solvent shell are described by a neural network potential trained with energies and forces generated from density functional calculations. The predicted energies and forces from the NN potential show excellent agreement with the quantum chemistry calculations. Using this approach, we carried out molecular dynamics simulation to study the hydration of zinc ion in water. The experimentally observed zinc-water radial distribution function, as well as the X-ray absorption near edge structure spectrum, is well-reproduced by the MD simulation. Comparison of the results with other theoretical calculations is provided, and important features of the present approach are discussed. The neural network approach used in this study can be applied to construct potentials to study solvation of other metal ions, and its salient features can shed light on the development of more accurate molecular potentials for metal ions in other environments such as proteins.

Original languageEnglish (US)
Pages (from-to)6587-6595
Number of pages9
JournalJournal of Physical Chemistry A
Volume123
Issue number30
DOIs
StatePublished - Aug 1 2019

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Molecular dynamics
Zinc
zinc
Ions
molecular dynamics
Neural networks
Water
Computer simulation
water
Metal ions
ions
simulation
Quantum chemistry
Molecular mechanics
metal ions
Solvation
X ray absorption
Nuclear energy
Hydration
Distribution functions

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry

Cite this

Molecular Dynamics Simulation of Zinc Ion in Water with an ab Initio Based Neural Network Potential. / Xu, Mingyuan; Zhu, Tong; Zhang, John.

In: Journal of Physical Chemistry A, Vol. 123, No. 30, 01.08.2019, p. 6587-6595.

Research output: Contribution to journalArticle

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