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Neural Network Corrections to Intermolecular Interaction Terms of a Molecular Force Field Capture Nuclear Quantum Effects in Calculations of Liquid Thermodynamic Properties.

Igor V KurnikovLeonid PereyaslavetsGanesh KamathSerzhan N SakipovEkaterina VoroninaOleg ButinAlexey IllarionovIgor LeontyevGrzegorz NawrockiMikhail DarkhovskiyMichael OlevanovIlya IvahnenkoYuChun ChenChristopher B LockMichael LevittRoger D KornbergBoris Fain
Published in: Journal of chemical theory and computation (2024)
We incorporate nuclear quantum effects (NQE) in condensed matter simulations by introducing short-range neural network (NN) corrections to the ab initio fitted molecular force field ARROW. Force field NN corrections are fitted to average interaction energies and forces of molecular dimers, which are simulated using the Path Integral Molecular Dynamics (PIMD) technique with restrained centroid positions. The NN-corrected force field allows reproduction of the NQE for computed liquid water and methane properties such as density, radial distribution function (RDF), heat of evaporation (HVAP), and solvation free energy. Accounting for NQE through molecular force field corrections circumvents the need for explicit computationally expensive PIMD simulations in accurate calculations of the properties of chemical and biological systems. The accuracy and locality of pairwise NN NQE corrections indicate that this approach could be applicable to complex heterogeneous systems, such as proteins.
Keyphrases
  • molecular dynamics
  • single molecule
  • density functional theory
  • neural network
  • monte carlo
  • molecular dynamics simulations
  • mass spectrometry
  • high resolution