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Efficient Osmotic Pressure Calculations Using Coarse-Grained Molecular Simulations.

Jörg SauterAndrea Grafmüller
Published in: Journal of chemical theory and computation (2018)
Osmotic pressure data is increasingly used to parametrize all-atom simulation Force Fields (FFs), leading to large computational cost for larger molecules. Here, we show that the osmotic pressure can be calculated precisely using transferable coarse-grained FFs obtained from short atomistic simulations using an inhomogeneously regularized coarse-graining procedure. This is demonstrated for carbohydrates, where compared to the equivalent atomistic system, an increase of the computational efficiency by a factor of ≈500 is achieved.
Keyphrases
  • molecular dynamics
  • density functional theory
  • molecular dynamics simulations
  • single molecule
  • electronic health record
  • machine learning
  • big data
  • deep learning