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Coarse-Grained Force Field for Polyethylene Oxide and Polyethylene Glycol Aqueous Solutions Based on a Polarizable Water Model.

Junjie SongMing MaYi DongMingwei WanWei-Hai FangLianghui Gao
Published in: Journal of chemical theory and computation (2023)
A new, accurate and transferable coarse-grained (CG) force field (FF) for polyethylene oxide (PEO) and polyethylene glycol (PEG) aqueous solutions based on a polarizable CG water (PCGW) model is developed in this work. A PCGW bead, which represents four water molecules, is modeled as two charged dummy particles connected by two constrained bonds to a central neutral particle; a PEO or PEG oligomer is modeled as a chain with repeated middle beads (PEOM) representing diether groups and two terminal beads (PEOT or PEGT) of a different type compared to PEOM. To describe nonbonded van der Waals interactions, a piecewise Morse potential with four tunable parameters is used. The force parameters are automatically and rigorously optimized by a meta-multilinear interpolation parameterization (meta-MIP) algorithm to simultaneously match multiple thermodynamic properties, including the density, heat of vaporization, vapor-liquid interfacial tension, and solvation free energy of the pure PEO or PEG oligomer bulk system as well as the mixing density and hydration free energy of the oligomer/water binary mixture. Additional thermodynamic and structural properties for longer PEO and PEG polymer aqueous solutions, such as the self-diffusion coefficient, radius of gyration, and end-to-end distance, are predicted to test the accuracy and transferability of this new CG FF. Based on the PCGW model, the presented FF optimization algorithm and strategy can be extended to more complex polyelectrolytes and surfactants.
Keyphrases
  • molecular dynamics simulations
  • molecular dynamics
  • drug delivery
  • ionic liquid
  • single molecule
  • machine learning
  • deep learning
  • computed tomography
  • magnetic resonance
  • magnetic resonance imaging
  • climate change