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Predicting hydrophobic solvation by molecular simulation: 1. Testing united-atom alkane models.

Miguel JorgeNuno M GarridoCarlos J V SimõesCândida G SilvaRui M M Brito
Published in: Journal of computational chemistry (2018)
We present a systematic test of the performance of three popular united-atom force fields-OPLS-UA, GROMOS and TraPPE-at predicting hydrophobic solvation, more precisely at describing the solvation of alkanes in alkanes. Gibbs free energies of solvation were calculated for 52 solute/solvent pairs from Molecular Dynamics simulations and thermodynamic integration making use of the IBERCIVIS volunteer computing platform. Our results show that all force fields yield good predictions when both solute and solvent are small linear or branched alkanes (up to pentane). However, as the size of the alkanes increases, all models tend to increasingly deviate from experimental data in a systematic fashion. Furthermore, our results confirm that specific interaction parameters for cyclic alkanes in the united-atom representation are required to account for the additional excluded volume within the ring. Overall, the TraPPE model performs best for all alkanes, but systematically underpredicts the magnitude of solvation free energies by about 6% (RMSD of 1.2 kJ/mol). Conversely, both GROMOS and OPLS-UA systematically overpredict solvation free energies (by ∼13% and 15%, respectively). The systematic trends suggest that all models can be improved by a slight adjustment of their Lennard-Jones parameters. © 2016 Wiley Periodicals, Inc.
Keyphrases
  • molecular dynamics simulations
  • ionic liquid
  • molecular dynamics
  • density functional theory
  • molecular docking
  • single molecule
  • machine learning
  • high throughput
  • aqueous solution
  • big data
  • single cell