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

Miguel Jorge1, Nuno M Garrido2, Carlos J V Simões3,4

  • 1Department of Chemical and Process Engineering, University of Strathclyde, 75 Montrose Street, Glasgow, G1 1XJ, United Kingdom.

Journal of Computational Chemistry
|December 30, 2016
PubMed
Summary

This study tested united-atom force fields for alkane solvation. TraPPE performed best, though all models require adjustments for accurate predictions of larger alkanes.

Keywords:
force fieldfree energymolecular simulationnon-polarsolubility

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Area of Science:

  • Computational chemistry
  • Molecular modeling
  • Physical chemistry

Background:

  • Accurate prediction of hydrophobic solvation is crucial for understanding chemical processes.
  • United-atom force fields are widely used for simulating large molecular systems.
  • Evaluating force field performance for alkane solvation is essential for refining molecular simulations.

Purpose of the Study:

  • To systematically evaluate the performance of OPLS-UA, GROMOS, and TraPPE force fields.
  • To assess their accuracy in predicting the solvation of alkanes in alkanes.
  • To identify systematic deviations and areas for improvement in these force fields.

Main Methods:

  • Calculated Gibbs free energies of solvation for 52 solute/solvent pairs.
  • Employed Molecular Dynamics simulations and thermodynamic integration.
  • Utilized the IBERCIVIS volunteer computing platform for extensive simulations.

Main Results:

  • All force fields performed well for small alkanes (up to pentane).
  • Performance degraded systematically with increasing alkane size.
  • TraPPE showed the best overall performance, underpredicting solvation by ~6%.
  • GROMOS and OPLS-UA overpredicted solvation by ~13% and ~15%, respectively.
  • Specific parameters are needed for cyclic alkanes due to excluded volume.

Conclusions:

  • Existing united-atom force fields show systematic deviations for larger alkanes.
  • Adjustments to Lennard-Jones parameters are suggested for improved accuracy.
  • The TraPPE model offers the best balance for alkane solvation predictions among the tested models.