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

Miguel Jorge, Nuno M. Garrido, Carlos J. V. Simões, Cândida G. Silva, Rui M. M. Brito

Research output: Contribution to journalArticle

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21 Downloads (Pure)

Abstract

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 in order 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.
Original languageEnglish
Pages (from-to)346–358
Number of pages13
JournalJournal of Computational Chemistry
Volume38
Issue number6
Early online date28 Dec 2016
DOIs
Publication statusPublished - 5 Mar 2017

Fingerprint

Molecular Simulation
Alkanes
Solvation
Paraffins
Free Energy
Force Field
Atoms
Testing
Lennard-Jones
Molecular Dynamics Simulation
Free energy
Adjustment
Thermodynamics
Experimental Data
Model
Tend
Ring
Computing
Prediction
Gibbs free energy

Keywords

  • solubility
  • molecular simulation
  • hydrocarbons
  • non-polar
  • free energy
  • united-atom force fields
  • hydrophobic
  • cyclic alkanes

Cite this

Jorge, Miguel ; Garrido, Nuno M. ; Simões, Carlos J. V. ; Silva, Cândida G. ; Brito, Rui M. M. / Predicting hydrophobic solvation by molecular simulation : 1. testing united-atom alkane models. In: Journal of Computational Chemistry . 2017 ; Vol. 38, No. 6. pp. 346–358.
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abstract = "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 in order 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.",
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author = "Miguel Jorge and Garrido, {Nuno M.} and Sim{\~o}es, {Carlos J. V.} and Silva, {C{\^a}ndida G.} and Brito, {Rui M. M.}",
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Predicting hydrophobic solvation by molecular simulation : 1. testing united-atom alkane models. / Jorge, Miguel; Garrido, Nuno M.; Simões, Carlos J. V.; Silva, Cândida G.; Brito, Rui M. M.

In: Journal of Computational Chemistry , Vol. 38, No. 6, 05.03.2017, p. 346–358.

Research output: Contribution to journalArticle

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AU - Brito, Rui M. M.

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