Predicting hydration Gibbs energies of alkyl-aromatics using molecular simulation : a comparison of current force fields and the development of a new parameter set for accurate solvation data

Garrido, Nuno M. and Jorge, Miguel and Queimada, Antonio J. and Gomes, Jose R. B. and Economou, Ioannis G. and Macedo, Eugenia A. (2011) Predicting hydration Gibbs energies of alkyl-aromatics using molecular simulation : a comparison of current force fields and the development of a new parameter set for accurate solvation data. Physical Chemistry Chemical Physics, 13 (38). pp. 17384-17394. ISSN 1463-9076 (https://doi.org/10.1039/c1cp21245a)

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Abstract

The Gibbs energy of hydration is an important quantity to understand the molecular behavior in aqueous systems at constant temperature and pressure. In this work we review the performance of some popular force fields, namely TraPPE, OPLS-AA and Gromos, in reproducing the experimental Gibbs energies of hydration of several alkyl-aromatic compounds-benzene, mono-, di- and tri-substituted alkylbenzenes-using molecular simulation techniques. In the second part of the paper, we report a new model that is able to improve such hydration energy predictions, based on Lennard Jones parameters from the recent TraPPE-EH force field and atomic partial charges obtained from natural population analysis of density functional theory calculations. We apply a scaling factor determined by fitting the experimental hydration energy of only two solutes, and then present a simple rule to generate atomic partial charges for different substituted alkyl-aromatics. This rule has the added advantages of eliminating the unnecessary assumption of fixed charge on every substituted carbon atom and providing a simple guideline for extrapolating the charge assignment to any multi-substituted alkyl-aromatic molecule. The point charges derived here yield excellent predictions of experimental Gibbs energies of hydration, with an overall absolute average deviation of less than 0.6 kJ mol(-1). This new parameter set can also give good predictive performance for other thermodynamic properties and liquid structural information.