Computational methodology for solubility prediction: Application to the sparingly soluble solutes.

Lunna Li,Daan Frenkel,Tim Totton

doi:10.1063/1.4983754

Lunna Li, Daan Frenkel + Show 1 more

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https://doi.org/10.1063/1.4983754

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Abstract

The solubility of a crystalline substance in the solution can be estimated from its absolute solid free energy and excess solvation free energy. Here, we present a numerical method, which enables convenient solubility estimation of general molecular crystals at arbitrary thermodynamic conditions where solid and solution can coexist. The methodology is based on standard alchemical free energy methods, such as thermodynamic integration and free energy perturbation, and consists of two parts: (1) systematic extension of the Einstein crystal method to calculate the absolute solid free energies of molecular crystals at arbitrary temperatures and pressures and (2) a flexible cavity method that can yield accurate estimates of the excess solvation free energies. As an illustration, via classical Molecular Dynamic simulations, we show that our approach can predict the solubility of OPLS-AA-based (Optimized Potentials for Liquid Simulations All Atomic) naphthalene in SPC (Simple Point Charge) water in good agreement with experimental data at various temperatures and pressures. Because the procedure is simple and general and only makes use of readily available open-source software, the methodology should provide a powerful tool for universal solubility prediction.

Highlights

Solubility is an important concept in many areas of science
We have developed a robust computational methodology to enable the solubility prediction of general crystalline solutes
The method is based on the equality of the chemical potentials of the solute in coexisting solution and solid phases

Summary

Introduction

Solubility is an important concept in many areas of science. For the development of pharmaceuticals, it is crucial to know the solubility of drugs, as this influences bioavailability. Organic/inorganic compounds with low aqueous solubility can form unwanted deposits (scaling/fouling) to cause blockages.. Organic/inorganic compounds with low aqueous solubility can form unwanted deposits (scaling/fouling) to cause blockages.4–7 These are but two examples to illustrate that it is extremely important to understand the precipitation of common materials under normal conditions and predict their solubility under conditions for which experimental information is difficult to obtain. It would be helpful to have a generic tool to predict solubility, which uses standard, open-source software. On the whole, simulationbased predictions of solubility are not widely used We argue that this is due to the fact that generic, open-source tools are lacking. As we argue below, the prediction of solubility should be a standard test of new force fields.

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