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

Area of Science:

• Computational chemistry
• Physical chemistry
• Materials science

Background:

• Accurate prediction of crystalline substance solubility is crucial for chemical and pharmaceutical industries.
• Current methods often lack generality or require extensive computational resources.
• Estimating solubility relies on calculating absolute solid free energy and excess solvation free energy.

Purpose of the Study:

• To develop a convenient numerical method for estimating the solubility of general molecular crystals.
• To enable solubility predictions under arbitrary thermodynamic conditions where solid and solution coexist.
• To provide a powerful and universal tool for solubility prediction.

Main Methods:

• Utilizes standard alchemical free energy methods, including thermodynamic integration and free energy perturbation.
• Employs an extended Einstein crystal method for calculating absolute solid free energies at various temperatures and pressures.
• Incorporates a flexible cavity method for accurate excess solvation free energy estimations.
• Employs classical Molecular Dynamic simulations for validation.

Main Results:

• The proposed method successfully predicts the solubility of naphthalene in water.
• Results show good agreement with experimental data across different temperatures and pressures.
• Demonstrates the applicability of the method for OPLS-AA based naphthalene and SPC water.

Conclusions:

• The presented numerical method offers a simple, general, and powerful approach for universal solubility prediction.
• The methodology leverages readily available open-source software, enhancing accessibility.
• This approach facilitates accurate solubility estimations for molecular crystals under diverse conditions.