An empirical model for solvation based on surface site interaction points.

Area of Science:

• Computational chemistry
• Physical chemistry
• Molecular modeling

Background:

• Non-covalent interactions are crucial for molecular behavior.
• Quantifying these interactions, like hydrogen bonds, is essential for predicting properties such as solvation energy and partition coefficients.
• Existing methods may lack simplicity or broad applicability.

Purpose of the Study:

• To develop a rule-based method for assigning Surface Site Interaction Points (SSIPs) based on chemical structure.
• To parameterize this method using experimental data on hydrogen-bonded complexes and solvent partitioning.
• To create a simple, spreadsheet-implementable model for calculating solvation energies and partition coefficients.

Main Methods:

• A rule-based approach was developed to identify and assign SSIPs from molecular structures.
• The model was parameterized using experimental data for 1:1 hydrogen-bonded complexes in non-polar solvents.
• Solute partitioning between different solvents was also utilized for parameterization.

Main Results:

• The developed SSIP model accurately describes solute transfer between water and various organic solvents (overall RMSD of 1.4 kJ mol⁻¹ for 1713 data points).
• The model effectively captures the hydrophobic effect and the behavior of perfluorocarbon solvents.
• New descriptors were determined for organic solvents not previously accessible through direct H-bond studies.

Conclusions:

• The SSIP method provides a simple yet accurate way to quantify molecular interactions and predict solvation properties.
• This approach offers a valuable tool for computational and physical chemists, applicable across a wide range of solutes and solvents.
• The model's ability to describe complex phenomena like the hydrophobic effect highlights its utility in molecular modeling.