Hydrotropy: binding models vs. statistical thermodynamics.

Area of Science:

• Physical Chemistry
• Chemical Thermodynamics
• Solution Chemistry

Background:

• Hydrophobic drugs often require hydrotropes to increase solubility.
• Previous work identified preferential drug-hydrotrope association as a key factor in enhanced solubility.
• Understanding the molecular basis of drug-hydrotrope interactions is crucial for developing effective solubilization strategies.

Purpose of the Study:

• To re-evaluate the molecular mechanisms underlying drug solubilization by hydrotropes.
• To investigate the role of solvation numbers and binding models in drug-hydrotrope interactions.
• To propose a revised theoretical framework for understanding hydrotropic solubilization.

Main Methods:

• Application of rigorous statistical thermodynamic theory, specifically fluctuation solution theory (originated by Kirkwood and Buff).
• Analysis of solvation numbers and excess solvation numbers in drug-hydrotrope-water systems.
• Comparison of theoretical predictions with existing stoichiometric binding models.

Main Results:

• The excess solvation number, representing the net change in solvent molecules around a solute, is identified as the critical parameter for describing solute-hydrotrope interactions.
• Stoichiometric binding models are insufficient to capture the complexities of drug-hydrotrope interactions.
• Long-range solvation structures significantly influence solute-hydrotrope binding, a factor not adequately addressed by traditional models.

Conclusions:

• The paradigm for understanding hydrotropic solubilization needs revision, shifting focus from coordination numbers to excess solvation numbers.
• Accurate molecular-level understanding of drug-hydrotrope interactions necessitates considering long-range solvation effects.
• This revised theoretical approach provides a more robust framework for predicting and optimizing drug solubility in hydrotropic solutions.