Predicting Solubility of Small Molecules in Macromolecular Compounds for Nanomedicine Application from Atomistic Simulations

Abstract Solubility of small molecules in macromolecular compounds is of fundamental importance for a number of applications, including the growing field of nanomedicine. Here, approaches for in silico solubility predictions based on atomistic models are evaluated. A computationally efficient atomistic simulation procedure based on the concept of inherent structures is proposed for statistical sampling of polymer conformations. Comprehensive test simulations of several polymers and common solvents confirm the accuracy of the procedure for calculation of physicochemical properties such as cohesive energy densities, which along with the Hansen solubility parameters and the Flory–Huggins (FH) theory facilitate rapid, qualitative solubility predictions. However, the FH theory fails to model specific interactions such as hydrogen bonding. Therefore, more accurate predictions are obtained employing the perturbed hard sphere chain (PHSC) equation of state (EOS). As test case, aqueous poly(ethylene oxide) (PEO) solutions revealing strong hydrogen bonding are used. The physicochemical properties including the PEO‐water phase diagram calculated by the PHSC EOS show good agreement with experimental observations. Consequently, the combination of qualitative predictions using the FH theory for rapid prescreening with computationally more demanding parameterization of the PHSC EOS provides a promising tool for in silico solubility predictions with potential applications in nanomedicine.