MACROMOLECULE SOLVATION IN COMPLEX SOLUTIONS

Radial distribution functions are not appropriate to represent the structure of a solvent around a solute with many atoms, and a complex, non-spherical shape. Typical solutes of complex shape are proteins, nucleic acids, and polymers.
To address this limitation, Minimum-Distance Distribution Functions (MDDFs) offer a versatile and practical approach to representing solute-solvent interactions in molecules with arbitrarily complex sizes and geometries. Instead of calculating the density distribution function of a specific atom or the center-of-mass of the molecules, MDDFs determine the distribution function of the minimum distance between any solute and solvent atoms. This approach yields a size and shape-independent distribution that can be naturally interpreted in terms of molecular interactions.
ComplexMixtures.jl is a package specifically developed for studying the interactions between solutes and solvents in mixtures of molecules with complex shapes, utilizing MDDFs. These MDDFs can be further analyzed by decomposing them into contributions from each type of atom or groups of atoms in the solute and solvent molecules. Such decomposition enables the interpretation of distribution profiles based on the chemical characteristics of the species involved in the interactions at various distances.
Moreover, with appropriate normalization, MDDFs can be utilized to compute Kirkwood-Buff integrals. These integrals establish connections between the accumulation or depletion of solvent components and various thermodynamic properties, including solutestructural stability, solubility, and more.
The application of MDDFs to understand the solvation of proteins, general polymers, membranes, and other complex solutes in mixtures of solvents such as ionic liquids, sugars, and osmolytes will be presented through a series of examples.

This work was supported by Fapesp (procs. 2018/24293-0, and 2013/08293-7).