Computational analysis of the solvation of coffee ingredients in aqueous ionic liquid mixtures

Abstract

We investigate the solvation behavior of valuable coffee ingredients in aqueous mixtures of the ionic liquid 1-ethyl-3-methylimidazolium acetate with a particular emphasis on hydrotropic theory and Kirkwood–Buff analysis.

Molecular Interpretation of Preferential Interactions in Protein Solvation: A Solvent-Shell Perspective by Means of Minimum-Distance Distribution Functions

“…Thus, the necessity of more general distribution functions for the analysis of solutes of complex shapes has been recognized frequently. [18][19][20][21] In particular, the use of the distance of one solvent site (an atom or the center of mass) of the solvent molecule to the surface of the solute, or to the nearest solute atom, was proposed independently by different authors as an alternative to overcome the complexity of the solute shape. [18][19][20][22][23][24][25][26][27] This choice defines what has been called the "solvation-shell" distribution functions, g ss (r), 23,24 or proximal distribution functions, g ⊥ (r), 18,22,26,27 which appeal directly to the concept of Voronoi tesselation.…”

“…[18][19][20][22][23][24][25][26][27] This choice defines what has been called the "solvation-shell" distribution functions, g ss (r), 23,24 or proximal distribution functions, g ⊥ (r), 18,22,26,27 which appeal directly to the concept of Voronoi tesselation. 21,28 In all cases, the counting of nearest distances is straightforward from a simulation, but the normalization procedure leading to the distribution functions can be cumbersome. 20 When using Voronoi tesselation, the normalization might depend on the estimation of the volumes in space associated with each reference atom or site.…”

“…Because RDFs rely usually on the distance between the centres of mass, non-spherical molecules require longer distances for the RDF to converge to 1 due simply to their shape. 21 For ternary systems (solute, solvent and cosolvent) it is possible from KBIs to compute preferential interaction parameters, which are a measure of the excess number of cosolvent molecules in the domain of the solute, and can be determined experimentally. 4,19,30,31 Interestingly, it is easier to compute the preferential interaction parameter than KBIs.…”

Computational solvation analysis of biomolecules in aqueous ionic liquid mixtures

“…Although this approach is feasible for many small solutes, it may give highly inaccurate results in case of anisotropic solutes (Zeindlhofer et al . 2017 , 2018 ) like large proteins (Neumayr et al 2010 ) due to non-symmetric excluded volume effects. Furthermore, for heterogeneous solvents with different molecular sizes, more than one shell radius would be necessary to describe a solvation shell appropriately (Haberler et al 2011 ).…”

“…As shown in the respective publications (Zeindlhofer et al . 2017 , 2018 ), the investigated biomolecules are flat, aromatic systems of high anisotropy, which makes Voronoi tessellation necessary to distinguish between several solvation shells. Since Voronoi tessellation allows straightforward calculation of solvent shell volumes, a shell-wise calculation of Kirkwood-Buff interaction parameters analogous to Kirkwood-Buff integrals (Zeindlhofer et al 2018 ) can be computed.…”