Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt–water mixtures

Abstract

Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt–water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water–water and water–ion entropies contribute strongly. We show that the water–ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water–water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.

Developing end-point methods for absolute binding free energy calculation using the Boltzmann-quasiharmonic model

“…More studies are needed to examine this further by comparing with more accurate explicit solvent based solvation free energy methods. [79][80][81][82] The main advantage of the EE-BQH approach outlined is that with this method, the different thermodynamic contributions to the free energy of binding can be decomposed into their physical contributions (translational, rotational, and torsional entropies, correlation entropies, etc.). This potentially allows for focusing ligand design efforts by addressing specifically the various contributions to the free energy of binding thereby providing useful guidance for ligand design.…”

Comparison of hydrophobicity scales for predicting biophysical properties of antibodies

“…For the score by Heiden et al (1993) , we first computed a solvent-excluded surface (SES), using the post-processing routines of our previous work ( Waibl et al, 2022 ) (available from https://github.com/liedllab/gisttools ) to compute the lowest possible distance to a solvent molecule on a 3D grid, and then creating an isosurface at the solvent radius of 1.4 Å using the marching cubes algorithm in scikit-image ( van der Walt et al, 2014 ). For each vertex k of the surface, we compute the molecular lipophilicity potential (MLP) using: …”

The kth nearest neighbor method for estimation of entropy changes from molecular ensembles

“…63,109 The same authors have been extending recently the GIST approach to salt-water solutions and other, rigid, solvents. 110,111 The method is implemented in the software GIST, 106,107 SSTMap, 108 PME-GIST, 112 GIGIST, 63,109 which are based on single molecule entropy computed on grid cells. A different approach is implemented in the software PerjMut, 64,113 which uses permutation of water labels to increase single water sampling, and the mutual information expansion 83 to deal with the large dimensionality.…”