Per|Mut: Spatially Resolved Hydration Entropies from Atomistic Simulations

The hydrophobic effect is essential for many biophysical phenomena and processes. It is governed by a fine-tuned balance between enthalpy and entropy contributions from the hydration shell. Whereas enthalpies can in principle be calculated from an atomistic simulation trajectory, calculating solvation entropies by sampling the extremely large configuration space is challenging and often impossible. Furthermore, to qualitatively understand how the balance is affected by individual side chains, chemical groups, or the protein topology, a local description of the hydration entropy is required. In this study, we present and assess the new method Per|Mut, which uses a permutation reduction to alleviate the sampling problem by a factor of N! and employs a mutual information expansion to the third order to obtain spatially resolved hydration entropies. We tested the method on an argon system, a series of solvated n-alkanes, and solvated octanol.

Automated summary

The study presents a new method called Per|Mut, which utilizes permutation reduction and mutual information expansion to address the sampling problem of hydration entropy. The method was tested on various systems, including an argon system, solvated n-alkanes, and solvated octanol.