Estimating Solvation Free Energies with Boltzmann Generators

TL;DR

This paper presents a novel flow-based computational method for estimating solvation free energies, improving accuracy and efficiency over traditional approaches by directly mapping solvent configurations.

Contribution

It introduces a normalizing flow framework that enhances overlap between states, enabling better free energy estimates with fewer intermediate steps.

Findings

Achieves acceptable accuracy for challenging solvation transformations.

Flow generates physically meaningful solvent rearrangements.

Enhances configurational overlap compared to conventional methods.

Abstract

Accurate calculations of solvation free energies remain a central challenge in molecular simulations, often requiring extensive sampling and numerous alchemical intermediates to ensure sufficient overlap between phase-space distributions of a solute in the gas phase and in solution. Here, we introduce a computational framework based on normalizing flows that directly maps solvent configurations between solutes of different sizes, and compare the accuracy and efficiency to conventional free energy estimates. For a Lennard-Jones solvent, we demonstrate that this approach yields acceptable accuracy in estimating free energy differences for challenging transformations, such as solute growth or increased solute-solute separation, which typically demand multiple intermediate simulation steps along the transformation. Analysis of radial distribution functions indicates that the flow generates physically meaningful solvent rearrangements, substantially enhancing configurational overlap between states in configuration space. These results suggest flow-based models as a promising alternative to traditional free energy estimation methods.