Architecture-Independent Absolute Solvation Free Energy Calculations with Neural Network Potentials.

ABSTRACT: Allowing atoms or molecules to disappear is a critical step in alchemical free energy simulations (FES). The necessary tricks are well understood when using force fields. Over the past few years, neural network potentials (NNPs) have seen rapid development. Their potentially higher accuracy compared to force fields makes them attractive for use in FES. Here, we outline a method for gradually decoupling atoms and molecules in systems that are fully described by NNPs. Specifically, we show that manipulating the neighbor list is equivalent to using soft-core potentials in force-field-based FES. Since constructing the neighbor list is a central step, regardless of the NNP's inner workings, our approach is agnostic to NNP architecture. We validate the correctness of our methodology by demonstra

SUBMITTER: Picha AK 

PROVIDER: S-EPMC12641469 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature