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Repeatability of Relative Free Energy Calculations in Solution with ANI-2x and MACE-OFF23
Sara Tkaczyk1,2, Thierry Langer1, Marcus Wieder3
1Department of Pharmaceutical Sciences, Pharmaceutical Chemistry Division, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
Journal of Chemical Theory and Computation
|December 17, 2025
Summary
Neural network potentials (NNPs) show promise for alchemical free energy calculations. However, careful evaluation of NNP performance in condensed-phase simulations is crucial for reliable results, as demonstrated by varying performance between ANI-2x and MACE-OFF23(small).
Area of Science:
- Computational Chemistry
- Molecular Modeling
- Physical Chemistry
Background:
- Alchemical free energy calculations are vital for predicting molecular properties.
- Neural network potentials (NNPs) offer a promising, transferable alternative to traditional force fields.
- Assessing NNP suitability for complex simulations, especially in condensed phases, remains an active research area.
Purpose of the Study:
- To investigate the feasibility and challenges of using NNPs for alchemical free energy calculations.
- To evaluate the performance of different NNPs (ANI-2x and MACE-OFF23(small)) in predicting tautomeric states.
- To develop and test a methodology for smooth interpolation between states using energy mixing and dummy atoms.
Main Methods:
- Employed a single-coordinate dual-topology approach for alchemical free energy calculations.
- Utilized energy mixing via selective masking of interactions involving dummy atoms for state interpolation.
- Tested the framework with ANI-2x and MACE-OFF23(small) NNPs for tautomer free energy differences in aqueous solution.
Main Results:
- MACE-OFF23(small) yielded converged free energy results.
- Simulations with ANI-2x exhibited significant variability and convergence issues.
- ANI-2x's performance was hindered by slow water dynamics and solute overstabilization, leading to sampling difficulties.
Conclusions:
- Transferable NNPs are advantageous but require rigorous validation in condensed-phase environments.
- The choice of NNP significantly impacts the reliability of free energy calculations.
- Careful assessment of NNP dynamics and potential for metastable states is essential before application in free energy simulations.
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