Teaching free energy calculations to learn from experimental data

Marcus Wieder, Josh Fass, and John Chodera
[bioRxiv] [code] [data]

We show, for the first time, how alchemical free energy calculations can be used to not only compute free energy differences between small molecules involving covalent bond rearrangements in systems treated entirely with quantum machine learning potentials, but that these calculations have the capacity to learn to efficiently generalize from conditioning on experimental free energy data.

Fitting quantum machine learning potentials to experimental free energy data: Predicting tautomer ratios in solution

Marcus Wieder, Josh Fass, and John D. Chodera
Chemical Science, in press [bioRxiv] [code]

We demonstrate, for the first time, how alchemical free energy calculations can performed on systems simulated entirely with quantum machine learning potentials and how these potentials can be retrained on experimental free energies to generalize to new molecules from limited training data. We apply this approach to a difficult problem in small molecule drug discovery: Predicting accurate tautomer ratios in solution.