Harren at al. has demonstrated that binding affinity data for pairs of closely related molecules (matched molecular pairs) combined with expert chemical knowledge can be a powerful benchmark, but it is difficult to quantify the performance using this approach. Sanchez-Lengeling et al. addressed this problem by fitting models to experimentally measured solvation energies and comparing the corresponding heatmaps to the contributions from Crippen's well-known linearly additive atom-based model of logP values -a property that is related to solubility. The attribution methods tested using this benchmark gave atomic attributions with relatively modest correlation to this ground truth but, as pointed out by Henderson et al. , part of the reason may be that the correlation between logP values and solvation energies is not perfect. Instead they suggested that it may be better to fit the model to Crippen logP values themselves, but did not test this approach.