directions; hence will be referred to as the "600 ps" protocol hereafter. Further, we have also performed NEQ calculations using four different transition lengths (400 ps, 800 ps, 1 ns and 2 ns; same length used in both directions) for the entire dataset whose predictions have been included in the Supporting Information and are referred to at appropriate places in the main text. As already mentioned in section 2.3, in case of the NEQ approach, we report the occurrence of extreme work values (>1000 kcal/mol) for forward transitions when the ligand is coupled in the protein environment. The origin and extent of such extreme work values is discussed in detail in the Supporting Information (see found that, out of the total 261k protein-ligand systems with K i measurements included in the ChEMBL dataset (version 12), only about 10% had more than one reported K i measurements available. Of these, more than half were either duplicate entries or cases where multiple measurements came from different publications. This means that less than 5% of the total systems had multiple K i measurements reported in the same publication. Even for this small subset, multiple measurements mostly correspond to reports on assay optimisations or different stereoisomers. Given the lack of ensembles, the reliability of experimental binding affinity estimates is also questionable. Ross et al. recently assessed the extent of reproducibility in experimental ∆G estimates and reported that RMSE between ABFE measurements from independent experiments is on average 0.9 kcal/mol (using different assays) which could be as high as 2 kcal/mol in some cases. Therefore, this is the limit of the accuracy achievable by any computational method predicting absolute ABFEs. We recently reported non-normality in experimental BFE distributions which obviously cannot be accounted for using one-off predictions. Further, the lack of uncertainty in experimental BFEs is responsible for bias in the least-squares regression metrics undermining their reliability .