At face value, these figures do not appear encouraging; however, looking carefully at the correlation plot, systematic errors in predicted ∆G values are clearly visible that heavily compromise the overall accuracy of predictions. This is a known issue in ABFE calculations as the two end-points of the ligand coupling alchemical transformation use the same protein conformation, while the two end-points represent apo and holo conformations of the protein which may be substantially different (including differences in their protonation and/or tautomeric states) . Indeed, these systematic errors may also partly (or even fully) correspond to multiple modes of ligand binding within the protein environment or to other factors such as differences in water occupancy, and may appear exaggerated due to lack of reported non-normal experimental BFE distributions (see the Supporting Information for more details). Such a difference in protein conformation and/or ligand binding mode is not directly accounted for in these ABFE calculations, leading to systematic errors in the predicted ∆Gs, an issue present in both EQ and NEQ methods. For the raw predictions, MUE and RMSE values obtained using EQ are better than those obtained using NEQ. The correlation is, however, better using NEQ due to a wider distribution of ∆G values in case of EQ. It must be noted that the correlation coefficient is a meaningful metric only when absolute values of ∆G are compared which is not true in our case due to the prevalence of systematic errors in predicted values that have widely varying magnitudes across systems. On ignoring the systems with large magnitudes of systematic errors (> 2 kcal/mol for TYK2, CDK2 and PDE2), RMSE values using the EQ approach are better for 11 out of 14 systems as compared to the NEQ approach.