We pulled out two mutually exclusive subsets of 30 randomly selected ligand pairs (denoted as 'rand1' and 'rand2') and repeated TIES calculations with sampling "enhanced" using the REST2 protocol. The results are compared with those obtained using the standard TIES protocol (normal MD, that is, without REST2) in Figure (a). It is evident that REST2 degrades the accuracy of results for both rand1 and rand2, separately as well as for the combined dataset of 60 ligand pairs. For rand1/rand2, RMSE increases from 1.17 ± 0.13/1.18 ± 0.16 kcal/mol to 1.64 ± 0.29/1.40 ± 0.25 kcal/mol, whereas r p decreases from 0.73 ± 0.09/0.66 ± 0.14 to 0.48 ± 0.12/0.47 ± 0.17. For the combined dataset of 60 ligand pairs, MUE and RMSE increase by 0.12 kcal/mol and 0.34 kcal/mol, respectively, whereas r p decreases from 0.69 ± 0.07 to 0.48 ± 0.10. Thus, it can be concluded that blindly applying REST2 assuming that it will always have a positive impact and at worst none on the ∆∆G predictions is wrong. Consequently, in drug discovery applications, one may risk excluding many potentially useful leads by simply applying REST2. Note that it is an inbuilt feature of the proprietary FEP+ package; an earlier study of ours comparing FEP+'s performance to TIES showed that the former generates worse results and degrades those further for longer simulation times. It should also be noted here that Khalak et al. reported degradation in accuracy of the predicted free energies using the PMX method on extending their simulations up to 1 µs. This apparently anomalous effect of REST2 may be explained by considering the fact that it involves biasing the potential so as to improve the sampling of otherwise less accessible states. However, this means that the weights of different accessed states of the ensemble are also biased. Ensemble averaging properties using such biased weights leads to inaccuracies in results. To further substantiate this argument, we have plotted the absolute differences between ∆∆G predictions obtained with and without REST2 applied against the corresponding statistical uncertainties in standard TIES predictions without REST2 sampling, as shown in Figure . These two quantities are moderately correlated with r p of 0.65 ± 0.13. Thus, the average deviation from normal MD results as well as the extent of corresponding degradation in accuracy are larger for this subset than those for the entire set of 60 ligand pairs (over six-fold increase in MUE; 0.76 kcal/mol versus 0.12 kcal/mol). This implies that, as the number of accessible states/minima (separated by relatively small energy barriers)