The complete set of ligands was then explored with DUck. Despite the high potency of the ligands in the data set, the distribution of ΔGQB shows lower values for CDK2 (Figure ) than for HSP90α (Figure ). Compounds from series A have predominantly labile interactions, followed by series D, while series B and C present more robust interactions (median ΔGQB values of 6.6, 13.6, 13.4 and 9.7 kcal mol -1 , respectively). The relatively high ΔGQB values in series C contrast with the metastable states found during the τRAMD simulations. A scan of ΔΔGQB thresholds was performed via a receiver operator curve, leading us to define an AC as a pair of compounds where ΔΔGQB is greater than half the minimum of both ΔGQB values. With this definition, the AC predictions of series B surpassed the HSP90α results, reaching a MCC of 0.6 and recovering 78% of the activity cliffs. The predictive capabilities for the other series were worse: Series D has a MCC of 0.2, followed by Series A and C, respectively, where no predictive capabilities were seen (i.e., MCC ≈ 0). The bad results from series C confirm that a steep quasi-bond barrier is an insufficient estimator of DUck's predictive confidence. A one-step dissociation mechanism is also needed. On the opposite spectrum, series D shows that ΔGQB can still have some predictive power (albeit mediocre) for series with low barriers, as long as there are no metastable states in the dissociation pathway.