To better understand the method's predictive power, we investigate its performance in predicting changes in kinetic off rates, which should be more directly related to the calculated magnitude. Indeed, cliff predictions based on koff (Figure .C) show a better correspondence than predictions based on Kd (MCC of 0.64 and 0.52, respectively). This indicates that DUck is well suited to guide the kinetic optimization of ligands, a task of considerable interest owing to the possible relationship of kinetic properties with in vivo efficacy. In practice, kinetic onrates are often relatively constant within series, as exemplified in Table . This leads to an (imperfect) correlation between koff and Kd, which allows us to address the more general problem of predicting potency-based activity cliffs.