Parameters of the various on-the-fly optimization protocols employed. indicates that there is a significant association between our predicted ∆∆𝐺 𝐴→𝐵 𝑏𝑖𝑛𝑑 s and their experimental values. This is important as the null model (∆∆𝐺 𝐴→𝐵 𝑏𝑖𝑛𝑑 = 0 for each mutation) performs extremely well on this system, as others have noted, with MAE and RMSE of 0.95 and 1.23 kcal/mol, respectively. Figure displays simulated distributions of MAEs, RMSEs, and R 2 s of Protocol A with respect to the number of replicates, referred to hereafter as batch size, included in the calculation. These distributions were generated by taking 10,000 random combinations of the given sample size of replicates, averaging the ∆∆𝐺 𝐴→𝐵 𝑏𝑖𝑛𝑑 , and then calculating the MAE, RMSE, and R 2 , respectively. Tabulated summary statistics for these distributions are shown in Table . The number of additional simulations performed varied by protocol, mutation, λ-window, and alchemical step, as seen in Figure . As expected, the protein-ligand complex step required more average additional simulation time to achieve convergence than the solvated ligand step regardless of the protocol employed. Protocol A generally required the least additional simulation time to achieve convergence in both alchemical steps (see Table for protocol details). Overall, the additional simulation time was evenly distributed between λ-windows of the solvated ligand step, with more variation in the protein-ligand complex step; however, this pattern broke down when comparing specific mutations, as seen in Figure . Correlation was observed between the average additional simulation times of the λ-windows of the various protocols, which indicates that our protocol is correctly identifying λ-windows that require additional simulation to achieve convergence. Truncated trajectories of all replicates were examined, with 10,000 MAEs and RMSEs generated via the resampling scheme described above. Mean MAE and RMSE and their respective standard errors are displayed below in Figure . In all protocols, significant accuracy improvement is observed during the first nanosecond of simulation time, with only minor accuracy improvement observed afterwards. After the initial simulation period, Protocols A and C12 do not display any gain in accuracy, whereas Protocols B and C do (see Table for protocol details). These results suggest that a shorter maximum simulation time may be employed without a loss of accuracy. (as opposed to a Langevin thermostat), and does not utilize the SHAKE algorithm unlike the other protocols.