To demonstrate the potential of our end-to-end RBFE workflow, we benchmarked it using the Amazon Web Services (AWS) cloud. The detailed configuration notes for this setup are provided in the SI. For this proof of concept demonstration we calculated relative binding free energy between two ligands from the set of TNKS2 inhibitors. By leveraging an AWS ParallelCluster and Icolos' SLURM interface, each simulation type was dispatched to a Figure : RMSE and Kendall's τ for each docking method on each of the four tested systems. Shaded regions represent 95% confidence intervals compared to experimental uncertainty. For the cases where experimental uncertainty was not available (PTP1B, TNKS2, SYK), a lower bound for uncertainty of 0.43 kcal/mol as suggested by the best practices was used . ratio. Optimal node selection for running GRO-MACS workflows in the cloud has been recently studied . Based on this work, minimisation and NVT equilibration jobs were performed using Intel CPU-only C5 instances, equilibrium simulations using NVIDIA-equipped G4DN nodes, and transitions using AMD HPC6a. In all, with our Icolos workflow, a single free energy estimate requires 10 hours of wall clock time, at a cost of $12-15 per ΔΔG value.