Having assembled the 2D and 3D structures of the core and user-defined R-groups, we include some simple tools for assessing the drug-likeness and synthetic tractability of the designed and bioactivity (e.g. taken from a single data source with adequate dynamic range) data, which has been collected with the goal of assessing the accuracy of free energy methods. For each target, modelled structures of the protein in complex with a congeneric series of ligands are provided as starting points for free energy calculations, but the methods used to position the R-groups are, to our knowledge, not necessarily consistent or documented. Here, we apply the FEgrow workflow to ten targets from the protein-ligand benchmark set. Starting from the crystal structure of each target, we truncate the bound ligand to a common core, which is shared across the congeneric series to be modelled. A summary of the targets, the crystal structures used, the number of R-groups grown, and their common core and net charge is provided in Tables and. We use the methods outlined in the previous section to re-grow the congeneric series of ligands in the binding pockets, including enumeration and optimisation of possible R-group conformers, and scoring of final poses.