Despite the challenge of discriminating between relatively small functional group modifications, the scoring function performs quite well and is useful in providing initial guidance for a number of targets from the protein-ligand benchmark set used here. Nevertheless, inspired by the BOMB/MCPRO approach to molecular design, 13 we envisage the primary use of FEgrow being as a source of input structures for more rigorous free energy based affinity predictions. We demonstrate this functionality here, using SOMD to calculate the relative binding free energies of 13 uracil-based inhibitors of the SARS-CoV-2 main protease. Using only a single crystal structure as input (PDB: 7L10) and the FEgrow workflow to build the remaining structures, we obtain excellent agreement with experimental binding affinities (MUE = 0.45 kcal/mol, R 2 = 0.53). We envisage future improvements including the use of a flexible receptor for the growth phase, and future use cases including seeding free energy calculations with multiple low energy conformers. FEgrow is available for download from , and we welcome suggestions from the community for added functionality.