In summary, we have benchmarked the accuracy of the QUBE force field against relative binding free energies of 17 drug-like inhibitors of p38α MAP kinase. The selected protein-ligand complex includes challenges due to sampling of protein-ligand binding modes and binding site hydration, and is therefore representative of typical hit-to-lead optimization projects. The mean unsigned error of 0.98 kcal/mol of the first generation of QUBE is competitive with widely-used biological force fields, and encouragingly the crystallographic binding pose of 17 was obtained despite starting from an alternative structure. More gen-erally, the FEP/REST enhanced sampling protocol employed here allowed us to obtain all predictions starting from a single binding pose, in contrast to previous studies that required two. One current disadvantage of QUBE is parameterization time, which can be of the same order of magnitude as the free energy calculation itself. However, there is future scope for the use of, for example, fragmentation schemes for reducing the computational expense of torsion scans and machine learning methods for non-bonded parameter assignment, especially when employed in congeneric series of ligands such as this one. Meanwhile, a wide range of accuracy improvements are envisaged, from the use of off-site charges in relative binding free energy calculations to improve the description of electron density anisotropy, to improved descriptions of polarization, van der Waals and short-range repulsion using advanced force field functional forms. Future work will continue to improve the accuracy and throughput of the QUBE force field for binding free energy applications in prospective medicinal chemistry efforts.