The cyclodextrin derivatives were new to SAMPL, and many methods achieved relatively low RMS errors -though this may partly be due to the low dynamic range of the set; a hypothetical method which predicted a constant binding free energy of -4 kcal/mol for all guests would achieve an RMS error of only 0.70 kcal/mol . This low dynamic range also meant that correlation metrics were typically poor. The force field used in this dataset played a role in computing accurate binding free energies, with GAFF2 seemingly giving more accurate results, followed by CGenFF and GAFF (a more detailed comparison of these force fields can be seen in Ref and Ref ). In addition, nonequilibrium approaches appear to perform slightly better with cyclodextrin systems. The performance of methods for the cyclodextrin dataset varied across host-guest systems, but predicting reliable binding free energies for cyclodextrins with large side chains to rimantadine was frequently challenging. There were no AMOEBA submissions for this aspect of SAMPL7, but the use of a polarizable force field may help ameliorate agreement between computational methods with experiments and facilitate accurate modeling of cyclodextrin host-guest interactions.