After both ligand and protein preparation, cross-docking is performed with gnina. All of the ligands are docked against the receptor structure used for the alignment, the alphabetically lowest PDB ID (Table ??). The receptor's cognate ligand identifies the binding site. Docking is performed using all default parameters, except for exhaustiveness, min rmsd filter, and num modes (Table ??). exhaustiveness is increased to 16 to perform more sampling of the ligand during docking. min rmsd filter is reduced to 0.01 to allow highly similar, high-scoring poses to be output. num modes is set to 30 to ensure we have a max number of 300 total poses for each ligand if we have ten starting conformations for each ligand. Following the docked pose statistics of Paggi et al. , which have up to 300 poses per docked ligand, we attempt to sample 300 docked poses per ligand complex. Additionally, gnina tends to produce distinct poses in comparison to Glide which tends to output highly similar poses, often leading to generating several near-native poses. Therefore, we utilize several ligand conformations during docking to increase the likelihood that gnina outputs more than one pose close to the native state. After docking, we re-sort the combined output poses from gnina for each ligand according to the 'CNNscore', a score in the range [0,1] denoting the likelihood a ligand pose is correct . Following Paggi et al. and to reduce computation, only the top 100 docked poses of each ligand are used for subsequent steps.