3.1 FlexPDBbind: ensemble models for 13,000 biomolecular complexes. For each biomolecular complex in the PDBbind 'refined' and 'general' sets we generated a six-member conformational ensemble. We applied Rosetta's FastRelax protocol to the crystal structures to generate the first member, and then repeatedly applied the Hybridize and FastRelax protocols to generate up to five additional conformations (Methods). This resulted in 13,063 biomolecular ensembles, for a total of 71,825 conformations. The mean Root Mean Square Deviation (RMSD) of the ensembles calculated over the CA atoms is 1.57 Å, and the Root Mean Square Fluctuations is 2.10 Å (Fig ). This compares to a mean RMSD of 1.24 Å for the structurally aligned crystal structures. To evaluate the structural quality of the generated models, we calculated clash scores and overall Molprobity scores with Molprobity 59 (Fig ). We discarded ensembles with outlying clash scores (scores over 10). We then docked ligands to each conformation of their cognate receptor using the protocol detailed in Methods. The RMSDs of docked ligand poses calculated to their starting pose in the source receptor conformation reveals a distribution sharply peaked around 3. Strikingly, when we applied an AtomNet PoseRanker model trained on sampled ensembles to predict binding modes using a dataset of single receptor structures, we found that top poses were enriched over the model trained on single structures (Fig 3C, green vs. black line). While, again, the improved performance could in part perhaps be attributable to the larger training set for the sampled ensembles, the result does suggest that the model retains information about flexible binding sites, illustrating the value of performing additional conformational sampling where experimental data is limited.