Second, we used an older version of OMEGA to generate conformers for docking, which, even though was able to handle macrocycles, was not optimized to handle macrocycles well. As a result, for some of the ligands (Table ) we did not sample conformations close to the native cocrystal pose, which in turn decreased our pose prediction accuracy. Recently a new distance geometry-based sampling algorithm was introduced in (released in Oct 2018 after D3R GC4), which is tailored towards sampling macrocycle conformations and will possibly help sampling the ligand conformational space in a more robust manner. Third, in this work, the query ligands in the pose prediction challenge had very similar reference ligands already deposited in the RCSB PDB database with co-crystal structures. POSIT might have been a better docking tool than HYBRID for the given dataset. For cross-docking studies with TanimotoCombo ligand similarity greater than 0.9, POSIT has been shown to have significantly better accuracy than other docking tools. It employs a shape-matching algorithm to overlay the query ligand on a reference ligand and optimizes the alignment of the query ligand and the induced strain.