A common method to assess the binding of a candidate molecule is docking. Docking protocols consist of a search algorithm that performs thousands of heuristic iterations assessed by a score function to find the lowest energy predicted position, orientation, and conformation of the ligand in the context of the target protein . Docking protocols find the energetic minimum according to the parameters of the force-field used to approximate the system, but may result in a local energy-minimum conformation that deviates from the one found in the experimental structure. This can occur for a variety of reasons ranging from insufficient or inaccessible sampling of either the ligand or protein conformations to inaccuracies of the physics in the empirical models. A common benchmark to assess the quality of a docking protocol is to "redock" the ligand from an X-ray crystal structure; namely removing the ligand and docking it and comparing the RMSD between the original and the docked ligand. With this approach, even the best algorithms reproduce roughly only half of all compounds docked to an RMSD of less than 2 Å . An approach to improve this poor fidelity to the parent hits is by adding constraints to pharmacophores or to key atoms on the protein . Another limitation stems from the fact most docking algorithms generate a set of small molecule conformers before docking which, especially for larger and more flexible small molecules, may all greatly diverge from the empirical crystallographic protein-bound conformer. Whereas it is straightforward to embed the conformer of a derivative compound with the conformation of a parent FBDD hits that is its direct substructure, it is non-trivial when the substructure overlaps are imperfect and between multiple hits, as will be addressed below.