In the early stages of drug discovery fragment-based drug discovery (FBDD) has emerged as a standard methodology . It uses small molecules (<250 Da) under the assumption that the information from multiple small molecules is more informative than the information from a low number of larger molecules (typically used in traditional high-throughput screening) in the early hit-tolead part of drug discovery . This is because small molecules are more likely to have a greater proportion of their potential interaction vectors associating with the protein than the proportion in large molecules, where significant functional parts of the molecule may not interact with the protein at all. Based on this assumption, it should be possible, as part of the FBDD lead-design process, to take the protein-ligand interaction information from these smaller proximal molecules to design larger derivative molecules. This should result in the more efficient design of molecules which possess better binding affinity at a lower cost than lead optimization through structure-activity relationship (SAR) exploration of larger initial hits . Regardless of whether informative structural information is available for initial fragment hits, by far the most common strategy is to enumerate derivative compounds independently of structure, often through similarity or substructure searching, and afterwards employ docking as a conformational filter . As discussed below, the shortcomings of this approach negatively affect successfulness of the searches.