To build a model of a project we need to choose a way to represent molecules, how each compound interacts with the project's biological target to produce an assay signal and a way of capturing the way that compounds change in an ordered sequence as the project progresses. For this work compounds are described as fixed length binary strings (analogous to a substructural fingerprint ) and molecular recognition is achieved by matching a subset of set bits at fixed bit positions. This eschews directly using standard chemical structures and protein receptors in favor of a more abstract representation of chemistry. Such a reduced model of molecules and their binding to receptors has precedence in the work of Hann et al . The authors of that paper fashioned a simple model of ligand binding by binary feature matching to draw out general principles of selecting compounds to test. This allowed exhaustive enumeration and simulation techniques to be applied to a population of model compounds interacting with a target.