Bioactive diversity and screening library selection via affinity fingerprinting

The Similarity Principle provides the conceptual framework behind most modern approaches to library sampling and design. However, it is often the case that compounds which appear to be very similar structurally may in fact exhibit quite different activities toward a given target. Conversely, some targets recognize a wide variety of molecules and thus bind compounds that have markedly different structures. Affinity fingerprints largely overcome the difficulties associated with selecting compounds on the basis of structure alone. By describing each compound in terms of its binding affinity to a set of functionally dissimilar proteins, fundamental factors relevant to binding and biological activity are automatically encoded. We demonstrate how affinity fingerprints may be used in conjunction with simple algorithms to select active-enriched diverse training sets and to efficiently extract the most active compounds from a large library.