LASSOO: a generalized directed diversity approach to the design and enrichment of chemical libraries.

Abstract

Pharmaceutical discovery relies on the screening of chemical libraries that are as diverse as possible yet constrained in favor of compounds possessing attributes that are normally associated with successful drug candidates. We describe a new algorithm for simultaneously addressing both objectives, providing an effective means to increase structural diversity in a chemical library while maintaining a bias toward compounds that retain the desirable properties of drugs. The LASSOO algorithm exploits differences in descriptor distributions to identify novel compounds that are most dissimilar to the members of an existing screening library and most similar to members of a target library with desirable characteristics. We illustrate the LASSOO technique using publicly available compound databases and bit string descriptors. The architecture of the algorithm is general enough to allow any set of descriptors or similarity measures to be employed, and it is easily adaptable to other means of directing diversity, such as the avoidance of toxicity and/or poor pharmacokinetic properties.