Comparison of algorithms for dissimilarity-based compound selection.

Dissimilarity-based compound selection has been suggested as an effective method for selecting structurally diverse subsets of chemical databases. This article reports a comparison of several maximum-dissimilarity and sphere-exclusion algorithms for dissimilarity-based selection. The effectiveness of the algorithms is quantified by the numbers of biological activity classes identified in subsets selected from the World Drugs Index database, and by the numbers of active compounds identified in feedback searches of this database. The experiments demonstrate the general effectiveness and efficiency of the MaxMin algorithm.