Selecting combinatorial libraries to optimize diversity and physical properties

The program SELECT is presented for the design of combinatorial libraries. SELECT is based on a genetic algorithm with a multi-objective fitness funct ion. Any number of objectives can be included, provided that they can be re adily calculated. Typically, the objectives would be to maximize structural diversity while ensuring that the compounds in the library have "drug-like " properties. In the examples given, structural diversity is measured using Daylight fingerprints as descriptors and either the normalized sum of pair wise dissimilarities, calculated with the cosine coefficient, or the averag e nearest neighbor distance, calculated with the Tanimoto coefficient, as t he measure of diversity. The objectives are specified at run time. Combinat orial libraries are selected by analyzing product space, which gives signif icant advantages over methods that are based on analyzing reactant space. S ELECT can also be used to choose an optimal configuration for a multicompon ent library. The performance of SELECT is demonstrated by its application t o the design of a two-component amide library and to the design of a three- component thiazoline-2-imine library.