Evolutionary and genetic methods in drug design

Abstract

Many phases of rational drug design involve finding solutions to large combinatorial problems for which an exhaustive search is intractable. A simulation of the evolutionary pressure of natural selection can be incorporated into artificial intelligence algorithms to rapidly find good, if not optimal, solutions to such problems. This review describes implementations and select applications of genetic algorithms and evolutionary programming in various aspects of rational drug design. Evolutionary methods have been developed in the areas of pharmacophore elucidation, lead discovery and lead optimization, as well as in many areas of peripheral importance to rational drug design.

Publication Title

Drug Discovery Today

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