A Bright Future for Evolutionary Methods in Drug Design

Tu Le, David Alan Winkler

    Research output: Contribution to journalArticlepeer-review

    21 Citations (Scopus)


    Most medicinal chemists understand that chemical space is extremely large, essentially infinite. Although high-throughput experimental methods allow exploration of drug-like space more rapidly, they are still insufficient to fully exploit the opportunities that such large chemical space offers. Evolutionary methods can synergistically blend automated synthesis and characterization methods with computational design to identify promising regions of chemical space more efficiently. We describe how evolutionary methods are implemented, and provide examples of published drug development research in which these methods have generated molecules with increased efficacy. We anticipate that evolutionary methods will play an important role in future drug discovery. Drug-like chemical space is extremely large, essentially infinite. Evolutionary algorithms are very effective ways to explore large spaces and to identify novel molecules with useful biological properties. The emergence of new technologies like automated chemical synthesis and robotic screening has removed the major barriers to much wider application of these ingenious and efficient evolutionary methods in drug discovery. (Image reproduced with permission.

    Original languageEnglish
    Pages (from-to)1296-1300
    Number of pages5
    Issue number8
    Publication statusPublished - 1 Aug 2015


    • chemical space
    • drug design
    • drug-like space
    • evolutionary algorithms
    • genetic algorithms


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