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Soft Computing Approaches in Chemistry pp 1–30Cite as

Application of Evolutionary Algorithms to Combinatorial Library Design

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 120))

Summary

The last deacde has seen a revolutionary change in the processes used to discover novel bioactive compounds in the pharmaceutical and agrochemical industries. This change is due to the introduction of automation techniques which allow tens or hundreds of thousands compounds to be synthesised simultaneously and then to be screened for activity rapidly. These techniques of combinatorial synthesis and high throughput screening have vastly increased the throughput of the traditional structure-activity cycle. Despite the initial enthusiasm for the methods, early results have been disappointing, producing fewer hits than were expected or hits that have undesirable properties to be suitable as new drugs or agrochemicals. It is now realised that the number of compounds that could potentially be considered as new bioactive compounds is enormous compared to the numbers that can be handled in practise, even using automated techniques. Thus, efficient and effective methods are required for designing the sets of compounds to be used in combinatorial syntheses and to be screened in high throughput screening experiments. It is not possible to explore such large search spaces systematically and hence many methods have been developed for designing combinatorial libraries. Evolutionary algorithms are well suited to search for solutions to large combinatorial problems and this chapter reviews the application of genetic algorithms, a sub-branch of evolutionary algorithms, to combinatorial library design.

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Author information

Authors and Affiliations

  1. Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK

    Valerie J. Gillet

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  1. Valerie J. Gillet
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Editors and Affiliations

  1. Physical and Theoretical Chemistry, Oxford University, South Parks Road, OX1 3QZ, Oxford, UK

    Hugh M. Cartwright

  2. CIS Department, Philadelphia University, 19144, Philadelphia, PA, USA

    Les M. Sztandera

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Gillet, V.J. (2003). Application of Evolutionary Algorithms to Combinatorial Library Design. In: Cartwright, H.M., Sztandera, L.M. (eds) Soft Computing Approaches in Chemistry. Studies in Fuzziness and Soft Computing, vol 120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36213-5_1

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  • DOI: https://doi.org/10.1007/978-3-540-36213-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53507-9

  • Online ISBN: 978-3-540-36213-5

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