Gillet, V.J., Khatib, W., Willett, P., Fleming, P.J. and Green, D.S.V. (2002) Combinatorial library design: using a multiobjective genetic algorithm. Journal of Chemical Information and Computer Sciences, 42 (2). pp. 375-385. ISSN 0095-2338Full text not available from this repository.
Early results from screening combinatorial libraries have been disappointing with libraries either failing to deliver the improved hit rates that were expected or resulting in hits with characteristics that make them undesirable as lead compounds. Consequently, the focus in library design has shifted toward designing libraries that are optimized on multiple properties simultaneously, for example, diversity and druglike physicochemical properties. Here we describe the program MoSELECT that is based on a multiobjective genetic algorithm and which is able to suggest a family of solutions to multiobjective library design where all the solutions are equally valid and each represents a different compromise between the objectives. MoSELECT also allows the relationships between the different objectives to be explored with competing objectives easily identified. The library designer can then make an informed choice on which solution(s) to explore. Various performance characteristics of MoSELECT are reported based on a number of different combinatorial libraries.
|Academic Units:||The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
The University of Sheffield > University of Sheffield Research Centres and Institutes > The Krebs Institute for Biomolecular Research (Sheffield)
|Depositing User:||Information Studies|
|Date Deposited:||23 Mar 2009 15:05|
|Last Modified:||13 May 2009 17:53|
|Publisher:||American Chemical Society|
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