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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of computer aided molecular design 10 (1996), S. 337-358 
    ISSN: 1573-4951
    Keywords: Genetic algorithms ; Evolutionary programming ; Evolution strategies ; Drug design ; Molecular modelling ; Protein folding
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary In recent years, search and optimisation algorithms inspired by evolutionary processes have been applied with marked success to a wide variety of problems in diverse fields of study. In this review, we survey the growing application of these ‘evolutionary algorithms’ in one such area: computer-aided molecular design. In the course of the review, we seek to summarise the work to date and to indicate where evolutionary algorithms have met with success and where they have not fared so well. In addition to this, we also attempt to discern some future trends in both the basic research concerning these algorithms and their application to the elucidation, design and modelling of chemical and biochemical structures.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1573-4951
    Keywords: Drug design ; De novo design ; Genetic algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary Recently, the development of computer programs which permit the de novo design of molecular structures satisfying a set of steric and chemical constraints has become a burgeoning area of research and many operational systems have been reported in the literature. Experience with PRO_LIGAND—the de novo design methodology embodied in our in-house molecular design and simulation system PRO-METHEUS—has suggested that the addition of a genetic algorithm (GA) structure refinement procedure can ‘add value’ to an already useful tool. Starting with the set of designed molecules as an initial population, the GA can combine features from both high- and low-scoring structures and, over a number of generations, produce individuals of better score than any of the starting structures. This paper describes how we have implemented such a procedure and demonstrates its efficacy in improving two sets of molecules generated by different de novo design projects.
    Type of Medium: Electronic Resource
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