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Computational library design genetic algorithms

The methods of simulated annealing (26), genetic algorithms (27), and taboo search (29) are three of the most popular stochastic optimization techniques, inspired by ideas from statistical mechanics, theory of evolutionary biology, and operations research, respectively. They are applicable to our current problem and have been used by researchers for computational library design. Because SA is employed in this chapter, a more-detailed description of the (generalized) SA is given below. [Pg.381]

Liu, D., Jiang, H., Chen, K. and Ji, R. A New Approach to Design Virtual Combinatorial Library with Genetic Algorithm Based on 3D Grid Property. J. Chem. Inf. Comput. Sci., 1998, 38, 233-242. [Pg.66]

P Willett, J Bradshaw and D V S Green 1999. Selecting Combinatorial Libraries to Optimize rsity and Physical Properties. Journal of Chemical Information and Computer Science 39 169-177. 1 and A W R Payne 1995. A Genetic Algorithm for the Automated Generation of Molecules in Constraints. Journal of Computer-Aided Molecular Design 9 181-202. [Pg.738]

P. J., Green, D. V. S. (2002) Combinatorial library design using a multiobjective genetic algorithm. J Chem Inf Comput Sci 42, 375-385. [Pg.50]

Fig. 3. MapMaker is a combinatorial library optimization tool developed at ArQule, currently used in the design of screening libraries. The system is represented as a black box, since the details of operation are hidden by a web interface, to which chemists provide a reaction scheme, lists of candidate reagents, and the number of reagents desired for each dimension of a library, and from which they retrieve lists of reagents that encode for the optimized library. Internally, MapMaker enumerates the full virtual array, calculates the desired properties and coordinates in chemical space for the virtual compounds, and performs the optimization using a genetic algorithm. Consensus scoring following property calculation allows the system to optimize around an arbitrary number of computed properties, which are determined at run-time. Fig. 3. MapMaker is a combinatorial library optimization tool developed at ArQule, currently used in the design of screening libraries. The system is represented as a black box, since the details of operation are hidden by a web interface, to which chemists provide a reaction scheme, lists of candidate reagents, and the number of reagents desired for each dimension of a library, and from which they retrieve lists of reagents that encode for the optimized library. Internally, MapMaker enumerates the full virtual array, calculates the desired properties and coordinates in chemical space for the virtual compounds, and performs the optimization using a genetic algorithm. Consensus scoring following property calculation allows the system to optimize around an arbitrary number of computed properties, which are determined at run-time.

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