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Combinatorial libraries optimization

Gillet VJ. Designing combinatorial libraries optimized on multiple objectives. Methods Mol Biol 2004 275 335-54. [Pg.375]

Designing Combinatorial Libraries Optimized on Multiple Objectives... [Pg.335]

Gillet, V. J. (2004) Designing combinatorial libraries optimized on multiple objectives in methods in molecular biology, in (Bajorath, J., ed.) Chemoinformatics Concepts, Methods, and Tools for Drug Discovery. Humana Press, Totowa, NJ, 275, pp. 335-354. [Pg.69]

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.
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]

Waldman M, Li H, Hassan M. Novel algorithms for the optimization of molecular diversity of combinatorial libraries. / Mo/ Graph Model 2000 18 412-26. [Pg.207]

Zheng W, Hung ST, Saunders JT, Seibel GL. PICCOLO a tool for combinatorial library design via multicriterion optimization. Pac Symp Biocomput 2000 588-99. [Pg.319]

Agraflotis DK. Multiobjective optimization of combinatorial libraries. Mol Divers 2002 5 209-30. [Pg.375]

Closely related to the use of PSA in virtual screening is its application in the design of combinatorial libraries with optimal properties. These applications are reviewed further in Refs. [46, 47], for example. [Pg.118]

Two main factors have guided the need for optimization of the early screening techniques on one hand the use of simple, quick and high-capacity cell monolayer methods, e.g., Caco-2 cell and MDCK and on the other hand the increased synthesis of more lipophilic, insoluble compounds from combinatorial libraries. This has created a vast number of different variants of cell-based assays and has resulted in variability among the data obtained. A need for optimization of as many as possible of the different parameters in order to increase the predictivity and throughput of the model has been suggested in the literature [98-100]. [Pg.108]

First the primary combinatorial library of chiral ligands LI —L5 and chiral activators Al —A5 (Scheme 12) were studied in order to optimize the lead structure of the next generation of chiral ligands and activators.87,89... [Pg.528]

Combinatorial chemistry, 7 380-434 8 400—401 13 283-284. See also High-throughput experimentation applications, 7 381-383 commercial environment, 7 387-389 methodology, 7 383-387 microwaves in, 16 548-552 nomenclature, 7 380 polymers, 7 405—413 Combinatorial libraries, 12 515-517 Combinatorial methods, 7 380 Combinatorial optimization approach, in computer-aided molecular design, 26 1037... [Pg.201]

Gillet, V.J., Willett, P., Bradshaw, J., and Green, D.V.S. Selecting combinatorial libraries to optimize diversity and physical properties. [Pg.197]

In general, reagent-based selection is much faster and more convenient to execute in the laboratory as compared with the product-based selection. On the other hand, the latter strategy usually provides more accurate results. There exists a potential to combine both approaches to achieve more optimal results, particularly in the case of large exploratory virtual combinatorial libraries, for which mass random synthesis and screening are not economically feasible. In this article, we demonstrated the usefulness of property-based approach for selection of optimal GPCR ligands. [Pg.310]


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See also in sourсe #XX -- [ Pg.217 , Pg.218 , Pg.219 , Pg.220 ]




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