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Volumn 2, Issue 5, 2007, Pages 636-640

Chemical space travel

Author keywords

Cheminformatics; Drug design; Glutamate receptors; Structure generation

Indexed keywords

ARTICLE; CHEMICAL STRUCTURE; DRUG DESIGN; MUTATION;

EID: 48949083830     PISSN: 18607179     EISSN: 18607187     Source Type: Journal    
DOI: 10.1002/cmdc.200700021     Document Type: Article
Times cited : (63)

References (39)
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    • An analysis of the Beilstein database based on graphs was recently reported using known chemical reactions as links between compounds. K. J. M. Bishop, R. Klajn, B. A. Grzybowski, Angew. Chem. 2006, 118, 5474-5480;
    • An analysis of the Beilstein database based on graphs was recently reported using known chemical reactions as links between compounds. K. J. M. Bishop, R. Klajn, B. A. Grzybowski, Angew. Chem. 2006, 118, 5474-5480;
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    • Although a manually guided mutational algorithm was recently reported based on a few mutations similar to those in Table 1, a targeted travel from A to B was not demonstrated. E.-W. Lameijer, J. N. Kok, T. Bäck, A. P. IJzerman, J. Chem. Inf. Comput. Sci. 2006, 46, 545-552
    • Although a manually guided mutational algorithm was recently reported based on a few mutations similar to those in Table 1, a targeted travel from A to B was not demonstrated. E.-W. Lameijer, J. N. Kok, T. Bäck, A. P. IJzerman, J. Chem. Inf. Comput. Sci. 2006, 46, 545-552.
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    • The Tanimoto similarity coefficient, also called Jaccard index, compares two different bitstrings X and Y of the same length as the ratio of the number of bits set to 1 in X AND Y to the number of bits set to 1 in X OR Y, and varies from 0 (no similarity) to 1 (identity). For a review on chemical similarity searching and similarity measures see: P. Willett, J. M. Barnard, G. M. Downs, J. Chem. Inf. Comput. Sci. 1998, 38, 983-996.
    • The Tanimoto similarity coefficient, also called Jaccard index, compares two different bitstrings X and Y of the same length as the ratio of the number of bits set to 1 in X AND Y to the number of bits set to 1 in X OR Y, and varies from 0 (no similarity) to 1 (identity). For a review on chemical similarity searching and similarity measures see: P. Willett, J. M. Barnard, G. M. Downs, J. Chem. Inf. Comput. Sci. 1998, 38, 983-996.
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    • In the roulette wheel selection each compound c is assigned a pocket whose size is proportional to its fitness F(c) before applying the selection. Here we used F(c, TSF(target, c) x TPF(target, c, 5 to correct for the large number of compounds with very low values of TSF(target, c) x TPF(target, c) and allow the selection of mutants with intermediate fitness. Each mutant was selected only once during the entire process to avoid standstill. This strategy is implemented to avoid local minima in the optimisation process
    • PF(target, c) and allow the selection of mutants with intermediate fitness. Each mutant was selected only once during the entire process to avoid standstill. This strategy is implemented to avoid local minima in the optimisation process.
  • 29
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    • The mutation methods and the spaceship algorithm are written in java with the ChemAxon-package JChem. of ChemAxon Ltd. We used structural and pharmacophore fingerprints of the ChemAxon-package JChem. The pharmacophore fingerprint of ChemAxon is an analogue of the fingerprint described in ref. 12 but formulated as bit-string. For each target B the bit-length of the structural fingerprint was adapted to cover all possible substructures, with extension of the pathlength up to 26 bonds, corresponding to up to 6 221 600-bit length fingerprint, with a 1-14% density of 1 s. Most targets were not found when using a higher density of 1 s and shorter fingerprints, or when using only one of the two fingerprints
    • The mutation methods and the spaceship algorithm are written in java with the ChemAxon-package JChem. of ChemAxon Ltd. We used structural and pharmacophore fingerprints of the ChemAxon-package JChem. The pharmacophore fingerprint of ChemAxon is an analogue of the fingerprint described in ref. 12 but formulated as bit-string. For each target B the bit-length of the structural fingerprint was adapted to cover all possible substructures, with extension of the pathlength up to 26 bonds, corresponding to up to 6 221 600-bit length fingerprint, with a 1-14% density of 1 s. Most targets were not found when using a higher density of 1 s and shorter fingerprints, or when using only one of the two fingerprints.
  • 30
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    • Molecules with geometrically strained centres (for example, bridgehead double bonds) and unstable functional groups (for example, enols, enamines, acyl halide, geminal diols) were excluded. See ref. [3b-c].
    • Molecules with geometrically strained centres (for example, bridgehead double bonds) and unstable functional groups (for example, enols, enamines, acyl halide, geminal diols) were excluded. See ref. [3b-c].
  • 31
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    • All trajectories used at least one step with a structure from the roulette wheel selection, implying a new path and new mutants for each trajectory. Only compounds obeying the above mentioned chemical stability and synthetic feasibility criteria were retained. Saturation of chemical space between AMPA and CNQX was not reached even after 10 000 trajectories, producing a total of 2 065 209 unique molecules, illustrating how vast chemical space can be.
    • All trajectories used at least one step with a structure from the roulette wheel selection, implying a new path and new mutants for each trajectory. Only compounds obeying the above mentioned chemical stability and synthetic feasibility criteria were retained. Saturation of chemical space between AMPA and CNQX was not reached even after 10 000 trajectories, producing a total of 2 065 209 unique molecules, illustrating how vast chemical space can be.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.