Comparing the chemical spaces of metabolites and available chemicals: Models of metabolite-likeness

Molecular Diversity

Volumn 11, Issue 1, 2007, Pages 23-36

  Gupta, Sunil ^a   Aires de Sousa, João ^a  

^a DEPARTAMENTO DE QUÍMICA   (Portugal)

Author keywords

Chemical diversity; Chemoinformatics; Computer chemistry; Metabolism; Neural networks

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL REACTION KINETICS; CHEMICAL STRUCTURE; COMPARATIVE STUDY; DATA BASE; MATHEMATICAL COMPUTING; METABOLITE; MOLECULAR WEIGHT; PRIORITY JOURNAL; THREE DIMENSIONAL IMAGING;

BIODEGRADATION, ENVIRONMENTAL; COMPUTER SIMULATION; DATABASES, FACTUAL; METABOLISM; MODELS, CHEMICAL; MOLECULAR CONFORMATION; ORGANIC CHEMICALS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 34247345395     PISSN: 13811991     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11030-006-9054-0     Document Type: Article

References (32)

1. Kulkarni SA, Zhu J, Blechinger S (2005) In silico techniques for the study and prediction of xenobiotic metabolism: a review. Xenobiotica 35:955-973, and references therein
2. Ellis LBM, Roe D, Wackett LP (2006) The University of Minnesota biocatalysis/biodegradation database: the first decade. Nucleic Acids Res 34:D517-D521
3. Holliday GL, Bartlett GJ, Almonacid DE, O'Boyle NM, Murray-Rust P, Thornton JM, Mitchell JBO (2005) MACiE: a database of enzyme reaction mechanisms. Bioinformatics 21:4315-4316
4. Reitz M, Sacher O, Tarkhov A, Trümbach D, Gasteiger J (2004) Enabling the exploration of biochemical pathways. Org Biomol Chem 2:3226-3237
5. Hattori M, Okuno Y, Goto S, Kanehisa M (2003) Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. J Am Chem Soc 125:11853-11865
6. Nobeli I, Ponstingl H, Krissinel EB, Thornton JM (2003) A structure-based anatomy of E. coli metabolome. J Mol Biol 334:697-719
7. Latino DARS, Aires-de-Sousa J (2006) Genome-scale classification ofmetabolic reactions: a chemoinformatics approach. Angew Chem Int Ed 45:2066-2069
8. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32:D277-D280
9. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M (2006) From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 34:D354-D357
10. Irwin JJ, Shoichet BK (2005) ZINC - a free database of commercially available compounds for virtual screening. J Chem Inf Comput Sci 45:177-182
11. Henkel T, Brunne RM, Muller H, Reichel F (1999) Statistical investigation into the structural complementarity of natural products and synthetic compounds. Angew Chem Int Ed Engl 38:643-647
12. Stahura FL, Jeffrey WG, Xue L, Bajorath J (2000) Distinguishing between natural products and synthetic molecules by descriptor Shannon entropy analysis and binary QSAR calculations. J Chem Inf Comput Sci 40:1245-1252
13. Lee M-L, Schneider G (2001) Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries. J Comb Chem 3:284-289
14. Feher M, Schmidt JM (2003) Property distributions: differences between drugs, natural products, and molecules from combinatorial chemistry. J Chem Inf Comput Sci 43:218-227
15. Koch MA, Schuffenhauer A, Scheck M, Wetzel S, Casaulta M, Odermatt A, Ertl P, Waldmann H (2005) Charting biologically relevant chemical space: a structural classification of natural products (SCONP). Proc Natl Acad Sci USA 102:17272-17277
16. Karakoc E, Sahinalp SC, Cherkasov A (2006) Comparative QSAR and fragments distribution analysis of drugs, druglikes, metabolic substances, and antimicrobial compounds. J Chem Inf Model 46:2167-2182
17. Cherkasov A (2006) Can 'bacterial-metabolitelikeness' model improve odds of 'in silico' antibiotic discovery? J Chem Inf Model 46:1214-1222
18. Kohonen T (1989) Self-organization and associative memory, 3rd edn. Springer, Berlin Heidelberg New York
19. Breiman L (2001) Random forests. Mach Learn 45:5-32
20. Breiman L, Friedman JH, Olshen RA, Stone CJ (2000) Classification and regression trees. Chapman & Hall/CRC, Boca Raton
21. Hemmer MC, Steinhauer V, Gasteiger J (1999) The prediction of the 3D structure of organic molecules from their infrared spectra. Vib Spectrosc 19:151-164
22. Organisation for Economic Co-operation and Development. http://www.oecd.org
23. PETRA can be tested on the website http://www2.chemie.uni-erlangen.de and is developed by Molecular Networks GmbH (Erlangen, Germany). http://www.mol-net.de
24. National Institute of Technology and Evaluation, Japan. http://www.safe.nite.go.jp/english/db.html
25. CORINA software is available from Molecular Networks GmbH (Erlangen, Germany). http://www.mol-net.de
26. Aires-de-Sousa J (2002) Java tools for neural networks. Chemometrics Intell Lab Syst 61:167-173
27. The JATOON applets are available at http://www.dq.fct.unl.pt/staff/jas/ jatoon
28. Svetnik V, Liaw A, Tong C, Culberson JC, Sheridan RP, Feuston BP (2003) Random forest: a classification and regression tool for compound classification and QSAR modeling. J Chem Inf Comput Sci 43:1947-1958
29. R Development Core Team (2004) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.org
30. Fortran original by Breiman L, Cutler A, R port by Liaw A, Wiener M (2004)
31. Zupan J, Gasteiger J (1999) Neural networks in chemistry and drug design, 2nd edn. Wiley-VCH, Weinheim
32. Dobson CM (2004) Chemical space and biology. Nature 432:824-828