Searching fragment spaces with feature trees

Journal of Chemical Information and Modeling

Volumn 49, Issue 2, 2009, Pages 270-279

  Lessel, Uta ^a   Wellenzohn, Bernd ^a   Lilienthal, Markus ^b   Claussen, Holger ^b  

^a BOEHRINGER INGELHEIM PHARMA GMBH AND CO KG   (Germany)

^b BioSolveIT GmbH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BIOCHIPS;

COMBINATORIAL CHEMISTRY; COMBINATORIAL LIBRARY; MACHINE READABLE FORM; ORDERS OF MAGNITUDE; PHARMACEUTICAL COMPANY; TIME CONSUMING ANALYSIS; VIRTUAL PRODUCTS; VIRTUAL SCREENING;

ENCODING (SYMBOLS);

ARTICLE; COMBINATORIAL CHEMISTRY; INFORMATION RETRIEVAL;

COMBINATORIAL CHEMISTRY TECHNIQUES; INFORMATION STORAGE AND RETRIEVAL;

EID: 65249124650     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci800272a     Document Type: Article

References (28)

1. Villar, H. O.; Koehler, R. T. Comments on the design of chemical libraries for screening. Mol. Diversity 2000, 5, 13-24.
2. Nikitin, S.; Zaitseva, N.; Demina, O.; Solovieva, V.; Mazin, E.; Mikhalev, S.; Smolov, M.; Rubinov, A.; Vlasov, P.; Lepikhin, D.; Khachko, D.; Fokin, V.; Queen, C.; Zosimov, V. A very large diversity space of synthetically accessible compounds for use with drug design programs. J. Comput.-Aided Mol. Des. 2005, 19, 47-63.
3. Rarey, M.; Stahl, M. Similarity searching in large combinatorial chemistry spaces. J. Comput.-Aided Mol. Des. 2001, 15, 497-520.
4. Ertl, P. Chemoinformatics analysis of organic substituents: identification of the most common substituents, calculation of substituent properties, and automatic identification of drug-like bioisosteric groups. J. Chem. Inf. Comput. Sci. 2003, 43, 374-380.
5. Bohacek, R. S.; McMartin, C.; Guida, W. C. The art and practice of structure-based drug design: a molecular modeling perspective. Med. Res. Rev. 1996, 16, 3-50.
6. Walters, P. W.; Stahl, M. T.; Murcko, M. A. Virtual screening - an overview. Drug Discovery Today 1998, 3, 160-178.
7. Gorse, A.-D. Diversity in medicinal chemistry space. Curr. Top. Med. Chem. 2006, 6, 3-18.
8. Lewell, X. Q.; Judd, D. B.; Watson, S. P.; Hann, M. M. RECAP -Retrosynthetic combinatorial analysis procedure: A powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J. Chem. Inf. Comput. Sci. 1998, 38, 511-522.
9. Schürer, S. C.; Tyagi, P.; Muskal, S. M. Prospective exploration of synthetically feasible, medicinally relevant chemical space. J. Chem. Inf. Model. 2005, 45, 239-248.
10. Hartenfeller, M.; Proschak, E.; Schüller, A.; Schneider, G. Concept of Combinatorial De Novo Design of Drug-like Molecules by Particle Swarm Optimization. Chem. Biol. Drug Des. 2008, 72, 16-26.
11. Degen, J.; Rarey, M. ELEXNovo: structure-based searching in large Fragment Spaces. ChemMedChem 2006, 1, 854-868.
12. Cramer, R. D.; Patterson, D. E.; Clark, R. D.; Soltanshahi, F.; Lawless, M. S. Virtual compound libraries: a new approach to decision making in molecular discovery research. J. Chem. Inf. Comput. Sci. 1998, 38, 1010-1023.
13. Andrews, K. M.; Cramer, R. D. Towards general methods of targeted library design: Topomer shape similarity searching with diverse structures as queries. J. Med. Chem. 2000, 43, 1723-1740.
14. 20 synthetically accessible structures. J. Comput.-Aided Mol. Des. 2007, 21, 341-350.
15. Jilik, R. J.; Cramer, R. D. Topomers: a validated protocol for their self-consistent generation. J. Chem. Inf. Comput. Sci. 2004, 44, 1221-1227.
16. Boehm, M.; Wu, T.-Y.; Claussen, H.; Lemmen, C. Similarity Searching and Scaffold Hopping in Synthetically Accessible Combinatorial Chemistry Spaces. J. Med. Chem. 2008, 51, 2468-2480.
17. Rarey, M.; Dixon, J. S. Feature trees: a new molecular similarity measure based on tree matching. J. Comput.-Aided Mol. Des. 1998, 12, 471-490.
18. FTrees, version 2.0.2; BioSolveIT GmbH: Sankt Augustin, Germany, 2008.
19. Good, A. C.; Hermsmeier, M. A.; Hindle, S. A. Measuring CAMD technique performance: A virtual screening case study in the design of validation experiments. J. Comput. -Aided Mol. Des. 2004, 18, 529-536.
20. CoLibri, version 1.1.4; BioSolveIT GmbH: Sankt Augustin, Germany, 2008.
21. Hessler, G.; Zimmermann, M.; Matter, H.; Evers, A.; Naumann, T.; Lengauer, T.; Rarey, M. Multiple-ligand-based virtual screening: methods and applications of the MTree approach. J. Med. Chem. 2005, 48, 6575-6584.
22. Callahan, J. F.; Burgess, J. L.; Fornwald, J. A.; Gaster, L. M.; Harling, J. D.; Harrington, F. P.; Heer, J.; Kwon, C.; Lehr, R.; Mathur, A.; Olson, B. A.; Weinstock, J.; Laping, N. J. Identification of Novel Inhibitors of the Transforming Growth Factor β1 (TGF-β1) Type 1 Receptor (ALK5). J. Med. Chem. 2002, 45, 999-1001.
23. Sawyer, J. S.; Anderson, B. D.; Beight, D. W.; Campbell, R. M.; Jones, M. L.; Herro, D. K.; Lampe, J. W.; McCowan, J. R.; McMillen, W. T.; Mort, N.; Parsons, S.; Smith, E. C. R.; Vieth, M.; Weir, L. C.; Yan, L.; Zhang, F.; Yingling, J. M. Synthesis and Activity of New Aryl- and Heteroaryl-Substituted Pyrazole Inhibitors of the Transforming Growth Factor-β Type I Receptor Kinase Domain. J. Med. Chem. 2003, 46, 3953-3956.
24. Singh, J.; Chuaqui, C. E.; Boriack-Sjodin, P. A.; Lee, W. C.; Pontz, T.; Corbley, M. J.; Cheung, H. K.; Arduini, R. M.; Mead, J. N.; Newman, M. N.; Papadatos, J. L.; Bowes, S.; Josiah, S.; Ling, L. E. Successful Shape-Based Virtual Screening: The Discovery of a Potent Inhibitor of the Type I TGFβ Receptor Kinase (TβRI). Bioorg. Med. Chem. Lett. 2003, 13, 4355-4359.
25. Structures taken from Scios-Patents WO2004/010929 A2, WO 2004/ 047818A2, WO 2004/048930 A2, WO 2004/087056 A2, WO 2005/ 032481 A2.
26. ROCS, version 2.3.1; OpenEye Scientific Software, Inc: Santa Fe, NM, 2007.
27. Symyx Technologies, Inc. CTFile Formats, November 2007. http:// www.mdl.com/downloads/public/ctfile/ctfile.pdf (accessed Dec 17, 2008).
28. Weininger, D.; Weininger, A.; Weininger, J. L. SMILES. 2. Algorithm for Generation of Unique SMILES Notation. J. Chem. Inf. Comput. Sci. 1989, 29, 97-101.