Structure activity relationships (SAR) and pharmacophore discovery using Inductive Logic Programming (ILP)

QSAR and Combinatorial Science

Volumn 22, Issue 5, 2003, Pages 527-532

  Sternberg, Michael J E ^a   Muggleton, Stephen H ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Drug Design; Machine Learning; Structure Activity Relationship

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER CIRCUITS; INDUCTIVE LOGIC PROGRAMMING (ILP); PHARMACODYNAMICS;

DRUG DESIGN; INDUCTIVE LOGIC; LOGIC-PROGRAMMING; MACHINE-LEARNING; PHARMACOPHORES; STRUCTURAL SUPERPOSITIONS; STRUCTURE-ACTIVITY RELATIONSHIPS;

LEARNING SYSTEMS;

ARTICLE; CHEMICAL STRUCTURE; LOGIC; MOLECULAR MODEL; PHARMACOPHORE; PRIORITY JOURNAL; STRUCTURE ACTIVITY RELATION; STRUCTURE ANALYSIS; SYSTEM ANALYSIS;

EID: 0042672725     PISSN: 1611020X     EISSN: None     Source Type: Journal    
DOI: 10.1002/qsar.200310005     Document Type: Article

References (30)

1. Marshall, G. R., and Cramer, R. D., Trends Pharm. Sci., 9, 285-289 (1988).
2. Debnath, A. K., Lopez de Compadre, R. L., Debnath, G., Shusterman, A. J., and Hansch, C., J. Med. Chem., 34, 786-797 (1991).
3. Cramer, R. D., Patterson, D. E., and Bunce, J. D., J. Am. Chem. Soc., 110, 5959-5967 (1988).
4. Klebe, G., Abraham, U., and Mietzner, T., J. Med. Chem., 37, 4130-4146 (1994).
5. Klebe, G., J. Mol. Med., 78, 269-281 (2000).
6. Livingstone, D. j., J. Chem. Inf. Comput. Sci., 40, 195-209 (2000).
7. Winkler, D. A., Briefings in Bioinformatics, 3, 73-86 (2002).
8. King, R. D., Muggleton, S., Lewis, R. A., and Sternberg, M. J. E., Proc. Nat. Acad. Sci. USA, 89, 11322-11326 (1992).
9. King, R. D., Muggleton, S. H., Srinivasan, A., and Sternberg, M. J. E., Proc. Nat. Acad. Sci. USA, 93, 438-442 (1996).
10. Hansch, C., Acc. Chem. Res., 2, 232-239 (1969).
11. Aoyama, T., Suzuki, Y., and Ichikawa, H., J. Med. Chem., 33, 2583-2590 (1990).
12. Brint, A. T., and Willett, P., J. Mol. Graph., 5, 49-56 (1987).
13. Willett, P., J. Mol. Recognit., 8, 290-303 (1995).
14. Brown, N., Willett, P., Wilton, D. J., and Lewis, R. A., J. Chem. Inf. Comput. Sci., 43, 288-297 (2003).
15. Barnum, D., Greene, J., Smellie, A., and Sprague, P., J. Chem. Inf. Comput. Sci., 36, 563-571 (1996).
16. Muggleton, S. H., Inductive Logic Programming. Academic Press, 1992.
17. Muggleton, S. H., Artficial Intelligence, 114, 283-296 (1999),
18. Mitchell, T., Machine Learning. McGraw Hill, 1997.
19. Muggleton, S. H., and Feng, C., in Inductive Logic Programming, S. H. Muggleton, ed., Academic Press, 1992, pp 281-298.
20. Muggleton, S., New Generation Computing Journal, 13, 245-286 (1995).
21. Hansch, C., Li, R.-I., Blaney, J. M., and Langridge, R., J. Med. Chem., 25, 777-784 (1982).
22. Roth, B., Rauckman, B. S., Ferone, R., Baccanari, D. P., Champness, J. N., and Hyde, R. M., J. Med. Chem., 30, 348-356 (1987).
23. Hirst, J. D., King, R. D., and Sternberg, M. J. E., J. Comp. Aided. Mol. Design, 8, 405-420 (1994).
24. Hirst, J. D., King, R. D., and Sternberg, M. J. E., J. Comp. Aided. Mol. Design, 8, 421-432 (1994).
25. Villemin, D., Cherqaoui, D., and Cense, J. M., J. Chim. Phys., 90, 1505-1519 (1993).
26. Breiman, L., Friedman, J. H., and Olshen, R. A., Classification and Regression Trees. Wadsworth, Belmont, 1984.
27. Finn, P., Muggleton, S. H., Page, D., and Srinivasan, A., Machine Learning, 30, 241-271 (1998).
28. Mayer, D., Naylor, C., Motoc, I., and Marshall, G., J. Comput. Aided Mol. Design, 1, 3-16 (1987).
29. Bohacek, R., Lombaert, S. D., McMartin, C., Priestle, J., and Grutter, M. J. Am. Chem. Soc., 118, 8231-8249 (1996).
30. Marchand-Geneste, N., Watson, K. A., Alsberg, B. K., and King, R. D., J. Med. Chem., 45, 399-409 (2002).