Quantifying the relationships among drug classes

Journal of Chemical Information and Modeling

Volumn 48, Issue 4, 2008, Pages 755-765

  Hert, Jérôme ^a   Keiser, Michael J ^a   Irwin, John J ^a   Oprea, Tudor I ^b   Shoichet, Brian K ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF NEW MEXICO SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; BIOINFORMATICS; LIGANDS;

CHEMICAL REPRESENTATION; CHEMOINFORMATICS METRICS,; DRUG TARGETS;

DRUG PRODUCTS;

DRUG; LIGAND;

ARTICLE; BAYES THEOREM; CHEMICAL STRUCTURE; CHEMISTRY; CLASSIFICATION;

BAYES THEOREM; LIGANDS; MOLECULAR STRUCTURE; PHARMACEUTICAL PREPARATIONS;

EID: 44449159422     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci8000259     Document Type: Article

References (43)

1. Izrailev, S.; Farnum, M. A. Enzyme classification by ligand binding. Proteins: Struct., Funct., Bioinf. 2004, 57, 711-724.
2. Vieth, M.; Higgs, R. E.; Robertson, D. H.; Shapiro, M.; Gragg, E. A.; Hemmerle, H. Kinomics-structural biology and chemogenomics of kinase inhibitors and targets. Biochim. Biophys. Acta 2004, 1697, 243-257.
3. Paolini, G. V.; Shapland, R. H. B.; van Hoorn, W. P.; Mason, J. S.; Hopkins, A. L. Global Mapping of Pharmacological Space. Nat. Biotechnol. 2006, 24, 805-815.
4. Keiser, M. J.; Roth, B. L.; Armbruster, B. N.; Ernsberger, P.; Iriwin, J. J.; Shoichet, B. K. Relating Protein Pharmacology by Their Ligands. Nat. Biotechnol. 2007, 25, 197-206.
5. Johnson, M. A.; Maggiora, G. M. Concepts and Applications of Molecular Similarity; John Wiley: New York, 1990.
6. Frye, S. V. Structure-activity relationship homology (SARAH): a conceptual framework for drug discovery in the genomic era. Chem. Biol. 1999, 6, R3-R7.
7. Bredel, M.; Jacoby, E. Chemogenomics: an emerging strategy for rapid target and drug discovery. Nat. Rev. Genet. 2004, 5, 262-275.
8. Nidhi; Glick, M.; Davies, J. W.; Jenkins, J. L. Prediction of biological targets for compounds using multiple-category Bayesian models trained on chemogenomics databases. J. Chem. Inf. Model. 2006, 46, 1124-1133.
9. The MDL Drug Data Report Database is available from MDL Information Systems, Inc. at http://mdl.com (accessed Feb 2008).
10. Olah, M.; Mracec, M.; Ostopovici, L.; Rad, R.; Bora, A., Hadaruga, N., Olah, I.; Banda, M.; Simon, Z., Mracec, M.; Oprea, T. I. WOMBAT: World of Molecular Bioactivity. In Chemoinformatics in Drug Discovery; Oprea, T. I., Ed.; Wiley-VCH: New York, 2004; pp 223-239.
11. Schuffenhauer, A.; Zimmermann, J.; Stoop, R.; van der Vyver, J. J.; Lecchini, S.; Jacoby, E. An Ontology for Pharmaceutical Ligands and Its Application for in Silico Screening and Library Design. J. Chem. Inf. Model. 2002, 42, 947-955.
12. The Daylight Toolkit is available from Daylight, Inc. at http://www.daylight.com (accessed Oct 2007).
13. Unity is available from Tripos, Inc. at http://www.tripos.com (accessed Feb 2008).
14. Durant, J. L.; Leland, B. A.; Henry, D. R.; Nourse, J. G. Reoptimization of MDL Keys for Use in Drug Discovery. J. Chem. Inf. Model. 2002, 42, 1273-1280.
15. Pipeline Pilot is available from SciTegic, Inc. at http://www.scitegic. com (accessed Feb 2008).
16. Fechner, U.; Franke, L.; Renner, S.; Schneider, P.; Schneider, G. Comparison of correlation vector methods for ligand-based similarity searching. J. Comput.-Aided Mol. Des. 2003, 17, 687-698.
17. Schneider, G.; Neidhart, W.; Giller, T.; Schmid, G. "Scaffold- Hopping" by Topological Pharmacophore Search: A Contribution to Virtual Screening. Angew. Chem., Int. Ed. 1999, 38, 2894-2896.
18. Jenkins, J. L.; Glick, M.; Davies, J. W. A 3D Similarity Method for Scaffold Hopping from Known Drugs or Natural Ligands to New Chemotypes. J. Med. Chem. 2004, 47, 6144-6159.
19. Hert, J.; Willett, P.; Wilton, D. J.; Acklin, P.; Azzaoui, K.; Jacoby, E.; Schuffenhauer, A. Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures. Org. Biomol. Chem. 2004, 2, 3256-3266.
20. Willett, P.; Barnard, J. M.; Downs, G. M. Chemical Similarity Searching. J. Chem. Inf. Comput. Sci. 1998, 38, 983-996.
21. Altschul, S. F.; Gish, W.; Miller, W.; Myers, E. W.; Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403-410.
22. Karlin, S.; Altschul, S. F. Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc. Natl. Acad. Sci. U.S.A. 1990, 87, 2264-2268.
23. Pearson, W. R. Empirical statistical estimates for sequence similarity searches. J. Mol. Biol. 1998, 276, 71-84.
24. Avidon, V. V.; Arolovich, V. S.; Kozlova, S. P.; Piruzyan, L. A. Statistical Study of Information File on Biologically Active Compounds. II. Choice of Decision Rule for Biological Activity Prediction. Khim. Farm. Zh. 1978, 12, 88-93.
25. Hert, J.; Willett, P.; Wilton, D. J.; Acklin, P.; Azzaoui, K.; Jacoby, E.; Schuffenhauer, A. New methods for ligand-based virtual screening: use of data fusion and machine learning to enhance the effectiveness of similarity searching. J. Chem. Inf. Model. 2006, 46, 462-470.
26. Xia, X.; Maliski, E. G.; Gallant, P.; Rogers, D. Classification of kinase inhibitors using a Bayesian model. J. Med. Chem. 2004, 47, 4463-4470.
27. Sheskin, D. J. Handbook of Parametric and Nonparametric Statistical Procedures, 3rd ed.; Chapman & Hall/CRC: Boca Raton, FL, 2003.
28. Altschul, S. F.; Madden, T. L.; Schaffer, A. A.; Zhang, J.; Zhang, Z.; Miller, W.; Lipman, D. J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acid Res. 1997, 25, 3389-3402.
29. Siegel, S.; Castellan, N. J. Nonparametric Statistics for the Behavioral Sciences; Mc-Graw Hill: New York, 1988.
30. Grigorov, M. G. Global properties of biological networks. Drug Discovery Today 2005, 10, 365-372.
31. Watts, D. J.; Strogatz, S. H. Collective dynamics of 'small-world' networks. Nature 1998, 393, 440-442.
32. Vendruscolo, M.; Dokholyan, N. V.; Paci, E.; Karplus, M. Smallworld view of the amino acids that play a key role in protein folding. Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys. 2002, 65, 061910.
33. Albert, R.; Barabási, A.-L. Statistical mechanics of complex networks. Rev. Mod. Phys. 2002, 74, 47.
34. Barabási, A.-L.; Réka, A. Emergence of Scaling in Random Networks. Science 1999, 286, 509-512.
35. Greene, L. H.; Higman, V. A. Uncovering network systems within protein structures. J. Mol. Biol. 2003, 334, 781-791.
36. Arita, M. The metabolic world of Escherichia coli is not small. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 1543-1547.
37. Amaral, L. A. N.; Scala, A.; Barthélémy, M.; Stanley, H. E. Classes of small-world networks. Proc. Natl. Acad. Sci. U.S.A. 2000, 97, 11149-11152.
38. Zhang, Z.; Grigorov, M. G. Similarity networks of protein binding sites. Proteins: Struct., Funct., Bioinf. 2006, 62, 470-478.
39. Nettles, J. H.; Jenkins, J. L.; Bender, A.; Deng, Z.; Davies, J. W.; Glick, M. Bridging chemical and biological space: "target fishing" using 2D and 3D molecular descriptors. J. Med. Chem. 2006, 49, 6802-6810.
40. Adamic, L. A.; Lukose, R. M.; Puniyani, A. R.; Huberman, B. A. Search in power-law networks. Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys. 2001, 64, 046135.
41. Yook, S.-H.; Jeong, H.; Barabási, A.-L. Modeling the Internet's largescale topology. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 13382-13386.
42. Barabási, A.-L.; Jeong, H.; Neda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T. Evolution of the social network of scientific collaborations. Physica A 2002, 311, 590-614.
43. Kogut, B.; Walker, G. The Small World of Germany and the Durability of National Networks. Am. Sociol. Rev. 2001, 66, 317-335.