Chemical Informatics: WOMBAT and WOMBAT-PK: Bioactivity Databases for Lead and Drug Discovery

Chemical Biology: From Small Molecules to Systems Biology and Drug Design, Volume 1-3

Volumn 2, Issue , 2008, Pages 760-786

  Olah, Marius ^a   Rad, Ramona ^a   Ostopovici, Liliana ^a   Bora, Alina ^a   Hadaruga, Nicoleta ^a   Hadaruga, Dan ^a   Moldovan, Ramona ^a   Fulias, Adriana ^a   Mractc, Maria ^a   Oprea, Tudor I ^a  

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

Author keywords

Heterocyclic backbone; Hormone receptors; Molar concentration; Receptor antagonists; Receptor subtype

Indexed keywords

EID: 84878771632     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9783527619375.ch13b     Document Type: Chapter

References (64)

1. Chemical Abstracts online and its search module, SeiFinder, are available from the American Chemical Society, http://www.cas.org/SCIFINDER/, 2006.
2. The Beilstein Information Systems is available from, http://www. beilstein.com/, 2006.
3. The Spresi Database is available from InfoChem GmbH, München, http://www.spresiweb.de/; and from Daylight Chemical Information Systems, http://www.daylight.com/products/databases/Spresi.html, 2006.
4. MDDR is available from MDL Information Systems, http://www.mdli.com/products/finders/database_finder/and from Prous Science Publishers, http://www.prous.com/index.html, 2006.
5. WDl. The Derwent World Drug Index, is available from Derwent Publications Ltd., http://thomsonderwent.com/products/lr/wdi/and from Daylight Chemical Information Systems, http://www.daylight.com/products/databases/WDI.html, 2006.
6. The Current Patents Fast Alert database is available from Current Patents Ltd., London, http://www.current-patents.com/, 2006.
7. The Comprehensive Medicinal Chemistry database is available from MDL Information Systems, Inc., http://www.mdli.com/products/knowledge/medicinaLchem/index.jsp, 2006.
8. DiscoveryGate is available from MDL Information Systems, Inc., http://www.mdli.com/products/knowledge/discoverygate/; a subset of DiscoveryGate is available through the PubChem system, see http://www.mdli.com/company/news/press_releases/2006/pr_pubchem_ 21mar06.jsp, 2006.
9. The PubChem database is available online at the National Center for Biotechnology Information, http://pubchem.ncbi.nlm.nih.gov/, 2006.
10. C.P. Austin, L.S. Brady, T.R. Insel, F.S Collins, NIH molecular libraries initiative, Science 2004, 306, 1138-1139.
11. The Physician Desk Reference is produced by Thomson Healthcare, 2003, ISBN 1-56363-472-4, and is available online at http://www. pdr.net/, 2006.
12. The DrugBank database is available at, http://redpoll.pharmacy.ualberta.ca/drugbank/, 2006.
13. M. Olah, M. Mracec, L. Ostopovici, R. Rad, A. Bora, N. Hadaruga, I. Olah, M. Banda, Z. Simon, M. Mracec, T.I. Oprea, WOMBAT: world of molecular bioactivity, in Cheminformatics in Drug Discovery, (Ed.: T.I. Oprea), Wiley-VCH, New York, 2005, 223-239.
14. T.I. Oprea, P. Benedetti, G. Berellini, M. Olah, K. Fejgin, S. Boyer, Rapid ADME filters for lead discovery, in Molecular Interaction Fields, (Ed.: G. Cruciani), Wiley-VCH, New York, 2006, 249-272.
15. WOMBAT and WOMBAT-PKare available from Sunset Molecular Discovery, Santa Fe, New Mexico, http://www.sunsetmolecular.com, 2006.
16. M. Olah, T.I Oprea, Bioactivity databases, in Comprehensive Medicinal Chemistry II, (Eds.: J. Taylor, D. Triggle), Elsevier, New York, 2006.
17. D. Weininger, SMILES 1. Introduction and encoding rules, J. Chem. Inf. Comput. Sei. 1988, 28, 31-36.
18. D. Weininger, A. Weininger, J.L. Weininger, SMILES 2. Algorithm for generation of unique SMILES notation, J. Chem. Inf. Comput. Sei. 1989, 29, 97-101.
19. The Enzyme Nomenclature is recommended by the International Union of Biochemistry and Molecular Biology, and is available at http://www.chem.qmul.ac.uk/iubmb/enzyme/, 2006.
20. Swiss-Prot Protein knowledgebase database, http://kr.expasy.org/sprot/, 2006.
21. C.A. Lipinski, F. Lombardo, B.W. Dominy, P.J Feeney, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv. Drug Delivery Rev. 1997, 23, 3-25.
22. oct from structures, Chem. Rev. 1993, 5, 1281-1306.
23. I.V. Tetko, V.Y Tanchuk, Application of associative neural networks for prediction of lipophilicity in ALOGPS 2.1 program, J. Chem. Inf. Comput. Sei. 2002, 42, 1136-1145, http://146.107.217.178/lab/alogps/index.html.
24. The Digital Object Identifier (DOI) is a system for identifying and exchanging intellectual property in the digital environment (http://www.doi.org/). An object is directly accessible using the customized address http://dx.doi.org/DOLVALUE, 2006.
25. Merck Index (13th edition), Merck & Co, Rahway NJ, 2001.
26. T.I. Oprea, M. Olah, L. Ostopovici, R. Rad, M. Mracec, in On the Propagation of Errors in the QSAR Literature in EuroQSAR 2002-Designing Drugs and Crop Protectants: Processes, Problems and Solutions, (Eds.: M. Ford, D. Livingstone, (. Dearden, H. Van de Waterbeemd), Blackwell Publishing, New York, 2003, 314-315.
27. ACDName is available from Advanced Chemistry Development Inc., Toronto, Ontario, CA, http://www.acdlabs.com.
28. G-protein coupled receptors are classified according to the GPCR nomenclature available at http://www.gpcr.org/7tm, whereas nuclear receptors are annotated based on the NR nomenclature available at http://www.receptors.org/NR, 2006.
29. E.J. Filardo, J.A. Quinn, K.I. Bland, A.R. Frackelton Jr, Estrogen-induced activation of Erk-I and Erk-2 requires the G protein-coupled receptor homolog, GPR30, and occurs via trans-activation of the epidermal growth factor receptor through release of HB-EGF, Mol. Endocrinol. 2000, 14, 1649-1660.
30. C.M. Revankar, D.F. Cimino, L.A. Sklar, J.B. Arterburn, E.R Prossnitz, A transmembrane intracellular estrogen receptor mediates rapid cell signaling, Science 2005, 307, 1625-1630.
31. N. Nidhi, M. Glick, J.W. Davies, J.L Jenkins, Prediction of biological targets for compounds using multiple-category Bayesian models trained on chemogenomics databases, J. Chem. Inf. Model. 2006, 46, 000-000.
32. T.I. Oprea, Cheminformatics in lead discovery, in Cheminformatics in Drug Discovery, (Ed.: T.I. Oprea), Wiley-VCH, New York, 2005, 27-42.
33. E.A. Coats, The CoMFA steroids as a benchmark dataset for development of 3D-QSAR methods, in 3D QSAR in Drug Design, Vol. 3, RecentAdvances, (Eds.: H. Kubinyi, G. Folkers, Y.C. Martin), Kluwer/ESCOM, Dordrecht, 1998, 199-213.
34. Q. Chen, C. Wu, D. Maxwell, G.A. Krudy, R.A.F. Dixon, T.J. You, A 3D-QSAR analysis of in vitro binding affinity and selectivity of 3-izoxazolylsulfonylaminothiophenes as endothelin receptor antagonists, Quant. Struct.-Act. Relat. 1999, 18, 124-133.
35. C. Wu, M.F. Chan, F. Stavros, B. Raju, I. Okun, S. Mong, K.M. Keller, T. Brock, T.P. Kogan, R.A Dixon, Discovery of TBCl 1251, a potent, long acting, orally active endothelin receptor-A selective antagonist, J. Med. Chem. 1997, 40, 1690-1697.
36. C. Wu, M.F. Chan, F. Stavros, B. Raju, I. Okun, R.S. Castillo, Structure-activity relationships of N2-aryl-3-(isoxazolylsulfamoyl)-2-thiophenecarboxamides as selective endothelin receptor-A antagonists, J. Med. Chem. 1997, 40, 1682-1689.
37. S.S. So, M. Karplus, Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 2. Applications, J. Med. Chem. 1997, 40, 4360-4371.
38. B.J. Burke, A.J. Hopfinger, 1-(Substituted-benzyl) imidazole-2(3H)thione inhibitors of dopamine /!-hydroxylase, J. Med. Chem. 1990, 33, 274-281.
39. A. Vedani, D.R. McMasters, M. Dobler, Multi-conformational ligand representation in 4D-QSAR: Reducing the bias associated with ligand alignment, Quant. Struct.-Act. Relat. 2000, 19, 149-161.
40. A.G.S. Blommaert, H. Dhotel, B. Ducos, C. Durieux, N. Goudreau, A. Bado, C. Garbay, B.P. Roques, Structure-based design of new constrained cyclic agonists of the cholecystokinin CCK-B receptor, J. Med. Chem. 1997, 40, 647-658.
41. T.I. Oprea, C.L. Waller, G.R. Marshall, 3D-QSAR of human immunodeficiency virus (I) protease inhibitors. II. Predictive power using limited exploration of alternate binding modes, J. Med. Chem. 1994, 37, 2206-2215.
42. A. Leo, Personal communication, 2004.
43. D. Abraham, Burger's Medicinal Chemistry (6th edn), Wiley-VCH, New York, 2003.
44. D. Abraham, Personal communication, 2004.
45. J.G. Hardman, L.E. Limbird, P.B. Molinoff, R.W. Ruddon, A.G. Gilman, Goodman (3/4 Gilman's the Pharmacological Basis of Therapeutics (9th edn), McGraw Hill, New York, 1996.
46. T.M. Speight, N.H.G. Holford, Avery's Drug Treatment (4th edn), Adis International, Auckland, 1997.
47. FDA labels are at the Center for Drug Evaluation and Research (CDER), website, http://www.accessdata.fda.gov/scripts/cder/drugsatfda/, 2006.
48. J.F. Contrera, E.J. Matthews, N.L. Kruhlak, R.D Benz, Estimating the safe starting dose in phase I clinical trials and no observed effect level based on QSAR modeling of the human maximum recommended daily dose, Regul. Toxicol. Pharmacol. 2004, 40, 185-206.
49. MRTD is available from the CDER, website, http://www.fda.gov/cder/Offices/OPSJO/MRTD.htm, 2006.
50. C. Hansch, A. Leo, D. Hoekman, Exploring QSAR, Vol. 2, ACS Publishers, Washington D.C., 1995.
51. The Sangster database is available at, http://logkow.cisti.nrc.ca/.
52. L.Z. Benet, Personal communication, 2006.
53. S. Andrieu, M. Lebret, J. Maclouf, F. Beverelli, J.F. Giudicelli, A. Berdeaux, Effects of antiaggregant and antiinflammatory doses of aspirin on coronary hemodynamics and myocardial reactive hyperemia in conscious dogs, J. Cardiovasc. Pharmacol. 1999, 33, 264-272.
54. D.G. Lloyd, G. Golfis, A.J.S. Knox, D. Fayne, M.J. Meegan, T.I Oprea, Oncology exploration: charting cancer medicinal chemistry space, Drug Discov. Today 2006, 11, 149-159.
55. M.M. Hann, A. Leach, D.V.S. Green, Computational chemistry, molecular complexity and screening set design, in Cheminformatics in Drug Discovery, (Ed.: T.I. Oprea), Wiley-VCH, New York, 2005, 43-57.
56. M.M. Hann, T.I Oprea, Pursuing the leadlikeness concept in pharmaceutical research, Curr. Opin. Chem. Biol. 2004, 8, 255-263.
57. R.A. Goodnow Jr, P. Gillespie, K. Bleicher, Cheminformatic tools for library design and the hit-to-lead process: a user's perspective, in Cheminformatics in Drug Discovery, (Ed.: T.I. Oprea), Wiley-VCH, New York, 2005, 381-435.
58. K.H. Baringhaus, H. Matter, Efficient strategies for lead optimization by simultaneously addressing affinity, selectivity and pharmacokinetic parameters, in Cheminformatics in Drug Discovery, (Ed.: T.I. Oprea), Wiley-VCH, New York, 2005, 333-379.
59. M. Congreve, R. Carr, C. Murray, H. Jhoti, A 'Rule of Three' for fragment-based lead discovery? Drug Discov. Today 2003, 8, 876-877.
60. T.I. Oprea, J. Blaney, Cheminformatics approaches to fragment-based lead discovery, in Fragment-based Approaches in Drug Discovery, (Eds.: W. Jahnke, D.A. Erlanson), Wiley-VCH, New York, 2006, 99-121.
61. V. Povolná, S. Dixon, D. Weininger, CABINET-Chemistry and biological informatics network, in Cheminformatics in Drug Discovery, (Ed.: T.I. Oprea), Wiley-VCH, New York, 2005, 241-269.
62. CABINET is available from Metaphorics LLC, Santa Fe, NM, http://cabinet.metaphorics.com/.
63. C. Hansch, D. Hoekman, A. Leo, D. Weininger, C.D. Selassie, C-QSAR database. Available from the BioByte Corporation, Claremont, CA, http://www.biobyte.com.
64. P. Furet, B. Gay, G. Caravatti, C. Garcia-Echeverria, J. Rahuel, J. Schoepfer, H. Fretz, Structure-based design and synthesis of high affinity tripeptide ligands of the Grb2-SH2 domain, J. Med. Chem. 1998, 41, 3442-3449.