G-protein-coupled receptor affinity prediction based on the use of a profiling dataset: QSAR design, synthesis, and experimental validation

Journal of Medicinal Chemistry

Volumn 48, Issue 21, 2005, Pages 6563-6574

  Rolland, Catherine ^a   Gozalbes, Rafael ^a   Nicolaï, Eric ^a   Paugam, Marie France ^a   Coussy, Laurent ^a   Barbosa, Frédérique ^a   Horvath, Dragos ^a,b   Revah, Frédéric ^a  

^a CEREP   (France)

^b CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

G PROTEIN COUPLED RECEPTOR; JP 2002138080; NEW DRUG; SNAP 7941; T 22696; UNCLASSIFIED DRUG; UNINDEXED DRUG; US 2003018022; US 6387932; US 6511994; WO 0023420; WO 0046203; WO 0061587; WO 0110842; WO 0138305; WO 0157023; WO 0162758; WO 0170731; WO 0177087; WO 0179209; WO 018578; WO 0202530; WO 02069905; WO 02102787; WO 0213824; WO 0215909; WO 0250019; WO 0257230; WO 0258702; WO 0260859; WO 0262423; WO 0274763; WO 03009847; WO 03013509; WO 03014110; WO 03015769; WO 03018556; WO 03020716; WO 03022277; WO 03024401; WO 03033476; WO 03040125; WO 03045313; WO 03045917; WO 03045926; WO 03048154; WO 03051839; WO 03053927; WO 03057676; WO 03066597; WO 03068281; WO 03068759; WO 03072545; WO 03075853; WO 03077907; WO 03078421; WO 03084954; WO 03087089; WO 03090677; WO 03091245; WO 03094918; WO 03099798; WO 03105853; WO 04002987; WO 04004714; WO 04004726; WO 04004731; WO 04005257; WO 04007472; WO 04011438; WO 04011440; WO 2089785; WO 9856771;

ARTICLE; BINDING AFFINITY; DRUG DESIGN; DRUG DETERMINATION; DRUG RECEPTOR BINDING; DRUG STRUCTURE; DRUG SYNTHESIS; PREDICTION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STRUCTURE ANALYSIS; VALIDATION PROCESS;

COMBINATORIAL CHEMISTRY TECHNIQUES; DRUG DESIGN; LIGANDS; MODELS, MOLECULAR; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RADIOLIGAND ASSAY; RECEPTORS, CHEMOKINE; RECEPTORS, G-PROTEIN-COUPLED; RECEPTORS, PEPTIDE;

EID: 27144503431     PISSN: 00222623     EISSN: None     Source Type: Journal    
DOI: 10.1021/jm0500673     Document Type: Article

References (26)

1. Drews, J. Drug discovery: A historical perspective. Science 2000, 287, 1960-1964.
2. Klabunde T.; Hessler G. Drug design strategies for targeting G-protein-coupled receptors. ChemBioChem 2002, 3 (10), 928-944.
3. Probst W. C.; Snyder L. A.; Schuster D. I.; Brosius J.; Sealfon S. C. Sequence alignment of the G-protein coupled receptor superfamily. DNA Cell. Biol. 1992, 11 (1), 1-20.
4. Joost, P.; Methner, A. Phylogenetic analysis of 277 human G-protein-coupled receptors as a tool for the prediction of orphan receptor ligands. Genome Biol. 2002, 3 (11), 0063.1-0063.16. (http://genomebiology.com/ 2002/3/11/research/0063).
5. Palczewski, K.; Kumasaka, T.; Hori, T.; Behnke, C. A.; Motoshima, H.; Fox, B. A.; Le Trong, I.; Teller, D. C.; Okada, T.; Stenkamp, R. E.; Yamamoto, M.; Miyano, M. Crystal structure of rhodopsin: A G protein-coupled receptor. Science 2000, 289 (5480), 739-745.
6. Becker, O. M.; Shacham, S.; Marantz, Y.; Noiman, S. Modeling the 3D structure of GPCRs: Advances and application to drug discovery. Curr. Opin. Drug Discov. Devel. 2003, 6(3), 353-361.
7. Bissantz, C.; Bernard, Ph.; Hibert, M.; Rognan, D. Protein-based virtual screening of chemical databases. II. Are homology models of G-protein coupled receptors suitable targets? Proteins 2003, 50 (1), 5-25.
8. Archer, E.; Maigret, B.; Escrieut, Ch.; Pradayrol, L.; Fourmy, D. Rhodopsin crystal: new template yielding realistic models of G-protein-coupled receptors? Trends Pharmacol. Sci. 2003, 24 (1), 36-40.
9. Krejsa, C. M.; Horvath, D.; Rogalski, S. L.; Penzotti, J. E.; Mao, B.; Barbosa, F.; Migeon, J. C. Predicting ADME properties and side effects: the BioPrint approach. Curr. Opin. Drug Discovery Dev. 2003, 6 (4), 470-480.
10. Gozalbes, R.; Barbosa, F.; Froloff, N.; Horvath, D. The BioPrint approach for the evaluation of ADME-T properties: Application to the prediction of cytochrome P450 2D6 inhibition. Proceedings of the LogP symposium, 2004, submitted.
11. Horvath, D. High throughput conformational sampling and fuzzy similarity metrics: a novel approach to similarity searching and focused combinatorial library design and its role in the drug discovery laboratory. In Combinatorial Library Design and Evaluation: Principles, Software Tools and Applications in Drug Discovery; Ghose, A., Viswanadhan, V., Eds.; Marcel Dekker: New York, 2001; pp 429-472.
12. Horvath, D.; Jeandenans, C. Neighborhood behavior of in silico structural spaces with respect to in vitro activity spaces - A novel understanding of the molecular similarity principle in the context of multiple receptor binding profiles. J. Chem. Inf. Comput. Sci. 2003, 43 (2), 680-690.
13. Horvath, D.; Jeandenans, C. Neighborhood behavior of in silico structural spaces with respect to in vitro activity spaces-A benchmark for neighborhood behavior assessment of different in silico similarity metrics. J. Chem. Inf. Comput. Sci. 2003, 43 (2), 691-698.
14. Todeschini, R.; Consonni, V. In Handbook of Molecular Descriptors; Mannhold, R., Kubinyi, H., Timmerman, H., Eds.; Wiley-VCH: 2000, 464-466.
15. Oprea, TI. Chemical space navigation in lead discovery. Curr. Opin. Chem. Biol. 2002, 6 (3), 384-389.
16. Patterson, D. E.; Cramer, R. D.; Ferguson, A. M.; Clark, R. D.; Weinberger, L. E. Neighborhood behavior: A useful concept for validation of "molecular diversity" descriptors. J. Med. Chem. 1996, 39, 9 (16), 3049-3059.
17. Holenz, J.; Merce, R.; Diaz, J. L.; Guitart, X.; Codony, X.; Dordal, A.; Romero, G.; Torrens, A.; Mas, J.; Andaluz, B.; Hernandez, S.; Monroy, X.; Sanchez, E.; Hernandez, E.; Perez, R.; Cubi, R.; Sanfeliu, O.; Buschmann, H. Medicinal chemistry driven approaches toward novel and selective serotonin 5-HT6 receptor ligands. J. Med. Chem. 2005, 48 (6), 1781-1795.
18. Moro, S.; Braiuca, P.; Deflorian, F.; Ferrari, C.; Pastorin, G.; Cacciari, B.; Baraldi, P. G.; Varani K.; Borea, P. A.; Spalluto, G. Combined target-based and ligand-based drug design approach as a tool to define a novel 3D-pharmacophore model of human A3 adenosine receptor antagonists: Pyrazolo[4,3-e]1,2,4-triazolo[l,5-c]pyrimidine derivatives as a key study. J. Med. Chem. 2005, 48 (1), 152-162.
19. Evers, A.; Klebe, G. Successful virtual screening for a submicromolar antagonist of the neurokinin-1 receptor based on a ligand-supported homology model. J. Med. Chem. 2004, 47 (22), 5381-5392.
20. Sun, H.; Greeley, D. N.; Chu, X. J.; Cheung, A.; Danho, W.; Swistok, J.; Wang, Y.; Zhao, C.; Chen, L.; Fry, D. C. A predictive pharmacophore model of human melanocortin-4 receptor as derived from the solution structures of cyclic peptides. Bioorg. Med. Chem. 2004, 12 (10), 2671-2677.
21. Bondensgaard, K.; Ankersen, M.; Thøgersen, H.; Hansen, B. S., Wulff, B. S., Bywater, R. P. Recognition of privileged structures by G-protein coupled receptors. J. Med. Chem. 2004, 47 (4), 888-899.
22. Hipskind, P. A.; Lobb, K. L.; Nixon, J. A.; Britton, T. C.; Bruns, R. F.; Catlow, J.; Dieckman-McGinty, D. K.; Gackenheimer, S. L.; Gitter, B. D.; Iyengar, S.; Schober, D. A.; Simmons, R. M.; Swanson, S.; Zarrinmayeh, H.; Zimmerman, D. M.; Gehlert, D. R. Potent and selective 1,2,3-trisubstituted indole NPY Y-1 antagonists. J. Med. Chem. 1997, 40, (23), 3712-3714.
23. Gurrath M. Peptide-binding G protein-coupled receptors: New oportunities for drug design. Curr. Med. Chem. 2001, 8 (13), 1605-1648.
24. Baggiolini, M. Chemokines in pathology and medicine. J. Intern. Med. 2001, 250 (2), 91-104.
25. Lindow, M.; Lüttichau, H. R.; Schwartz, T. W. Viral leads for chemokine-modulatory drugs. Trends Pharmacol. Sci. 2003, 24 (3), 126-130.
26. Poulsen, A.; Liljefors, T.; Gundertofte, K.; Bjørnholm, B. A pharmacophore model for NK2 antagonist comprising compounds from several structurally diverse classes. J. Comput.-Aided Mol. Des. 2002, 16, 273-286.