Relating protein pharmacology by ligand chemistry

Nature Biotechnology

Volumn 25, Issue 2, 2007, Pages 197-206

  Keiser, Michael J ^a   Roth, Bryan L ^b,c   Armbruster, Blaine N ^c   Ernsberger, Paul ^b   Irwin, John J ^a   Shoichet, Brian K ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b CASE WESTERN RESERVE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOTECHNOLOGY; DRUG PRODUCTS; MOLECULAR STRUCTURE; PHARMACODYNAMICS; STATISTICAL METHODS; TOPOLOGY;

BIOLOGICAL INFORMATION; CHEMICAL SIMILARITY; LIGAND TOPOLOGY; PROTEIN PHARMACOLOGY;

PROTEINS;

ALPHA 2 ADRENERGIC RECEPTOR STIMULATING AGENT; EMETINE; LIGAND; LOPERAMIDE; METHADONE; MUSCARINIC M3 RECEPTOR ANTAGONIST; NEUROKININ; PROTEIN;

ARTICLE; CHEMISTRY; HUMAN; PRIORITY JOURNAL; PROTEIN FUNCTION; QUANTITATIVE ANALYSIS;

BINDING SITES; DATABASES, PROTEIN; DRUG DELIVERY SYSTEMS; DRUG DESIGN; LIGANDS; PHARMACEUTICAL PREPARATIONS; PROTEIN BINDING; PROTEIN INTERACTION MAPPING; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN;

EID: 33846876695     PISSN: 10870156     EISSN: 15461696     Source Type: Journal    
DOI: 10.1038/nbt1284     Document Type: Article

References (51)

1. Roth, B.L., Sheffler, D.J. & Kroeze, W.K. Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia. Nat. Rev. Drug Discov. 3, 353-359 (2004).
2. Kroeze, W.K., Kristiansen, K. & Roth, B.L. Molecular biology of serotonin receptors structure and function at the molecular level. Curr. Top. Med. Chem. 2, 507-528 (2002).
3. Ebert, B., Andersen, S. & Krogsgaard-Larsen, P. Ketobemidone, methadone and pethidine are non-competitive N-methyl-D-aspartate (NMDA) antagonists in the rat cortex and spinal cord. Neurosci. Lett. 187, 165-168 (1995).
4. Callahan, R.J., Au, J.D., Paul, M., Liu, C. & Yost, C.S. Functional inhibition by methadone of N-methyl-D-aspartate receptors expressed in Xenopus oocytes: stereospecific and subunit effects. Anesth. Analg. 98, 653-659 (2004).
5. Krueger, K.E. Peripheral-type benzodiazepine receptors: a second site of action for benzodiazepines. Neuropsychopharmacology 4, 237-244 (1991).
6. Finlayson, K., Witchel, H.J., McCulloch, J. & Sharkey, J. Acquired QT interval prolongation and HERG: implications for drug discovery and development. Eur. J. Pharmacol. 500, 129-142 (2004).
7. Schreiber, S.L. Small molecules: the missing link in the central dogma. Nat. Chem. Biol. 1, 64-66 (2005).
8. Johnson, M.A. & Maggiora, G.M. Concepts and applications of molecular similarity. (Wiley, New York; 1990).
9. Matter, H. Selecting optimally diverse compounds from structure databases: a validation study of two-dimensional and three-dimensional molecular descriptors. J. Med. Chem. 40, 1219-1229 (1997).
10. Whittle, M., Gillet, V.J., Willett, P., Alex, A. & Loesel, J. Enhancing the effectiveness of virtual screening by fusing nearest neighbor lists: a comparison of similarity coefficients. J. Chem. Inf. Comput. Sci. 44, 1840-1848 (2004).
11. Willett, P. Searching techniques for databases of two- and three-dimensional chemical structures. J. Med. Chem. 48, 4183-4199 (2005).
12. Paolini, G.V., Shapland, R.H.B. & v Hoorn, W.P. Mason, J.S. & Hopkins, A.L. Global mapping of pharmacological space. Nat. Biotechnol. 24, 805-815 (2006).
13. Vieth, M. et al. Kinomics-structural biology and chemogenomics of kinase inhibitors and targets. Biochim. Biophys. Acta 1697, 243-257 (2004).
14. Izrailev, S. & Farnum, M.A. Enzyme classification by ligand binding. Proteins 57, 711-724 (2004).
15. Bender, A. et al. "Bayes affinity fingerprints" improve retrieval rates in virtual screening and define orthogonal bioactivity space: when are multitarget drugs a feasible concept? J. Chem. Inf. Model. 46, 2445-2456 (2006).
16. 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. 46, 1124-1133 (2006).
17. Steindl, T.M., Schuster, D., Laggner, C. & Langer, T. Parallel screening: a novel concept in pharmacophore modeling and virtual screening. J. Chem. Inf. Model. 46, 2146-2157 (2006).
18. Schuffenhauer, A., Floersheim, P., Acklin, P. & Jacoby, E. Similarity metrics for ligands reflecting the similarity of the target proteins. J. Chem. Inf. Comput. Sci. 43, 391-405 (2003).
19. 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. 43, 680-690 (2003).
20. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 215, 403-410 (1990).
21. Karlin, S. & Altschul, S.F. Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc. Natl. Acad. Sci. USA 87, 2264-2268 (1990).
22. Pearson, W.R. Empirical statistical estimates for sequence similarity searches. J. Mol. Biol. 276, 71-84 (1998).
23. Sheridan, R.P. & Miller, M.D. A Method for Visualizing Recurrent Topological Substructures in Sets of Active Molecules. J. Chem. Inf. Comput. Sci. 38, 915-924 (1998).
24. Bradshaw, J. & Sayle, R.A. Some thoughts on significant similarity and sufficient diversity. Presented at the 1997 EuroMUG meeting, 7-8 October 7-8, 1997, Verona, Italy. 〈http://www.daylight.com/meetings/emug97/ Bradshaw/Significant_Similarity.html〉.
25. Hert, J. et al. Comparison of fingerprint-based methods for virtual screening using multiple bioactive reference structures. J. Chem. Inf. Comput. Sci. 44, 1177-1185 (2004).
26. Hert, J. et al. 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. 46, 462-470 (2006).
27. Altschul, S.F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389-3402 (1997).
28. Sheridan, R.P. & Kearsley, S.K. Why do we need so many chemical similarity search methods? Drug Discov. Today 7, 903-911 (2002).
29. Goodman, L.S., Gilman, A., Brunton, L.L., Lazo, J.S. & Parker, K.L. Goodman & Gilman's The Pharmacological Basis Of Therapeutics, edn. 11 (McGraw-Hill, New York; 2006).
30. Cleves, A.E. & Jain, A.N. Robust ligand-based modeling of the biological targets of known drugs. J. Med. Chem. 49, 2921-2938 (2006).
31. DRUGDEX (see Methadone) (Thomson Micromedex, Greenwood Village, Colorado, 2006). 〈http://www.thomsonhc.com〉.
32. de Vos, J.W., Geerlings, P.J., van den Brink, W., Ufkes, J.G. & van Wilgenburg, H. Pharmacokinetics of methadone and its primary metabolite in 20 opiate addicts. Eur. J. Clin. Pharmacol. 48, 361-366 (1995).
33. DRUGDEX (see Emetine) (Thomson Micromedex, Greenwood Village, Colorado; 2006). 〈http://www.thomsonhc.com〉
34. Kojima, S., Ikeda, M. & Kamikawa, Y. Loperamide inhibits tachykinin NK3-receptor-triggered serotonin release without affecting NK2-receptor- triggered serotonin release from guinea pig colonic mucosa. J. Pharmacol. Sci. 98, 175-180 (2005).
35. MDL Drug Data Report, 2006.1 (MDL Information Systems Inc., San Leandro, CA, 2006).
36. Schuffenhauer, A. et al. An ontology for pharmaceutical ligands and its application for in silico screening and library design. J. Chem. Inf. Comput. Sci. 42, 947-955 (2002).
37. International Union of Biochemistry and Molecular Biology, Nomenclature Committee & Webb, E.C. Enzyme Nomenclature 1992: Recommendations of the Nomenclature Committee of the International Union Of Biochemistry and Molecular Biology on the Nomenclature and Classification of Enzymes (Academic Press, San Diego; 1992).
38. James, C., Weininger, D. & Delany, J. Daylight Theory Manual (Daylight Chemical Information Systems Inc., Mission Viejo, CA; 1992-2005).
39. Willett, P. Similarity and Clustering in Chemical Information Systems (Research Studies Press; Wiley, Letchworth, Hertfordshire, England; New York; 1987).
40. Brown, R.D. & Martin, Y.C. Use of structure Activity data to compare structure-based clustering methods and descriptors for use in compound selection. J. Chem. Inf. Comput. Sc.i 36, 572-584 (1996).
41. Chen, X. & Reynolds, C.H. Performance of similarity measures in fragment-based similarity searching: comparison of structural descriptors and similarity coefficients. J. Chem. Inf. Comput. Sci. 42, 1407-1414 (2002).
42. Jones, E., Oliphant, T. & Peterson, P. SciPy: Open Source Scientific Tools for Python. (2001). 〈http://www.scipy.org/〉.
43. Kruskal, J. On the shortest spanning subtree and the traveling salesman problem. Proc. Am. Math. Soc. 7, 48-50 (1956).
44. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498-2504 (2003).
45. Pavlidis, P. & Noble, W.S. Matrix2png: a utility for visualizing matrix data. Bioinformatics 19, 295-296 (2003).
46. Rost, B. Enzyme function less conserved than anticipated. J. Mol. Biol. 318, 595-608 (2002).
47. Roth, B.L. et al. Salvinorin A: a potent naturally occurring nonnitrogenous kappa opioid selective agonist. Proc. Natl. Acad. Sci. USA 99, 11934-11939 (2002).
48. Davies, M.A., Compton-Toth, B.A., Hufeisen, S.J., Meltzer, H.Y. & Roth, B.L. The highly efficacious actions of N-desmethylclozapine at muscarinic receptors are unique and not a common property of either typical or atypical antipsychotic drugs: is M1 agonism a pre-requisite for mimicking clozapine's actions? Psychopharmacology (Berl.) 178, 451-460 (2005).
49. Chelala, J.L., Kilani, A., Miller, M.J., Martin, R.J. & Ernsberger, P. Muscarinic receptor binding sites of the M4 subtype in porcine lung parenchyma. Pharmacol. Toxicol. 83, 200-207 (1998).
50. Takeda, Y. et al. Ligand binding kinetics of substance P and neurokinin A receptors stably expressed in Chinese hamster ovary cells and evidence for differential stimulation of inositol 1,4,5-trisphosphate and cyclic AMP second messenger responses. J. Neurochem. 59, 740-745 (1992).
51. Wozniak, M. & Limbird, L.E. The three alpha 2-adrenergic receptor subtypes achieve basolateral localization in Madin-Darby canine kidney II cells via different targeting mechanisms. J. Biol. Chem. 271, 5017-5024 (1996).