Pharmacophore Identification and Pseudo-Receptor Modeling

The Practice of Medicinal Chemistry

Volumn , Issue , 2008, Pages 572-586

  Sippl, Wolfgang ^a  

^a MARTIN LUTHER UNIVERSITY HALLE WITTENBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 65249131863     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-0-12-374194-3.00028-7     Document Type: Chapter

References (84)

1. Wermuth C.G., Ganellin C.R., Lindberg P., Mitschler L.A. Glossary of terms used in medicinal chemistry (IUPAC Recommen-dations 1997). Annu. Rep. Med. Chem. 1998, 33:385-395.
2. Langley J.N. On the reaction of cells and nerve-endings to certain poissons, chiefly as regards the reaction of striated muscle to nictoine and to cuare. J. Physiol. 1905, 33:374-413.
3. Ehrlich P., Morgenroth J. Über Haemolysine. Dritte Mitteilung. Berl. Klin. Wochenschr. 1900, 37:453-457.
4. Fischer E. Einfluss der Konfiguration auf die Wirkung der Enzyme. Ber. Dtsch. Chem. Ges. 1894, 27:2985-2993.
5. Perutz M.F. X-ray analysis of haemoglobin. Science 1963, 140:863-869.
6. Marshall G.R. Binding-site modelling of unknown receptors. 3D QSAR in Drug Design, Theory Methods and Applications 1993, 80-116. ESCOM, Leiden. H. Kubinyi (Ed.).
7. Barry C.D., Ellis R.A., Graesser S., Marshall G.R. Display and manipulation in three dimensions. Pertinent Concepts in Computer Graphics 1969, 104-153. University of Illinois Press, Chicago, IL. M. Faiman, J. Nievergelt (Eds.).
8. Kier L.B., Aldrich H.S. A theoretical study of receptor site models for trimethylammonium group interactions. J. Theor. Biol. 1974, 46:529-541.
9. Gund P., Wipke W.T., Langridge R. Computer searching of a molecular structure file for pharmacophoric patterns. Comput. Chem. Res. Educ. Technol. 1974, 3:5-21.
10. Poptodorov K., Liu T., Hoffmann R.D. Pharmacophore model generation software tools. Pharmacophores and Pharmacophore Searches 2006, 17-47. WILEY-VCH, Weinheim, Germany. T. Langer, R.D. Hoffmann (Eds.).
11. Evans B.E., et al. Methods for drug discovery: development of potent selective, orally effective cholecystokinin antagonists. J. Med. Chem. 1988, 31:2235-2246.
12. Wermuth C.G. Pharmacophores: historical perspective and viewpoint from a medicinal chemist. Pharmacophores and Pharmacophore Searches 2006, 1-13. WILEY-VCH, Weinheim, Germany. T. Langer, R.D. Hoffmann (Eds.).
13. Snyder, J. P., Rao, S. N., Koehler, A., Vedani, A. Minireceptors and pseudoreceptors. In 3D QSAR in Drug Design, Theory Methods and Applications (Kubinyi, H. (Ed.), ESCOM, Leiden, 336-354.
14. Vedani A., Zbinden P., Snyder J.P. Pseudo-receptor modelling: a new concept for the three-dimensional construction of receptor binding sites. J. Recept. Res. 1993, 13:163-177.
15. Höltje H.D., Anzali A. Molecular modelling studies on the digitalis binding site of the Na+/K(+)-ATPase. Pharmazie 1992, 47:691-698.
16. Frühbeis H., Klein R., Wallmeier H. Computergestütztes Moleküldesign (CAMD) - ein Überblick. Angew. Chem. Int. Ed. Engl. 1987, 26:403-418.
17. Böhm H.J., Klebe G., Kubinyi H. Wirkstoffdesign 1996, Spektrum Akademischer Verlag, Heidelberg, Germany.
18. Osterberg F., Morris G.M., Sanner M.F., Olson A.J., Goodsell D.S. Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in autodock. Proteins 2002, 46:34-40.
19. Gold, Cambridge Crystallographic Data Centre, Cambridge, UK. http://www.ccdc.cam.ac.uk.
20. Glide, Schrödinger, Portland, OR. http://www.schroedinger.com.
21. FlexE, BiosolveIT, St. Augustin, Germany. http://www.biolsolveit.de.
22. Klebe G. Virtual ligand screening. Drug Discov. Today 2006, 11:580-594.
23. Tame J.R. Scoring functions-the first 100 years. J. Comput.-Aided Mol. Des. 2005, 19:445-451.
24. 3-receptor ligands. J. Med. Chem. 2003, 46:3883-3899.
25. Cramer R.D., Patterson D.E., Bunce J.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc. 1988, 110:5959-5967.
26. Ahlstrom M.M., Ridderstrom M., Luthman K., Zamora I. Virtual screening and scaffold hopping based on GRID molecular interaction fields. J. Chem. Inform. Model. 2005, 45:1313-1323.
27. Steindl T.M., Schuster D., Wolber G., Laggner C., Langer T. High-throughput structure-based pharmacophore modelling as a basis for successful parallel virtual screening. J. Comput.-Aided Mol. Des. 2006, 20:703-715.
28. Catalyst, Accelrys Software, San Diego, CA. http://www.accelrys.com.
29. DISCOtech, St. Louis, MO. http://www.tripos.com.
30. Galahad, Tripos, St. Louis, MO. http://www.tripos.com.
31. LigandScout, Inteligand, Wien, Austria. http://www.inteligand.com.
32. Phase, Schrödinger, Portland, OR. http://www.schroedinger.com.
33. MOE, Chemical Computing Group, Montreal, Canada. http://www.chemcomp.com.
34. Patel Y., Gillet V.J., Bravi G., Leach A. A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP. J. Comput.-Aided Mol. Des. 2002, 16:653-681.
35. Boström J., Norrby P.-O., Liljefors T. Conformational energy penalties of protein-bound ligands 1998, 12:383-396.
36. Agrafiotis D.K., Gibbs A.C., Zhu F., Izrailev S., Martin E. Conformational sampling of bioactive molecules: a comparative study. J. Chem. Inform. Model. 2007, 47:1067-1086.
37. Höltje H.-D., Sippl W., Rognan D., Folkers G. Molecular Modelling: Basic principles and applications 2007, Wiley-VCH, Weinheim, Germany. 3rd Edition.
38. Marshall G.R., Barry C.D., Bosshard H.E., Dammkoehler R.A., Dunn D.A. The conformational parameter in drug design: the active analog approach. Computer-Assisted Drug Design, ACS Monograph 112 1979, 205-226. American Chemical Society, Washington DC. E.C. Olsen, R.E. Christoffersen (Eds.).
39. Smellie A., Teig S., Towbin P. Poling: promoting conformational variation. J. Comput. Chem. 1994, 16:171-187.
40. Kearsley S.K., Smith G.M. An alternative method for the alignment of molecular structures: maximizing electrostatic and steric overlap. Tetrahedron Comput. Methodol 1990, 3:615-633.
41. Kirchmair J., Wolber G., Laggner C., Langer T. Comparative performance assessment of the conformational model generators omega and catalyst: a large-scale survey on the retrieval of protein-bound ligand conformations. J. Chem. Inform. Model. 2006, 46:1848-1861.
42. Boström J. Reproducing the conformations of protein-bound ligands: a critical evaluation of several popular conformational searching tools. J. Comput.-Adided Mol. Des 2001, 15:1137-1152.
43. Omega, OpenEye Scientific Software, Santa Fee, NM. http://www.eyesopen.com.
44. Boström J., Greenwood J.R., Gottfries J. Assessing the performance of OMEGA with respect to retrieving bioactive conformations. J. Mol. Graph. Model. 2003, 21:449-462.
45. FlexS, BiosolveIT, St. Augustin, Germany. http://www.biosolveit.com.
46. Lemmen C., Lengauer T. Computational methods for the structural alignment of molecules. J. Comput.-Aided Mol. Des. 2000, 14:215-232.
47. Schlegel B., Meier R., Laggner C., Schnell D., Langer T., Seifert R., Stark H., Höltje H.-D., Sippl W. J. Comput.-Aided Mol. Des. 2007, in press.
48. UNITY, Tripos, St. Louis, MO. http://www.tripos.com.
49. Wolber G., Langer T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J. Chem. Inform. Model. 2005, 45:160-169.
50. Hindle S.A., Rarey M., Buning C., Lengauer T. Flexible docking under pharmacophore type constraints. J. Comput.-Aided Mol. Des. 2002, 16:129-149.
51. Barreca M.L., De Luca L., Iraci N., Rao A., Ferro S., Maga G., Chimirri A. Structure-based pharmacophore identification of new chemical scaffolds as non-nucleoside reverse transcriptase inhibitors. J. Chem. Inform. Model. 2007, 47:557-562.
52. Krovat E.M., Fruhwirth K.H., Langer T. Pharmacophore identification, in silico screening, and virtual library design for inhibitors of the human factor Xa. J. Chem. Inform. Model. 2005, 45:146-159.
53. Maccari R., Ottana R., Ciurleo R., Vigorita M.G., Rakowitz D., Steindl T., Langer T. Evaluation of in vitro aldose reductase inhibitory activity of 5-arylidene-2,4-thiazolidinediones. Bioorg. Med. Chem. Lett. 2007, 17:3886-3893.
54. Laggner C., Schieferer C., Fiechtner B., Poles G., Hoffmann R.D., Glossmann H., Langer T., Moebius F.F. Discovery of high-affinity ligands of sigma1 receptor, ERG2, and emopamil binding protein by pharmacophore modelling and virtual screening. J. Med. Chem. 2005, 48:4754-4764.
55. Spannhoff A., Heinke R., Bauer I., Trojer P., Metzger E., Gust R., Schüle R., Brosch G., Sippl W., Jung M. Target-based approach to inhibitors of histone arginine methyltransferases. J. Med. Chem. 2007, 50:2319-2325.
56. Wolber G., Dornhöfer A.A., Langer T. Efficient overlay of small organic molecules using 3D pharmacophores. J. Comput.-Aided Mol. Des. 2006, 20:773-788.
57. Capdeville R., Buchdunger E., Zimmermann J., Matter A. Glivec (STI571, imatinib), a rationally developed, targeted anticancer drug. Nat. Rev. Drug. Discov. 2002, 7:493-502.
58. Mol C.D., Fabbro D., Hosfield D.J. Structural insights into the conformational selectivity of STI-571 and related kinase inhibitors. Curr. Opin. Drug Discov. Dev. 2004, 5:639-648.
59. Wolber G., Kosara R. Pharmacophores from macromolecular complexes with LigandScout. Pharmacophores and Pharmacophore Searches 2006, 131-150. WILEY-VCH, Weinheim, Germany. T. Langer, R.D. Hoffmann (Eds.).
60. Schleifer K.J. Concept and applications of pseudoreceptors. Pharmacophores and Pharmacophore Searches 2006, 117-130. WILEY-VCH, Weinheim, Germany. T. Langer, R.D. Hoffmann (Eds.).
61. Höltje H.-D. Theoretical studies on drug-receptor model complexes. Pharm. Acta Helv. 1979, 54:125-134.
62. Marrer S., Höltje H.-D. Molecular modelling study of calcium channel activating and blocking 1,4-dihydropyridine derivatives: a hypothetical molecular receptor model. J. Protein Chem. 1989, 8:420-421.
63. 3-receptor agonists. Pharmazie 1998, 53:433-437.
64. 2a receptor model. Arch. Pharm. (Weinheim) 1995, 328:577-584.
65. McMartin C., Bohacek R.S. QXP: powerful, rapid computer algorithms for structure-based drug design. J. Comput.-Aided Mol. Des. 1997, 11:333-344.
66. Vedani A., Zbinden P. Quasi-atomistic receptor modelling. A bridge between 3D QSAR and receptor fitting. Pharm. Acta Helv. 1998, 73:11-18.
67. Walters D.E., Hinds R.M. Genetically evolved receptor models: a computational approach to construction of receptor models. J. Med. Chem. 1994, 37:2527-2536.
68. Lill M.A., Vedani A., Dobler M. Raptor: combining dual-shell representation, induced-fit simulation, and hydrophobicity scoring in receptor modelling: application toward the simulation of structurally diverse ligand sets. J. Med. Chem. 2004, 47:6174-6186.
69. Lill M.A., Vedani A. Combining 4D pharmacophore generation and multidimensional QSAR: modelling ligand binding to the bradykinin B2 receptor. J. Chem. Inform. Model. 2006, 46:2135-2145.
70. Hahn M., Rogers D. Receptor surface models. 2. Application to quantitative structure-activity studies. J. Med. Chem. 1995, 38:2091-2102.
71. Schleifer K.J. Pseudoreceptor model for ryanodine derivatives at calcium release channels. J. Comput.-Aided Mol. Des. 2000, 14:467-475.
72. Vedani A., Dobler M., Dollinger H., Hasselbach K.M., Birke F., Lill M.A. Novel ligands for the chemokine receptor-3 (CCR3): a receptor-modeling study based on 5D-QSAR. J. Med. Chem. 2005, 48:1515-1527.
73. Bohacek R., Boosalis M.S., McMartin C., Faller D.V., Perrine S.P. Identification of novel small-molecule inducers of fetal hemoglobin using pharmacophore and 'PSEUDO' receptor models. Chem. Biol. Drug Des. 2006, 67:318-328.
74. Vedani A., Dobler M., Lill M.A. Combining protein modeling and 6D-QSAR. Simulating the binding of structurally diverse ligands to the estrogen receptor. J. Med. Chem. 2005, 48:3700-3703.
75. Sippl W., Contreras J.M., Parrot I., Rival Y.M., Wermuth C.G. Receptor-based QSAR and design of novel acetylcholinesterase inhibitors. J. Comput.-Aided Mol. Des. 2001, 15:395-410.
76. Doweyko A.M. 3D-QSAR illusions. J. Comput.-Aided Mol. Des. 2004, 18:587-596.
77. 3 receptor: preclinical pharmacology. J. Pharmacol. Exp. Therapeut. 2007, 320:365-375.
78. 3 receptor antagonists. Mini Rev. Med. Chem. 2004, 4:965-977.
79. Schlegel B., Sippl W., Höltje H.-D. Molecular dynamics simulations of bovine rhodopsin: influence of protonation states and different membrane-mimicking environments. J. Mol. Model. 2005, 12:49-64.
80. Steuber H., Zentgraf M., La Motta C., Sartini S., Heine A., Klebe G. Evidence for a novel binding site conformer of aldose reductase in ligand-bound state. J. Mol. Biol. 2007, 369:186-197.
81. Steuber H., Zentgraf M., Gerlach C., Sotriffer C.A., Heine A., Klebe G. Expect the unexpected or caveat for drug designers: multiple structure determinations using aldose reductase crystals treated under varying soaking and co-crystallisation conditions. J. Mol. Biol. 2006, 363:174-187.
82. Specker E., Bottcher J., Brass S., Heine A., Lilie H., Schoop A., Muller G., Griebenow N., Klebe G. Unexpected novel binding mode of pyrrolidine-based aspartyl protease inhibitors: design, synthesis and crystal structure in complex with HIV protease. Chem. Med. Chem. 2006, 1:106-117.
83. Sippl W. Receptor-based 3D QSAR analysis of estrogen receptor ligands-merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods. J. Comput.-Aided Mol. Des. 2000, 14:559-572.
84. Evers A., Gohlke H., Klebe G. Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials. J. Mol. Biol. 2003, 334:327-345.