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Pharmacophore modelling: methods, experimental verification and applications

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References

  1. Ehrlich, P., Über den jetzigen Stand der Chemotherapie, Chem. Ber., 42 (1909) 17.

    Google Scholar 

  2. Marshall, G.R. and Naylor, C.B., Use of molecular graphics for structural analysis of small molecules, In Hansch, C., Sammes, P.G., Taylor, J.B. and Ramsden, C.A. (Eds.) Comprehensive medicinal chemistry: Vol. 4, Pergamon Press, Oxford, 1990, pp. 431–458.

    Google Scholar 

  3. Marshall, G.R., Barry, C.D., Bosshard, H.E., Dammkoehler, R.A. and Dunn, D.A., The conformational parameter in drug design, Computer Assisted Drug Design, ACS Symp. Ser. 112, 1979, pp. 205–226.

  4. Gund, P., Pharmacophoric pattern searching and receptor mapping, Ann. Rep. Med. Chem., 14 (1979) 299–308.

    Google Scholar 

  5. Ghose, A.K., Logan, M.E., Treasurywala, A.M., Wang, H., Wahl, R.C., Tomczuk, B.E., Gowravaram, M.R., Jaeger, E.P. and Wendoloski, J.J., Determination of pharmacophoric geometry for collagenase inhibitors using a novel computational method and its verification using molecular dynamics, NMR and X-ray crystallography, J. Am. Chem. Soc., 17 (1995) 4671–82.

    Google Scholar 

  6. Humblet, C. and Marshall, G.R. Pharmacophore identification and receptor mapping, Ann. Rep. Med. Chem., 15 (1980) 267–276.

    Google Scholar 

  7. Kelebe, G., Structural alignment of molecules, In Kubinyi, H. (Ed.) 3D QSAR in drug design: theory, methods and applications, ESCOM, Leiden, 1993, pp. 173–199.

    Google Scholar 

  8. Clark, D.E., Willet, P. and Kenny, P.W., Pharmacophoric pattern matching in files of three-dimensional chemical structures: Use of smoothed bounded distances for incompletely specified query patterns, J. Mol. Graph., 9 (1991) 157–160.

    Google Scholar 

  9. Johnson, W.H., Roberts, N.A. and Borkakoti, N., Collagenase inhibitors: Their design and potential therapeutic use, J. Enzyme Inhib., 2 (1987) 1–22.

    Google Scholar 

  10. Schwartz, M.A. and Van Wart, H.E., Synthetic inhibitors of bacterial and mammalian interstitial collagenase, Prog. Med. Chem, 29 (1992) 271–334.

    Google Scholar 

  11. Matthews, B.W., Structural basis of the action of thermolysin and related Zn peptidases, Acc. Chem. Res., 21(1988) 333–340.

    Google Scholar 

  12. Crippen, G.M., Quantitative structure-activity relationships by distance geometry: systematic analysis of dihydrofolate reducatase inhibitors, J. Med. Chem. 23 (1980) 599–606.

    Google Scholar 

  13. Ghose, A.K., Crippen, G.M., Revankar, G.R., McKernan, P.A., Smee, D.F. and Robins, R.K., Analysis of the in vitro antiviral activity of certain ribonucleosides against parainfluenza virus using a novel computer aided receptor modeling procedure, J. Med. Chem., 32 (1989) 746–756.

    Google Scholar 

  14. Viswanadhan, V.N., Ghose, A.K., Revankar, G.R. and Robins, R.K., Atomic physicochemical parameters of three-dimensional structure directed quantitative structure-activity relationships: 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics, J. Chem. Inf. Comput. Sci., 29 (1989) 163–172.

    Google Scholar 

  15. Martin, Y.C., Bures, M.G., Danaher, E.A., DeLazzer, J., Lico, I. and Pavlik, P.A. A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists, J. Comput.-Aided Mol. Design, 7 (1993) 83–102.

    Google Scholar 

  16. Jones, G., Willet, P. and Glen, R.C., A genetic algorithm for flexible molecular overlay and pharma-cophore elucidation, J. Comput.-Aided Mol. Design, 9 (1995) 532–549.

    Google Scholar 

  17. Crippen, G.M. and Havel, T.F., Stable calculation of coordinates from distance information, Acta Crystalloger., Sect. A, 34 (1978) 282.

    Google Scholar 

  18. Sheridan, R.P., Nilakantan, R., Dixon, J.S. and Venkataraghavan, R. The ensemble distance geometry: Application to the nicotinic pharmacophore, J. Med. Chem., 29 (1986) 899–906.

    Google Scholar 

  19. Crippen, G.M., Distance geometry approach to rationalizing binding data, J. Med. Chem., 22 (1979) 988–997.

    Google Scholar 

  20. Ghose, A.K. and Crippen, G.M., Distance geometry approach to modeling receptor sites, In Hansch, C., Sammes, P.G., Taylor, J.B. and Ramsden, C.A. (Eds) Comprehensive medicinal chemistry, Vol. 4, Pergamon Press, 1990, pp. 715–734.

  21. Ghose, A.K. and Crippen, G.M., Geometrically feasible binding models of the flexible ligand molecule at the receptor site, J. Comp. Chem., 6 (1985) 350–359.

    Google Scholar 

  22. Motoc, I., Dammkoehler, R.A. and Marshall, G.R. Three-dimensional structure-activity relationships and biological receptor mapping, In Trinajstic, N. (Ed.) Mathematical and computational concepts in chemistry, Ellis Horwood Ltd., Chichester, 1986, pp. 222–251.

    Google Scholar 

  23. Kuhl, F.S., Crippen, G.M. and Friesen, D.K., A combinatorial algorithm for calculating ligand binding, J. Comput. Chem., 5 (1984) 24–34.

    Google Scholar 

  24. Tripos Associates, Inc., 1699 S. Hanley Road, St. Louis, MO 63144, U.S.A.

  25. Payne, A.W. and Glen, R.C., Molecular recognition using a binary genetic search algorithm, J. Mol. Graph., 11 (1993) 74–91.

    Google Scholar 

  26. Bohacek, R., Delombaert, S., McMartin, C., Priestle, J., and Grutter, M., 3-Dimensional models of ACE and NEP inhibitors and their use in the design of potent dual ACE/NEP inhibitors, J. Am. Chem. Soc., 118 (1996) 8231–8249.

    Google Scholar 

  27. Dalpaiz, A., Bertolasi, V., Borea, P.A., Nacci, V., Fiorini, I., Campiani, G., Mennini, T., Manzoni, C., Novellino, E. and Greco, G., A concerted study using binding measurements, X-ray structural data and molecular modeling on the stereochemical features responsible for the affinity of 6-arylpyrrolo [2,1-D][1,5]benzothiazepines toward mitochondrial benzodiazepine receptors, J. Med. Chem., 38 (1995) 4730–4738.

    Google Scholar 

  28. Froimowitz, M., Patrick, K.S. and Cody, V., Conformational analysis of methylphenidate and its structural relationship to other dopamine reuptake blockers such as CFT, Pharmaceutic. res., 12 (1995) 1430–1434.

    Google Scholar 

  29. Bandoli, G., Dolmella, A., Gatto, S. and Nicolini, M., X-ray studies, empirical, semiempirical and statistical calculations on a series of thyrotropin-releasing-hormone derivatives, J. Mol. Struct., 345 (1995) 213–225.

    Google Scholar 

  30. Morita, H., Yun, Y.S., Takeya, K., Itokawa, H. and Shiro, M., Conformational analysis of a cyclic hexa-peptide, segetalin-A from Vaccariasegetalis, Tetrahedron, 51 (1995) 5987–6002.

    Google Scholar 

  31. Brandt, W., Drosihin, S., Haurand, M., Holzgrabe, U. and Nachtsheim, C., Search for the phar-macophore in k-agonistic diazabicyclo[3.3.1]nonan-9-one-1,5-diesters and arylacetamides, Arch. der Pharmazie, 329 (1996) 311–323.

    Google Scholar 

  32. Hennig, P., Raimbaud, E., Thurieau, C., Volland, J.P., Michel, A. and Fauchere, J.L., Solution conformation by NMR and molecular modeling of 3 sulfide-free somatostatin octapeptide analogs compared to angiopeptin, J. Comput.-Aided Mol. Design, 10 (1996) 83–86.

    Google Scholar 

  33. Boger, D.L. and Zhou, J.C., N-Desmethyl derivatives of Deoxybouvardin and RA-VII: synthesis and evaluation, J. Am. Chem. Soc., 117 (1995) 7364–7378.

    Google Scholar 

  34. Morita, H., Yun, Y.s., Takeya, K., Itokawa, H. and Shiro, M., Conformational analysis of a cyclic hexapeptide, segetalin-A from Vaccariasegetalis, Tetrahedron, 51 (1995) 5987–6002.

    Google Scholar 

  35. Sefler, A.M., He, J.X., Sawyer, T.K., Holub, K.E., Omecinsky, D.O., Reily, M.D., Thanball, V., Akunne, H.C. and Cody, W.L., Design and structure-activity relationships of C-terminal cyclic neu-rotensin fragment analogs, J. Med. Chem., 38 (1995) 249–257.

    Google Scholar 

  36. Nicklaus, M.C., Wang, S., Driscoll, J.S. and Milne, G.W., Conformational changes of small molecules binding to proteins, Bioorg. Med. Chem., 3 (1995) 411–428.

    Google Scholar 

  37. MDL Information Systems Inc., 14600 Cataline Street, San Leandro, CA 94577, U.S.A.

  38. AM Technologies Inc., 14785 Omicron Dr., Texas Research Park, San Antonio, TX 78245, U.S.A.

  39. Ghose, A.K. and Crippen, G.M., A general distance geometry three-dimensional receptor model for dihydrofolate reductase inhibitors, J. Med. Chem., 27 (1984) 901–914.

    Google Scholar 

  40. Ghose, A.K. and Crippen, G.M., Use of physicochemical parameters in distance geometry and related three-dimensional quantitative structure-activity relationships: A demonstration using Escheria coli dihydrofolate reductase inhibitors, J. Med. Chem., 28 (1985) 333–346.

    Google Scholar 

  41. Cramer, R.D., Patterson, D.E. and Bunce, J.D., Comparative molecular field analysis (CoMFA): I. Effect of shape on binding of steroids to carrier proteins, J. Am. Chem. Soc., 110 (1988) 5959–5967.

    Google Scholar 

  42. Holzgrabe, U. and Hopfinger, A.J., Conformational-analysis, molecular shape comparison, and phar-macophore identification of different allosteric modulators of muscarinic receptors, J. Chem. Inf. Comp. Sci., 36 (1996) 1018–1024.

    Google Scholar 

  43. Hariprasad, V. and Kulkarni, V.M., A proposed common spatial pharmacophore and the corresponding active conformations of some peptide leukotriene receptor antagonists, J. Comput.-Aided Mol. Design, 10 (1996) 284–292.

    Google Scholar 

  44. Barlett, P.A., Shea, J.T. Telfer, S.J. and Waterman, S. CAVEAT: S program to facilitate the structure-derived design of biologically active molecules (Special publ. Molecular recognition in chemical and biological problems), 78 (1989) 182–196.

    Google Scholar 

  45. Tschinke, V. and Cohen, N.C., The NEWLEAD program: A net method for the design of candidate structures from pharmacophore hypothesis. J. Med. Chem., 36 (1993) 3863–3870.

    Google Scholar 

  46. Pickett, S.D., Mason, J.S. and Mclay, I.M., Diversity profiling and design using 3D pharmacophores - pharmacophore-derived queries (pdq), J. Chem. Inf. Comput. Sci. 36 (1996) 1214–1223.

    Google Scholar 

  47. Mattos, C. and Ringe, D., Multiple Binding Modes, In H. Kubinyi (Ed.) 3D QSAR in drug design: Theory, methods and applications, ESCOM, Leiden, 1993, pp. 226–254.

    Google Scholar 

  48. Diana, G.D., Jaeger, E.P., Peterson, M.L. and Treasurywala, A.M., The use of an algorithmic method of small molecule superpositions in the design of antiviral agents, J. Comput.-Aided Mol. Design, 7 (1993), 325–335.

    Google Scholar 

  49. Martin, Y.C., Pharmacophore mapping, In Martin, Y.C. and Willet, P. (Eds) Design of bioactive molecules using 3D structure information, ACS Washington D.C., 1997.

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Ghose, A.K., Wendoloski, J.J. Pharmacophore modelling: methods, experimental verification and applications. Perspectives in Drug Discovery and Design 9, 253–271 (1998). https://doi.org/10.1023/A:1027213408430

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