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Pseudoreceptor: Concept and an Overview

  • Kothandan, Gugan (Department of Bio-New Drug Development, College of Medicine, Chosun University) ;
  • Madhavan, Thirumurthy (Department of Bio-New Drug Development, College of Medicine, Chosun University) ;
  • Gadhe, Changdev G. (Department of Bio-New Drug Development, College of Medicine, Chosun University) ;
  • Cho, Seung Joo (Department of Bio-New Drug Development, College of Medicine, Chosun University)
  • 투고 : 2010.09.01
  • 심사 : 2010.09.27
  • 발행 : 2010.09.30

초록

A pseudoreceptor combines structure-based and ligand-based techniques to represent a unifying concept for both receptor mapping and ligand matching. In this molecular modeling approach, there are opportunities to construct the pseudoreceptor models using a set of small molecules. To build a reliable pseudoreceptor model, we need a set of ligand molecules with known affinity (biological activity) to generate 3D bioactive conformation for each of these ligand molecules. Several software packages are available to generate a pseudoreceptor model and this can provide an entry point for structure based drug discovery in cases where receptor structure information is not available. In this review, we presented the concept of pseudoreceptor, as well as discussed about various software packages available to generate a pseudoreceptor model.

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참고문헌

  1. G. Schneider and K. H. Baringhaus, "Molecular Design: Concepts and Applications", Wiley-VCH, Weinheim., pp. 1-277, 2008.
  2. G. Klebe, "Virtual ligand screening: strategies, perspectives and limitations", Drug Discov. Today., Vol. 11, pp. 580-594, 2006. https://doi.org/10.1016/j.drudis.2006.05.012
  3. M. Congreve, C. W. Murray and T. L. Blundell, "Structural biology and drug discovery", Drug Discov. Today., Vol. 10, pp. 895-907, 2005. https://doi.org/10.1016/S1359-6446(05)03484-7
  4. H. Fruhbeis, R. Klein and H. Wallmeier, "Computer- Assited Molecular Design - An Overview", Angew. Chem. Int. Ed. Engl., Vol. 26, pp. 403-418, 1987. https://doi.org/10.1002/anie.198704031
  5. J. P. Snyder and S. N. Rao, "Pseudoreceptors: A bridge between receptor fitting and receptor mapping in drug design", Chem. Des. Autom. News., Vol. 4, pp. 13-15, 1989.
  6. H. D. Holtje and S. Anzali, "Molecular modeling studies on the digitalis binding site of the. Na+/K+- ATPase", Pharmazie., Vol. 47, pp. 691-698, 1992.
  7. J. P. Snyder, S. N. Rao, K. F. Koehler and R. Pellicciari, "Trends in Receptor Research", Elsevier., pp. 367-403, 1992.
  8. J. P. Snyder, S. N. Rao, K. F. Koehler and A. Vedani, "3D QSAR in Drug Design", ESCOM Science Publishers., pp. 336-354, 1993.
  9. R. D. Cramer, D. E. Patterson and J. D. Bunce, "Comparative molecuar field analysis (CoMFA).1. Effect of shape on binding of steroids to carrier proteins", J. Am. Chem. Soc., Vol. 110, pp. 5959-5967, 1988. https://doi.org/10.1021/ja00226a005
  10. G. Klebe, U. Abraham and T. Mietzner, "Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological potency", J. Med. Chem., Vol. 37, pp. 4130-4146, 1994. https://doi.org/10.1021/jm00050a010
  11. M. Baroni, G. Costantino, G. Cruciani, D. Riganelli, R. Valigi and S. Clementi, "Generating Optimal Linear PLS Estimations (GOLPE): an advanced chemometric tool for handling 3D-QSAR problems", Quant. Struct. Act. Relat., Vol. 12, pp. 9-20, 1993. https://doi.org/10.1002/qsar.19930120103
  12. F. Momany, R. Pitha, V. J. Klimkovsky and C. M. Venkatachalam, "Expert Systems and Applications in Chemistry eds B. A. Hohne, T. H. Pierce", American Chemical Society., Washington DC, pp. 82-91 1989.
  13. H. D. Holtje and S. Anzali, "Molecular modeling studies on the digitalis binding site of the. Na+/K+- ATPase", Pharmazie., Vol. 47, pp. 691-698, 1992.
  14. J. P. Snyder, S. N. Rao, K. F. Koehler and A. Vedani, "3D QSAR in Drug Design: Theory, Methods and Applications (ed. Kubinyi, H.)", pp. 336-354, Leiden/Escom, Dordrecht, 1993.
  15. W. Chen and M. K. Gilson, "Concept: de novo design of synthetic receptors for targeted ligands", J. Chem. Inf. Model., Vol. 47, pp. 425-434, 2007. https://doi.org/10.1021/ci600233v
  16. J. Pei and J. Zhou, "Flexible atom receptor model", Acta Chim. Sin., Vol. 60, pp. 973-979, 2002.
  17. Z. Peter, D. Max, F. Gerd and V. Angelo, "pseudoreceptor modeling using receptor mediated ligand alignment and pharmacophore equilibration", Quant. Struct. Act. Relat., Vol.17, pp.122-130, 1998. https://doi.org/10.1002/(SICI)1521-3838(199804)17:02<122::AID-QSAR122>3.3.CO;2-C
  18. V. Angelo and Z. Peter, "A bridge between 3D QSAR and receptor fitting", Pharm. Acta Helv., Vol. 73, pp. 11-18, 1998. https://doi.org/10.1016/S0031-6865(97)00042-3
  19. K. Yuichi, I. Akiko and I. Yoichi, "A novel method for superimposing molecules and receptor mapping", Tetrahedron, Vol. 43, pp. 5229-5236, 1987. https://doi.org/10.1016/S0040-4020(01)87698-5
  20. K. Yuichi, I. Atsushi, Y. Miho, T. Nobuo and I. Akiko, "Automatic superposition of drug molecules based on their common receptor site", J. Comput. Aided Mol. Des., Vol. 6, pp. 475-486, 1992. https://doi.org/10.1007/BF00130398
  21. H. Mathew, "Receptor surface models. 1. Definition and construction", J. Med. Chem., Vol. 38, pp. 2080-2090, 1995. https://doi.org/10.1021/jm00012a007
  22. H. Mathew and R. David, "Receptor surface models. 2. Application to quantitative structure-activity relationship studies", J. Med. Chem., Vol. 38, pp. 2091-2102, 1995. https://doi.org/10.1021/jm00012a008
  23. H. Mathew and R. David, "3D QSAR in Drug Design: Recent Advances", pp.117- 133,1998.
  24. N. P. Todorov and P. M. Dean, "Evaluation of a method for controlling molecular scaffolds diversity in de novo ligand design", J. Comput. Aided Mol. Des., Vol. 11, pp. 175-192, 1997. https://doi.org/10.1023/A:1008042711516
  25. N. P. Todorov and P. M. Dean, "A branch and bound method for optimal atom-type assignment in de novo ligand design", J. Comput. Aided Mol. Des., Vol. 12, pp. 335-350, 1998. https://doi.org/10.1023/A:1007994827087
  26. A. Vedani, P. Zbinden, J. P. Snyder and P. A. Greenidge, "Pseudo-receptor modeling: a new concept for the three-dimensional construction of receptor binding sites", J. Recept. Res., Vol. 13, pp. 163-177, 1993. https://doi.org/10.3109/10799899309073653
  27. A. Vedani, P. Zbinden, J. P. Snyder and P. A. Greenidge, "Pseudoreceptor modeling: the construction of three dimensional receptor surrogates", J. Am. Chem. Soc., Vol. 117, pp. 4987-4994, 1995. https://doi.org/10.1021/ja00122a030
  28. T. Yusuf, P. Ewgenij, W. Tim, G. Tim, T. Nickolay, K. Alexander, K. Tim, S. Kerstin, S. Erich, S. Roland, S. Holger, C. Timothy and S. Gisbert, "Homology Model Adjustment and Ligand Screening with a Pseudoreceptor of the Human Histamine H4 Receptor", Chem. Med. Chem., Vol. 4, pp. 820-827, 2009. https://doi.org/10.1002/cmdc.200800443
  29. P. H. Bauer, C. Cui, W. R. Liu, T. Stehle, S.C. Harrison, J. A. DeCaprio and T. L. Benjamin, "Discrimination between Sialic Acid-Containing Receptors and Pseudoreceptors Regulates Polyomavirus Spread in the Mouse", J. Virol., Vol. 73, pp. 5826-5832, 1999.
  30. M. Laura, M. Fabrizio, C. Federico and B. Maurizio, "3D QSAR studies for the b-tubulin binding site of microtubulestabilizing anticancer agents (MSAAs) A pseudoreceptor model for taxanes based on the experimental structure of tubulin", IL Farmaco., Vol. 58, pp. 659-668, 2003. https://doi.org/10.1016/S0014-827X(03)00099-5
  31. C. M. R. de Sant'Anna, R. Bicca de Alencastro and E. J. Barreiro, "Toward a platelet-activating factor pseudoreceptor 2. Three-dimensional semiempirical models for agonist and antagonist binding", J. Mol. Struct.: THEOCHEM, Vol. 490, pp. 167-180, 1999. https://doi.org/10.1016/S0166-1280(99)00097-4
  32. C. H. Chae, S. E. Yoo and W. Shin, "Novel receptor surface approach for 3D-QSAR: The weighted probe interaction energy method", J. Chem. Inf. Comput. Sci., Vol. 44, pp. 1774-1787, 2004. https://doi.org/10.1021/ci0498721
  33. A. J. Lu and J. J. Zhou, "Pseudoreceptor models and 3D-QSAR for imidazobenzodiazepines at GABA A/BzR subtypes R x 3 2 [x) 1-3, 5, and 6] via flexible atom receptor model", J. Chem. Inf. Comput. Sci., Vol. 44, pp. 1130-1136, 2004. https://doi.org/10.1021/ci034281g
  34. T. Peng, J. Pei and J. Zhou, "3D-QSAR and receptor modeling of tyrosine kinase inhibitors with flexible atom receptor model (FLARM)", J. Chem. Inf. Comput. Sci., Vol. 43, pp. 298-303, 2003. https://doi.org/10.1021/ci0256034
  35. S. Forli, F. Manetti, K. H. Altmann and M. Botta, "Evaluation of Novel Epothilone Analogues by means of a Common Pharmacophore and a QSAR Pseudoreceptor Model for Taxanes and Epothilones", Chem. Med. Chem., Vol. 5, pp. 35-40, 2010. https://doi.org/10.1002/cmdc.200900303
  36. Y. Zeng, M. Pinard, J. Jaime, L. Bourget, P. U. Le, M. D. O'Connor-McCourt, R. Gilbert and B. Massie, "A ligand-pseudoreceptor system based on de novo designed peptides for the generation of adenoviral vectors with altered tropism", J. Gene. Med., Vol. 10, pp. 355-367, 2008. https://doi.org/10.1002/jgm.1155
  37. D. G. Lloyd, C. L. Buenemann, N. P. Todorov, D. T. Manallack and P. M. Dean, "Scaffold hopping in de novo design. Ligand generation in the absence of receptor information", J. Med. Chem., Vol. 47, pp. 493-496, 2004. https://doi.org/10.1021/jm034222u
  38. A. Bassoli, M. G. B. Drew, L. Merlini and G. Morini, "General pseudoreceptor model for sweet compounds: A semiquantitative prediction of binding affinity for sweet-tasting molecules", J. Med. Chem., Vol. 45, pp. 4402-4409, 2002. https://doi.org/10.1021/jm020833v
  39. K. J. Schleifer, "Pseudoreceptor model for ryanodine derivatives at calcium release channels", J. Comput-Aided Mol. Des., Vol. 14, pp. 467-475, 2000. https://doi.org/10.1023/A:1008141819487
  40. S. Schmetzer, P. Greenidge, K. A. Kovar, M. Schulze-Alexandru and G. Folkers, "Structure-activity relationships of cannabinoids: A joint CoMFA and pseudoreceptor modelling study", J. Comput-Aided Mol. Des., Vol. 11, pp. 278-292, 1997. https://doi.org/10.1023/A:1007960712989
  41. M. K. Gilson, J. A. Given, B. L. Bush and J. A. McCammon, "The statistical-thermodynamic basis for computation of binding affinities: a critical review", Biophys. J., Vol. 72, pp. 1047-1069, 1997. https://doi.org/10.1016/S0006-3495(97)78756-3
  42. C. E. Chang and M. K. Gilson, "Tork: conformational analysis method for molecules and complexes", J. Comput. Chem., Vol. 24, pp. 1987-1998, 2003. https://doi.org/10.1002/jcc.10325
  43. W. Chen, J. Huang and M. K. Gilson, "Identification of symmetries in molecules and complexes", J. Chem. Inf. Comput. Sci., Vol. 44, pp. 1301-1313, 2004. https://doi.org/10.1021/ci049966a
  44. C. E. Chang, M. J. Potter and M. K. Gilson, "Calculation of molecular configuration integrals", J. Phys. Chem. B, Vol. 107, pp. 1048-1055, 2003. https://doi.org/10.1021/jp027149c
  45. D. E. Walters and R. M. Hinds, "Genetically evolved receptor models: A computational approach to construction of receptor models", J. Med. Chem., Vol. 37, pp. 2527-2536, 1994. https://doi.org/10.1021/jm00042a006
  46. H. Chen, J. Zhou and G. Xie, "PARM: a genetic evolved algorithm to predict bioactivity", J. Chem. Inf. Comput. Sci., Vol. 38, pp. 243-250, 1998. https://doi.org/10.1021/ci970004w