DOI QR코드

DOI QR Code

Classification of Piperazinylalkylisoxazole Library by Recursive Partitioning

  • Kim, Hye-Jung (Life Sciences Division, Korea Institute of Science and Technology) ;
  • Park, Woo-Kyu (Pharmaceutical Screening Research Team, Korea Research Institute of Chemical Technology) ;
  • Cho, Yong-Seo (Life Sciences Division, Korea Institute of Science and Technology) ;
  • No, Kyoung-Tai (Department of Biotechnology, Yonsei University) ;
  • Koh, Hun-Yeong (Department of Chemistry, Inha University) ;
  • Choo, Hyun-Ah (Life Sciences Division, Korea Institute of Science and Technology) ;
  • Pae, Ae-Nim (Life Sciences Division, Korea Institute of Science and Technology)
  • 발행 : 2008.01.20

초록

A piperazinylalkylisoxazole library containing 86 compounds was constructed and evaluated for the binding affinities to dopamine (D3) and serotonin (5-HT2A/2C) receptor to develop antipsychotics. Dopamine antagonists (DA) showing selectivity for D3 receptor over the D2 receptor, serotonin antagonists (SA), and serotonin-dopamine dual antagonists (SDA) were identified based on their binding affinity and selectivity. The analogues were divided into three groups of 7 DAs (D3), 33 SAs (5-HT2A/2C), and 46 SDAs (D3 and 5-HT2A/2C). A classification model was generated for identifying structural characteristics of those antagonists with different affinity profiles. On the basis of the results from our previous study, we conducted the generation of the decision trees by the recursive-partitioning (RP) method using Cerius2 2D descriptors, and identified and interpreted the descriptors that discriminate in-house antipsychotic compounds.

키워드

참고문헌

  1. Creese, I.; Burt, D. R.; Snyder, S. H. Science 1976, 192(4238), 481-3 https://doi.org/10.1126/science.3854
  2. Seeman, P.; Lee, T.; Chau-Wong, M.; Wong, K. Nature 1976, 261(5562), 717-9 https://doi.org/10.1038/261717a0
  3. Bouthenet, M. L.; Souil, E.; Martres, M. P.; Sokoloff, P.; Giros, B.; Schwartz, J. C. Brain Res. 1991, 564(2), 203-19 https://doi.org/10.1016/0006-8993(91)91456-B
  4. Meltzer, H. Y. J. Clin. Psychiatry 1994, 55(Suppl B), 47-52
  5. Casey, D. E. Schizophr. Res. 1999, 35(suppl), S61-S66 https://doi.org/10.1016/S0920-9964(98)00160-1
  6. Moller, H. J. Eur. Arch. Psychiatry Clin. Neurosci. 1999, 249(suppl 4), 99-107 https://doi.org/10.1007/PL00014191
  7. Green, M. F.; Kern, R. S.; Braff, D. L.; Mintz, J. Schizophr. Bull. 2000, 26, 119-136 https://doi.org/10.1093/oxfordjournals.schbul.a033430
  8. Wahlbeck, K.; Cheine, M.; Tuisku, K.; Ahokas, A.; Joffe, G.; Rimon, R. Prog. Neuropsychopharmacol Biol. Psychiatry 2000, 24(6), 911-22 https://doi.org/10.1016/S0278-5846(00)00118-4
  9. Padich, R. A.; McCloskey, T. C.; Kehne, J. H. Psychopharmacology (Berl) 1996, 124(1-2), 107-16 https://doi.org/10.1007/BF02245610
  10. Roth, B. L.; Craigo, S. C.; Choudhary, M. S.; Uluer, A.; Monsma, F. J., Jr.; Shen, Y.; Meltzer, H. Y.; Sibley, D. R. J. Pharmacol. Exp. Ther. 1994, 268(3), 1403-10
  11. Cha, M. Y.; Choi, B. C.; Kang, K. H.; Pae, A. N.; Choi, K. I.; Cho, Y. S.; Koh, H. Y.; Lee, H. Y.; Jung, D.; Kong, J. Y. Bioorg. Med. Chem. Lett. 2002, 12(10), 1327-30 https://doi.org/10.1016/S0960-894X(02)00179-8
  12. Kim, H. J.; Choo, H.; Cho, Y. S.; Koh, H. Y.; No, K. T.; Pae, A. N. Bioorg. Med. Chem. 2006, 14(8), 2763-70 https://doi.org/10.1016/j.bmc.2005.11.059
  13. Breiman, L.; Friedman, J. H.; Olshen, R. A.; Stone, C. J. Classification and Regression Trees; Wadsworth: Belmont, CA, 1984
  14. Everitt, B. S.; Dunn, G. Applied Multivariate Analysis; Oxford University Press; New York, 1992
  15. Dunn III, W. J.; Wold, S. Chemometric Methods in Molecular Design; VCH: New York, 1995; pp 179-193
  16. Neural Networks in Chemistry & Drug Design, 2nd ed.; Zupan, J., Gasteiger, J., Eds.; Wiley-VCH: Weinheim, 1999
  17. Bronowska, A.; Les, A.; Chilmonczyk, Z.; Filipek, S.; Edvardsen, O.; Ostensen, R.; Sylte, I. Bioorg. Med. Chem. 2001, 9(4), 881-95 https://doi.org/10.1016/S0968-0896(00)00307-2