Skip to main content
Log in

A new proposed model of aldose reductase enzyme inhibition on the basis of an artificial intelligence approach: A computer automated structure evaluation (case) study

  • Molecular Mechanics
  • Published:
Journal of Mathematical Chemistry Aims and scope Submit manuscript

Abstract

A large number of inhibitors of aldose reductase enzyme were submitted to the CASE (computer automated structure evaluation) program in order to ascertain the topological features relevant to activity. On the basis of the twenty-six biophores (activating fragments) and one biophobe (inactivating fragment), a new proposed interaction model was suggested for an aldose reductase enzyme with the chemical inhibitors. The critical relationship between enzyme inhibition and the structure of inhibitors is believed to depend on the relative positions of subordinate regions within the inhibitor structure.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. K. Lindsday, B.G. Buchanan, E.A. Feigenbaum and J. Lederberg,Application of Artificial Intelligence for Organic Chemistry: The DENDRAL Project (McGraw-Hill, New York, 1980).

    Google Scholar 

  2. R.O. Duda and E.H. Shortlife, Science 220 (1983) 261.

    Google Scholar 

  3. R. Osman, H. Weinstein, and J.P. Green, ACS Symp. Ser. 112 (1979) 21.

    Google Scholar 

  4. K. Yuta and P.C. Jurs, J. Med. Chem. 24 (1981) 241.

    Google Scholar 

  5. S. Dowe, K. Fronke, O.L. Monshjan, W.A. Schkuljev and L.W. Chashanjan, J. Med. Chem. 22 (1982) 521.

    Google Scholar 

  6. L.B. Kier, in:Molecular Orbital Theory, ed. L.B. Kier (Academic Press, New York, 1971).

    Google Scholar 

  7. G. Klopman, J. Amer. Chem. Soc., 106 (1984) 7315.

    Google Scholar 

  8. G. Klopman, M. MacGonigal, J. Chem. Inf. Comput. Sci. 106 21 (1981) 48.

    Google Scholar 

  9. G. Klopman, and R. Contreras, Mol. Pharmacol. 27 (1985) 86.

    Google Scholar 

  10. G. Klopman and A.N. Kalos, J. Theor. Biol. 118 (1986) 199.

    Google Scholar 

  11. G. Klopman, O.T. Macina, E.J. Simon and J.M. Miller, J. Mol. Struct. 134 (1986) 299.

    Google Scholar 

  12. G. Klopman and E. Buyukbingol, Mol. Pharmacol. 34 (1988) 852.

    Google Scholar 

  13. J.H. Kinoshita, D. Dvornik, M. Kraml and K.H. Gabbay, Biochim. Biophys. Acta 158 (1968) 472.

    Google Scholar 

  14. P.F. Kador and N.E. Sharpless, Biophys. Chem. 8 (1978) 81

    Google Scholar 

  15. S.D. Varma, I. Mikuni and J.H. Kinoshita, Science 188 (1975) 1215.

    Google Scholar 

  16. J. DeRuiter, A.N. Brubaker, W.L. Whitmer and J.L. Stein, Jr., J. Med. Chem. 29 (1986) 2024.

    Google Scholar 

  17. P.F. Kador, N.E. Sharpless and J.D. Goosey, Prog. Clin. Biol. Res. 114 (1982) 243.

    Google Scholar 

  18. J.R. Pfister and L.D. Goosey, Prog. Clin. Biol. Res. 114 (1982) 243.

    Google Scholar 

  19. J.R. Pfister and L.D. Waterbury, J. Med. Chem. 23 (1980) 1264.

    Google Scholar 

  20. K. Inagaki, I. Miwa, T. Yashiro and J. Okuda, Chem. Pharm. Bull. 30 (1982) 3244.

    Google Scholar 

  21. I. Miwa, M. Hirano, K. Inagaki, C. Belbeoch and J. Okuda, Biochem. Pharmacol. 36 (1987) 2789.

    Google Scholar 

  22. J.P. Rizzi, R.C. Schnur, N.J. Hutson, K.G. Kraus and P.R. Kelbaugh, J. Med. Chem. 32 (1989) 1208.

    Google Scholar 

  23. M.J. Peterson, R. Sarges, C.E. Aldinger and D.P. MacDonald, Metabolism 28, Suppl. 1 (1979) 456.

    Google Scholar 

  24. P.F. Kador, W.G. Robinson, Jr. and J.H. Kinoshita, Ann. Rev. Pharmacol. Toxicol. 25 (1985) 691.

    Google Scholar 

  25. J.H. Kinoshita, S. Fukushi, P.F. Kador and L.O. Merola Metabolism 28 (1979) 462.

    Google Scholar 

  26. P.F. Kador and N.E. Sharpless, Mol. Pharmacol. 24 (1983) 521.

    Google Scholar 

  27. P.F. Kador, J.H. Kinoshita and N.E. Sharpless, Metabolism 35 (1986) 109.

    Google Scholar 

  28. P.F. Kador, J.D. Goosey, N.E. Sharpless, J. Kolish and D.D. Miller, Eur. J. Med. Chem. 16 (1981) 293.

    Google Scholar 

  29. J.H. Kinoshita, P.F. Kador and M. Catiles, J. Amer. Med. Assoc. 246 (1981) 257.

    Google Scholar 

  30. K.H. Gabbay and J.B. O'Sullivan, Diabetes 17 (1986) 239.

    Google Scholar 

  31. J.H. Kinoshita, L.O. Merola, K. Satoh and E. Dikmak, Nature (London) 194 (1962) 1085.

    Google Scholar 

  32. P.F. Kador, J.H. Kinoshita and N.E. Sharpless, J. Med. Chem. 28 (1985) 841.

    Google Scholar 

  33. D. Dvornik Ann. Rep. Med. Chem. 13 (1978) 159.

    Google Scholar 

  34. P.R. Andrews, D.L. Craik and J.L. Martin, J. Med. Chem. 27 (1984) 1648.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Buyukbingol, E., Klopman, G. A new proposed model of aldose reductase enzyme inhibition on the basis of an artificial intelligence approach: A computer automated structure evaluation (case) study. J Math Chem 8, 195–205 (1991). https://doi.org/10.1007/BF01166936

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01166936

Keywords

Navigation