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Journal of Molecular Modeling

, Volume 16, Issue 1, pp 155–161 | Cite as

Generation of a 3D model for human GABA transporter hGAT-1 using molecular modeling and investigation of the binding of GABA

  • Thomas Wein
  • Klaus T. WannerEmail author
Short Comments

Abstract

A three-dimensional model of the human Na+/Cl-dependent γ-aminobutyric acid (GABA) transporter hGAT-1 was developed by homology modeling and refined by subsequent molecular modeling using the crystal structure of a bacterial homologue leucine transporter from Aquifex aeolicus (LeuTAa) as the template. Protein structure quality checks show that the resulting structure is particularly suited for the analysis of the substrate binding pocket and virtual screening experiments. Interactions of GABA and the substrate binding pocket were investigated using docking studies. The difference of 6 out of 13 substrate interacting side chains between hGAT-1 and LeuTAa lead to the different substrate preference which can be explained using our three-dimensional model of hGAT-1. In particular the replacement of serine 256 and isoleucine 359 in LeuTAa with glycine and threonine in hGAT-1 seems to facilitate the selection of GABA as the main substrate by changing the hydrogen bonding pattern in the active site to the amino group of the substrate. For a set of 12 compounds flexible docking experiments were performed using LigandFit in combination with the Jain scoring function. With few exceptions the obtained rank order of potency was in line with experimental data. Thus, the method can be assumed to give at least a rough estimate of the potency of the potential of GABA uptake inhibitors.

Keywords

Docking Homology modeling GABA GABA transporter GAT-1 

References

  1. 1.
    Nelson H, Mandiyan S, Nelson N (1990) FEBS Lett 269:181–184CrossRefGoogle Scholar
  2. 2.
    Borden LA, Smith KE, Hartig PR, Branchek TA, Weinshank RL (1992) J Biol Chem 267:21098–21104Google Scholar
  3. 3.
    Guastella J, Nelson N, Nelson H, Czyzyk L, Keynan S, Miedel MC, Davidson N, Lester HA, Kanner BI (1990) Science 249:1303–1306CrossRefGoogle Scholar
  4. 4.
    Masson J, Sagné C, Hamon M, Mestikawy SE (1999) Pharmacol Rev 51:439–464Google Scholar
  5. 5.
    Chen N, Reith MEA, Quick MW (2004) Pflugers Arch 447:519–531CrossRefGoogle Scholar
  6. 6.
    Gether U, Andersen PH, Larsson OM, Schousboe A (2006) Trends Pharmacol Sci 27:375–383CrossRefGoogle Scholar
  7. 7.
    Yamashita A, Singh SK, Kawate T, Jin Y, Gouaux E (2005) Nature 437:215–223CrossRefGoogle Scholar
  8. 8.
    Dodd JR, Christi DL (2007) J Biol Chem 282:15528–15533CrossRefGoogle Scholar
  9. 9.
    Beuming T, Shi L, Javitch JA, Weinstein H (2006) Mol Pharmacol 70:1630–1642CrossRefGoogle Scholar
  10. 10.
    Palló A, Bencsura A, Héja L, Beke T, Perczel A, Kardos J, Simon A (2007) Biochem Biophys Res Commun 364:952–958CrossRefGoogle Scholar
  11. 11.
    Boeckmann B, Bairoch A, Apweiler R, Blatter M, Estreicher A, Gasteiger E, Martin MJ, Michoud K, O'Donovan C, Phan I, Pilbout S, Schneider M (2003) Nucleic Acids Res 31:365–370CrossRefGoogle Scholar
  12. 12.
    Bernstein FC, Koetzle TF, Williams GJB, Meyer EF Jr, Brice MD, Rodgers JR, Kennard O, Shimanouchi T, Tasumi M (1977) J Mol Biol 112:535–542CrossRefGoogle Scholar
  13. 13.
    Sali A, Blundell TL (1993) J Mol Biol 234:779–815CrossRefGoogle Scholar
  14. 14.
    van der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC (2005) J Comput Chem 26:1701–1718CrossRefGoogle Scholar
  15. 15.
    Hess B, Kutzner C, van der Spoel D (2008) Lindahl E 4:435–447Google Scholar
  16. 16.
    Scott WRP, Hunenberger PH, Tironi IG, Mark AE, Billeter SR, Fennen J, Torda AE, Huber T, Kruger P, van Gunsteren WF (1999) J Phys Chem A 103:3596–3607CrossRefGoogle Scholar
  17. 17.
    Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG (1995) J Chem Phys 103:8577–8592CrossRefGoogle Scholar
  18. 18.
    Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) J App Cryst 26:283–291CrossRefGoogle Scholar
  19. 19.
    Lüthy R, Bowie JU, Eisenberg D (1992) Nature 356:83–85CrossRefGoogle Scholar
  20. 20.
    Maple JR, Hwang MJ, Stockfisch TP, Dinur U, Waldman M, Ewig CS, Hagler AT (1994) J Comput Chem 15:162–182CrossRefGoogle Scholar
  21. 21.
    Venkatachalam CM, Jiang X, Oldfield T, Waldman M (2003) J Mol Graph Model 2:289–307CrossRefGoogle Scholar
  22. 22.
    Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ (1998) J Comput Chem 19:1639–1662CrossRefGoogle Scholar
  23. 23.
    Moustakas DT, Lang PT, Pegg S, Pettersen E, Kuntz ID, Brooijmans N, Rizzo RC (2006) J Comput-Aided Mol Design 20:601–619CrossRefGoogle Scholar
  24. 24.
    Zsoldos Z, Reid D, Simon A, Sadjad SB, Johnson AP (2007) J Mol Graph Model 26:198–212CrossRefGoogle Scholar
  25. 25.
    Rarey M, Kramer B, Lengauer T, Klebe G (1996) J Mol Biol 261:470–489CrossRefGoogle Scholar
  26. 26.
    Jones G, Willet P, Glen RC, Leach AR, Taylor R (1997) J Mol Biol 267:727–748CrossRefGoogle Scholar
  27. 27.
    Jain AN (1996) J Comput-Aided Mol Design 10:427–440CrossRefGoogle Scholar
  28. 28.
    Kanner B, Zomot E (2008) Chem Rev 108(5):1654–1668CrossRefGoogle Scholar
  29. 29.
    Kragler A, Höfner G, Wanner KT (2008) Eur J Med Chem 43:2404–2411CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.Department of Pharmacy, Center for Drug ResearchLudwig-Maximilians-University MunichMunichGermany

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