Skip to main content
Log in

Homology modeling of human α1β2γ2 and house fly β3 GABA receptor channels and Surflex-docking of fipronil

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

To further explore the mechanism of selective binding of the representative γ-aminobutyric acid receptors (GABARs) noncompetitive antagonist (NCA) fipronil to insect over mammalian GABARs, three-dimensional models of human α1β2γ2 and house fly β3 GABAR were generated by homology modeling, using the cryo-electron microscopy structure of the nicotinic acetylcholine receptor (nAChR) of Torpedo marmorata as a template. Fipronil was docked into the putative binding site of the human α1β2γ2 and house fly β3 receptors by Surflex-docking, and the calculated docking energies are in agreement with experimental results. The GABA receptor antagonist fipronil exhibited higher potency with house fly β3 GABAR than with human α1β2γ2 GABAR. Furthermore, analyses of Surflex-docking suggest that the H-bond interaction of fipronil with Ala2 and Thr6 in the second transmembrane segment (TM2) of these GABARs plays a relatively important role in ligand selective binding. The different subunit assemblies of human α1β2γ2 and house fly β3 GABARs may result in differential selectivity for fipronil.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7a–d

Similar content being viewed by others

References

  1. Chebib M, Johnston GA (2000) J Med Chem 43:1427–1447

    Article  CAS  Google Scholar 

  2. Bormann J (2000) Trends Pharmacol Sci 21:16–19

    Article  CAS  Google Scholar 

  3. Novère NL, Changeux JP (2001) Phil Trans R Soc B 356:1121–1130

    Article  Google Scholar 

  4. Barnard EA, Skolnick P, Olsen RW, Mohler H, Sieghart W, Biggio G, Braestrup C, Bateson AN, Langer SZ (1998) Pharmacol Rev 50:291–314

    CAS  Google Scholar 

  5. Burt DR, Kamatchi GL (1991) Faseb J 5:2916–2913

    CAS  Google Scholar 

  6. Davies PA, Hanna MC, Hales TG, Kirkness EF (1997) Nature 385:820–823

    Article  CAS  Google Scholar 

  7. Whiting PJ, Mcallister G, Vassilatis D, Bonnert TP, Heavens RP, Smith DW, Hewson L, O’Donnell R, Rigby MR, Sirinathsinghji DJS, Marshall G, Thompson SA, Wafford KA (1997) J Neurosci 17:5027–5037

    CAS  Google Scholar 

  8. McKerman RM, Whiting PJ (1996) Trends Neurosci 19:139–143

    Article  CAS  Google Scholar 

  9. Chang YC, Wang RP, Barot S, Weiss DS (1996) J Neurosci 16:5415–5424

    CAS  Google Scholar 

  10. Farrar SJ, Whiting PJ, Bonnert TP, McKernan RM (1999) J Biol Chem 274:10100–10104

    Article  CAS  Google Scholar 

  11. Ffrench-Constant RH, Mortlock DP, Shaffer CD, MacIntyre RJ, Roush RT (1991) Proc Natl Acad Sci USA 88:7209–7213

    Article  CAS  Google Scholar 

  12. Hosie AM, Aronstein K, Sattelle DB, ffrench-Constant RH (1997) Trends Neurosci 20:578–583

    Article  CAS  Google Scholar 

  13. Ffrench-Constant RH, Steichen JC, Rocheleau TA, Aronstein K, Roush RT (1993) Proc Natl Acad Sci USA 90:1957–1961

    Article  CAS  Google Scholar 

  14. Casida JE, Tomizawa M (2008) J Pestic Sci 33:4–8

    Article  CAS  Google Scholar 

  15. Hawkinson JE, Casida JE (1992) Mol Pharmacol 42:1069–1076

    CAS  Google Scholar 

  16. Cole LM, Casida JE (1992) Pestic Biochem Physiol 44:1–8

    Article  CAS  Google Scholar 

  17. Ratra GS, Casida JE (2001) Toxicol Lett 122:215–222

    Article  CAS  Google Scholar 

  18. SYBYL software, Version 7.3, Tripos Associates, St. Louis, 2006, http://www.tripos.com/

  19. Miyazawa A, Fujiyoshi Y, Unwin N (2003) Nature 423:949–955

    Article  CAS  Google Scholar 

  20. Needleman SB, Wunsch CD (1970) J Mol Biol 48:443–453

    Article  CAS  Google Scholar 

  21. Zhu ZY, Sali A, Blundell TL (1992) Protein Eng 5:43–51

    Article  CAS  Google Scholar 

  22. Jain AN (1996) J Comput Aided Mol Des 10:427–440

    Article  CAS  Google Scholar 

  23. Baker D, Sali A (2001) Science 294:93–96

    Article  CAS  Google Scholar 

  24. Barnard EA (1996) Trends Pharmacol Sci 17:305–308

    Article  CAS  Google Scholar 

  25. Campagna-Slater V, Weaver DF (2007) J Mol Graphics Model 25:721–730

    Article  CAS  Google Scholar 

  26. Casida JE, Tomizawa M (2008) J Pestic Sci 33:4–8

    Article  CAS  Google Scholar 

  27. Hisano K, Ozoe F, Huang J, Kong X, Ozoe Y (2007) Invert Neurosci 7:39–46

    Article  CAS  Google Scholar 

  28. Ratra GS, Kamita SG, Casida JE (2001) Toxicol Appl Pharmacol 172:233–240

    Article  CAS  Google Scholar 

  29. Slany A, Zezula J, Tretter V, Sieghart W (1995) Mol Pharmacol 48:385–391

    CAS  Google Scholar 

  30. Casida JE, Quistad GB (2004) J Pestic Sci 29:81–86

    Article  CAS  Google Scholar 

  31. Chen LG, Durkin KA, Casida JE (2006) Proc Natl Acad Sci USA 103:5185–5190

    Article  CAS  Google Scholar 

  32. Ffrench-Constant RH, Anthony N, Aronstein K, Rocheleau T, Stilwell G (2000) Annu Rev Entomol 48:449–466

    Article  Google Scholar 

Download references

Acknowledgment

This study was supported by National Natural Science Foundation of China; contract/grant number: 20572084

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiu-Lian Ju.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cheng, J., Ju, XL., Chen, XY. et al. Homology modeling of human α1β2γ2 and house fly β3 GABA receptor channels and Surflex-docking of fipronil. J Mol Model 15, 1145–1153 (2009). https://doi.org/10.1007/s00894-009-0477-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00894-009-0477-2

Keywords

Navigation