Skip to main content
SpringerLink
Log in

Quantitative Structure-Retention Relationship Modeling of the Retention Behavior of Guanidine and Imidazoline Derivatives in Reversed-Phase Thin-Layer Chromatography

  • Original Research Papers
  • Published:
JPC – Journal of Planar Chromatography – Modern TLC Aims and scope Submit manuscript

Summary

The quantitative structure-retention relationship (QSRR) study has been performed in order to investigate the retention behavior of 16 guanidine and imidazoline derivatives in the reversed-phase thin-layer chromatography (RP-TLC) system consisting of RP-8 stationary phase and the mixture of methanol, water, and ammonia as the mobile phase. Statistical results obtained in the one-parameter model with KOWWINlog P indicated that the lipophilicity of the investigated compounds could be determined based on the respective retentions. Three different modeling methodologies such as stepwise multiple linear regression (MLR), partial least squares regression (PLS), and artificial neural networks (ANN) were used in the QSRR approach and for the selection of the most important variables that describe the behavior of the investigated compounds the best. The performance of the developed stepwise MLR-QSRR, PLS-QSRR, and ANN-QSRR models was tested by cross-validation and the external test set prediction. The validated models were compared, and the optimal QSRR model (stepwise MLR-QSRR) was selected. Besides lipophilicity (KOWWINlog P), the number of secondary (aliphatic) amines (nRNHR) among the tested compounds has the strongest influence on the retention in the examined RP-TLC system. The predictive performance of the selected QSRR model suggests its applicability for a reliable prediction of the retention behavior for the congeners.

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

Access this article

Log in via an institution

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. P. Bousquet, J. Feldman, Drugs 58 (1999) 799–812.

    Article  CAS  Google Scholar 

  2. G.A. Head, S.L. Burke, Am. J. Hypertens. 13 (2000) 89S–98S.

    Article  CAS  Google Scholar 

  3. C. Farsang, J. Clin. Basic Cardiol. 4 (2001) 197–200.

    CAS  Google Scholar 

  4. C. Dardonville, I. Rozas, Med. Res. Rev. 24 (2004) 639–661.

    Article  CAS  Google Scholar 

  5. G. Olmos, R. Alemany, M.A. Boronat, J.A. Garcia-Sevilla, Ann. NY Acad. Sci. 881 (1999) 144–160.

    Article  CAS  Google Scholar 

  6. I. Ulibarri, J. Soto, J. Ruiz, J. Ballesteros, J.V. Jauregui, J.J. Meana, Ann. NY Acad. Sci. 881 (1999) 199–202.

    Article  CAS  Google Scholar 

  7. J.X. Li, Y. Zhang, Eur. J. Pharmacol. 658 (2011) 49–56.

    Article  CAS  Google Scholar 

  8. N.G. Morgan, S.L. Chan, Curr. Pharm. Des. 7 (2001) 1413–1431.

    Article  CAS  Google Scholar 

  9. D.A. Williams, T.L. Lemke (eds.), Foy’s Principles of Medicinal Chemistry, 7th edn., Lippincott Williams & Wilkins, Philadelphia, PA, 2013, pp. 351.

    Google Scholar 

  10. R.G. Evans, J.M. Haynes, Ann. NY Acad. Sci. 763 (1995) 357–360.

    Article  CAS  Google Scholar 

  11. A. Radwanska, J. Dlugokecka, R. Wasilewski, R. Kaliszan, J. Physiol. Pharmacol. 60 (2009) 131–142.

    CAS  PubMed  Google Scholar 

  12. B. Szabo, R. Urban, Ann. NY Acad. Sci. 763 (1995) 552–565.

    Article  CAS  Google Scholar 

  13. K. Nikolic, S. Filipic, D. Agbaba, Bioorg. Med. Chem. 16 (2008) 7134–7140.

    Article  CAS  Google Scholar 

  14. K. Nikolic, S. Filipic, D. Agbaba, SAR QSAR Environ. Res. 20 (2009) 133–144.

    Article  CAS  Google Scholar 

  15. A. Nasal, D. Siluk, R. Kaliszan, Curr. Med. Chem. 10 (2003) 381–426.

    Article  CAS  Google Scholar 

  16. P. Wiczling, A. Nasal, L. Kubik, R. Kaliszan, Eur. J. Pharm. Sci. 47 (2012) 1–5.

    Article  CAS  Google Scholar 

  17. S. Erić, M. Pavlović, G. Popović, D. Agbaba, J. Chromatogr. Sci. 45 (2007) 140–145.

    Article  Google Scholar 

  18. M.S.M. Shenger, S. Filipic, K. Nikolic, D. Agbaba, J. Liq. Chromatogr. Relat. Technol. 37 (2014) 2829–2845.

    Article  Google Scholar 

  19. C. Quiñones-Torrelo, S. Sagrado, R.M. Villanueva-Camañas, M.J. Medina-Hernández, J. Chromatogr. B 801 (2004) 185–198.

    Article  Google Scholar 

  20. A. Detroyer, V. Schoonjans, F. Questier, Y. Vander Hey den, A.P. Borosy, Q. Guo, D.L. Massart, J. Chromatogr. A 897 (2000) 23–36.

    Article  CAS  Google Scholar 

  21. A. Detroyer, Y. Vander Heyden, I. Cambre, D.L. Massart, J. Chromatogr. A 986 (2003) 227–238.

    Article  CAS  Google Scholar 

  22. R. Put, C. Perrin, F. Quester, D. Coomans, D.L. Massart, Y. Vander Heyden, J. Chromatogr. A 988 (2003) 261–276.

    Article  CAS  Google Scholar 

  23. K. Héberger, J. Chromatogr. A 1158 (2007) 273–305.

    Article  Google Scholar 

  24. S. Šegan, F. Andrić, A. Radoičić, D. Opsenica, B. Šolaja, M. Zlatović, D. Milojković-Opsenica, J. Sep. Sci. 34 (2011) 2659–2667.

    Article  Google Scholar 

  25. D. Dabić, M. Natić, Z. Džambaski, R. Marković, D. Milojković-Opsenica, Ž. Tešić, J. Sep. Sci. 34 (2011) 2397–2404.

    Article  Google Scholar 

  26. E.C. Bate-Smith, R.G. Westall, Biochim. Biophys. Acta 4 (1950) 427–440.

    Article  Google Scholar 

  27. E. Soczewiński, C.A. Wachtmeister, J. Chromatogr. 7 (1962) 311–320.

    Article  Google Scholar 

  28. K. Nikolic, S. Filipic, A. Smoliński, R. Kaliszan, D. Agbaba, J. Pharm. Pharm. Sci. 16 (2013) 622–647.

    Article  Google Scholar 

  29. ChemAxon Marvin 5.5.1.0 program, Budapest, Hungary, 2011, www.chemaxon.com/products.html.

  30. M. Remko, M. Swart, F.M. Bickelhaupt, Bioorgan. Med. Chem. 14 (2006) 1715–1728.

    Article  CAS  Google Scholar 

  31. M.J. Frisch, G.W. Trucks, H.B. Schlegel, et al., Gaussian 98 (Revision A.7), Gaussian, Inc., Pittsburgh, PA, 1998.

    Google Scholar 

  32. CambridgeSoft Corporation, Chem3D Ultra, version 9.0.1, Cambridge, MA, 2005.

  33. Molinspiration software or free molecular property calculation services, www.molinspiration.com.

  34. Talete srl, DRAGON (Software for Molecular Descriptor Calculation), Version 6.0, 2010, http://www.talete.mi.it/.

  35. R.G. Parr, R.G. Pearson, J. Am. Chem. Soc. 105 (1983) 7512–7516.

    Article  CAS  Google Scholar 

  36. Tetko IV. Virtual Computational Chemistry Laboratory, www.vcclab.org.

  37. SciFinder Scholar – CAS, log P calculated using Advanced Chemistry Development (ACD/Labs), Software V11.02 (©1994–2013 ACD/Labs), https://scifnder.cas.org/.

  38. CS Chem Offce, Version 7.0, Cambridge Soft Corporation, Cambridge, MA, 2001.

  39. Umetrics AB, SIMCA P+ program, Version 12.0.0.0, Umeå, May 20, 2008, www.umetrics.com.

  40. L. Eriksson, E. Johansson, N. Kettaneh-Wold, J. Trygg, C. Wikstrom, S. Wol (eds.), Multi-and Megavariate Data Analysis. Basic Principles and Applications I, 2nd edn., Umetrics Academy, Umeå, 2001.

  41. STATISTICA Neural Networks 4.0, StatSoft, Inc., Tulsa, OK, 1998.

  42. Y.X. Zhang, Talanta 73 (2007) 68–75.

    Article  CAS  Google Scholar 

  43. V.K. Gupta, H. Khani, B. Ahmadi-Roudi, S. Mirakhorli, E. Fereyduni, S. Agarwal, Talanta 83 (2011) 1014–1022.

    Article  CAS  Google Scholar 

  44. M. Jalali-Heravi, Z.J. Garkani-Nejad, J. Chromatogr. A 971 (2002) 207–215.

    Article  CAS  Google Scholar 

  45. S. Filipic, K. Nikolic, I. Vovk, M. Krizman, D. Agbaba, Electrophoresis 34 (2013) 471–482.

    Article  CAS  Google Scholar 

  46. V. Dobričić, B. Marković, K. Nikolic, V. Savić, S. Vladimirov, O. Čudina, Eur. J. Pharm. Sci. 52 (2014) 95–108.

    Article  Google Scholar 

  47. R. Mannhold, G.I. Poda, I.V. Tetko, J. Pharm. Sci. 98 (2009) 861–893.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, Belgrade, Serbia

    Slavica Filipic, Milica Elek, Katarina Nikolic & Danica Agbaba

Authors
  1. Slavica Filipic
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Milica Elek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Katarina Nikolic
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Danica Agbaba
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Danica Agbaba.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Filipic, S., Elek, M., Nikolic, K. et al. Quantitative Structure-Retention Relationship Modeling of the Retention Behavior of Guanidine and Imidazoline Derivatives in Reversed-Phase Thin-Layer Chromatography. JPC-J Planar Chromat 28, 119–125 (2015). https://doi.org/10.1556/JPC.28.2015.2.6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1556/JPC.28.2015.2.6

Key Words

Search

Navigation