Skip to main content
Log in

Chemometric estimation of the RP TLC retention behaviour of some estrane derivatives by using multivariate regression methods

  • Research Article
  • Published:
Central European Journal of Chemistry

Abstract

Quantitative structure-retention relationship (QSRR) was developed for a series of estrane derivatives, on the basis of their retention data, obtained in reversed-phase thin-layer chromatography (RP TLC), and in silico molecular descriptors. Physicochemical and topological descriptors, as well as molecular bulkiness descriptors, were calculated from the optimized molecular structures. Full geometry optimization was achieved by using Austin Model 1 (AM1) semi-empirical molecular orbital method. In the present study, QSRR analysis was based on principal component analysis (PCA), multiple linear regression (MLR) and partial least squares (PLS) method. PCA was applied in order to reveal similarities or dissimilarities between analytes, and MLR and PLS regression methods were carried out in order to identify the most important in silico molecular descriptors and quantify their influence on the retention behaviour of studied compounds. Physically meaningful and statistically significant structure-retention relationships were established.

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.

Similar content being viewed by others

References

  1. K. Héberger, J. Chromatogr. A 1158, 273 (2007)

    Article  Google Scholar 

  2. T. Cserhati, E. Forgacs, J. AOAC Int. 81, 1105 (1998)

    Google Scholar 

  3. Q.S. Wang, L. Zhang, J. Liq. Chromatogr. Relat. Technol. 22, 1 (1999)

    Article  Google Scholar 

  4. J. Trifković, F. Andrić, P. Ristivojević, D. Andrić, Ž.Lj. Tešić, D.M. Milojković-Opsenica, J. Sep. Sci. 33, 2619 (2010)

    Article  Google Scholar 

  5. R. Kaliszan, Chem. Rev. 107, 3212 (2007)

    Article  CAS  Google Scholar 

  6. Z. Chilmonczyk, A. Nikitiuk, A.Z. Wilczewska, J.W. Morzycki, J. Witowska-Jarosz, Acta Cromatogr. 18, 93 (2007)

    CAS  Google Scholar 

  7. M. Salo, H. Sirén, P. Volin, S. Wiedmer, H. Vuorela, J. Chromatogr. A 728, 83 (1996)

    Article  CAS  Google Scholar 

  8. T. Tosti, M. Natić, D. Dabić, D. Milić, D. Milojković-Opsenica, Ž. Tešić, J. Sep. Sci. 35, 2693 (2012)

    Article  CAS  Google Scholar 

  9. C.G. Georgakopoulos, J.C. Kiburis, J. Chromatogr. B 867, 151 (1996)

    Google Scholar 

  10. A.G. Fragkaki, A. Tsantili-Kakoulidou, Y.S. Angelis, M. Koupparis, C. Georgakopoulos, J. Chromatogr. A 1216, 8404 (2009)

    Article  CAS  Google Scholar 

  11. C.G. Georgakopoulos, O.G. Tsika, J.C. Kiburis, P.C. Jurs, Anal. Chem. 63, 2025 (1991)

    Article  CAS  Google Scholar 

  12. A.G. Fragkaki, E. Farmaki, N. Thomaidis, A. Tsantili-Kakoulidou, Y.S. Angelis, M. Koupparis, C. Georgakopoulos, J. Chromatogr. A 1256, 232 (2012)

    Article  CAS  Google Scholar 

  13. L.I. Nord, D. Fransson, S.P. Jacobsson, Chemom. Intell. Lab. Syst. 44, 257 (1998)

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  15. S.M. Petrovic, E. Loncar, Lj. Kolarov, V. Pejanovic, J. Chromatogr. Sci. 40, 170 (2002)

    Article  Google Scholar 

  16. ChemBioOffice 2010, PerkinElmer Informatics, http://www.cambridgesoft.com/

    Google Scholar 

  17. MOPAC2012, James J. P. Stewart, Stewart Computational Chemistry, Colorado Springs, CO, USA, http://OpenMOPAC.net (2012)

    Google Scholar 

  18. MarvinSketch 5.11.4, 2012, ChemAxon, http://www.chemaxon.com/

  19. R. Put, Y. Vander Heyden, Anal. Chim. Acta, 602, 164 (2007)

    Article  CAS  Google Scholar 

  20. J. Li, J. Sun, Z. He, J. Chromatogr. A 1140, 174 (2007)

    Article  CAS  Google Scholar 

  21. Z. Királova, K. Šnuderl, F. Kraic, J. Mocak, Acta Chim. Slov. 1, 143, (2008)

    Google Scholar 

  22. K.H. Esbensen, Multivariate Data Analysis — In Practice: An Introduction to Multivariate Data Analysis and Experimental Design, 5th Edition, CAMO Software AS, USA (2009)

    Google Scholar 

  23. J.N. Miller, J.C. Miller, Statistics and Chemometrics for Analytical Chemistry, 6th edition (Pearson Education Limited, Harlow, UK, 2010)

    Google Scholar 

  24. N. Minovski, A. Jezierska-Mazzarello, M. Vračko, T. Šolmajer, Cent. Eur. J. Chem. 9, 855 (2011)

    Article  CAS  Google Scholar 

  25. R.G. Brereton, Chemometrics, Data Analysis for the Laboratory and Chemical Plant (Wiley, Chichester, England, 2003)

    Google Scholar 

  26. Eigenvector Research, Inc. http://www.eigenvector.com/

  27. The MathWorks Inc, Natick, MA, USA, http://www.mathworks.com/

  28. J. Hintze, NCSS and GESS, NCSS, LLC, Kaysville, Utah, http://www.ncss.com/

  29. S.O. Podunavac-Kuzmanović, L.R. Jevrić, S.Z. Kovačević, N.D. Kalajdžija, APTEFF 43, 273 (2012)

    Article  Google Scholar 

  30. R. Supratim, C. Sengupta, K. Roy, Cent. Eur. J. Chem. 6, 267 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Strahinja Z. Kovačević.

Electronic supplementary material

About this article

Cite this article

Kovačević, S.Z., Jevrić, L.R., Podunavac Kuzmanović, S.O. et al. Chemometric estimation of the RP TLC retention behaviour of some estrane derivatives by using multivariate regression methods. cent.eur.j.chem. 11, 2031–2039 (2013). https://doi.org/10.2478/s11532-013-0328-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2478/s11532-013-0328-y

Keywords

Navigation