Prediction of Reversed-Phase Liquid Chromatography Retention Parameters for Phenylisothiocyanate Derivatives of Amino Acids

Open access


We report our experience with highly polar and charged analyte retention parameter prediction for a reversed-phase high-performance liquid chromatographic method. The solvatic retention model has been used to predict retention of phenylisothiocyanate derivatives of 25 natural amino acids under gradient elution conditions. Retention factors have been calculated from molecular parameters of analyte structures and from the column and eluent characteristics. A step-by-step method which includes the first guess prediction of initial conditions from structural formula and fine tuning of the retention model parameters using data from successive runs can substantially save method development time

1. Snyder, L.R., Kirkland, J.J., Gajch, J.L. (1998). Practical HPLC method development, 2nd ed. New York: John Wiley&Sons.

2. Snyder, L.R., Dolan, J.W. (2007). High-Performance Gradient Elution-The Practical Application of the Linear-Solvent-Strength Model. Hoboken, New York: Wiley-Interscience, John Wiley&Sons, Inc.

3. Kromidas, S. (2006). HPLC Made to Measure. A Practical Handbook for Optimization. Weinheim: WILEY-VCH Verlag GmbH&Co.

4. Rafferty, J. L, Siepmann, J. I, Schure, M. R. (2009). Understanding the retention mechanism in reversed-phase liquid chromatography: insights from molecular simulation. Advances in Chromatography, 48, 1-55, edit. Grushka, E., Grinberg, N.: CRC Press, Taylor & Francis Group.

5. Put, R., Vander Heyden, Y. (2007). Review on modelling aspects in reversed-phase liquid chromatographic quantitative structure-retention relationships. Anal. Chim. Acta, 602 (2), 164-172.

6. Heberger, K. (2007). Quantitative structure-(chromatographic) retention relationships. J. Chromatogr. A, 1158 (1-2), 273-305.

7. Vitha, M., Carr, P.W. (2006). The chemical interpretation and practice of linear solvation energy relationships in chromatography. J. Chromatogr. A, 1126 (1-2), 143-194.




11. Galushko, S. V. (1991). Calculation of retention and selectivity in reversed-phase liquid chromatography. J. Chromatogr. A, 552, 91-102.

12. Galushko, S.V., Kamenchuk, A.A., Pit, G.L. (1994). Calculation of retention in reversedphase liquid chromatography: IV. ChromDream software for the selection of initial conditions and for simulating chromatographic behaviour. J. Chromatogr. A, 660 (1-2), 47-59.

13. Galushko, S.V. (1993). The calculation of retention and selectivity in reversed-phase liquid chromatography II. Methanol-water eluents. Chromatogr., 36 (1), 39-42.

14. Goluško, J. (2007). Solvātu sorbcijas modeļa izmantošana sorbcijas prognozēšanai apgrieztās fāzes augsti efektīvajā šķidrumu hromatogrāfijā. Promocijas darbs. Rīga.

15. Horváth, C., Melander, W., Molnár, I. (1976). Solvophobic interactions in liquid chromatography with nonpolar stationary phases. J. Chromatogr. A, 125 (1), 129-156.

16. Baczek, T., Kaliszan, R. (2002). Combination of linear solvent strength model and quantitative structure-retention relationships as a comprehensive procedure of approximate prediction of retention in gradient liquid chromatography. J. Chromatogr. A, 962 (1-2), 41-55.

17. Baczek, T., Kaliszan, R. (2003). Predictive approaches to gradient retention based on analyte structural descriptors from calculation chemistry. J. Chromatogr. A, 987 (1-2), 29-37.

18. Du, H., Wang, J., Yao, X., Hu, Z. (2009). Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine. J. Chromatogr. Sci., 47 (5), 396-404.

19. Kaliszan, R., Wiczling, P., Markuszewski, M.J., Al-Haj, M.A. (2011). Thermodynamic vs. extrathermodynamic modeling of chromatographic retention. J. Chromatogr. A, 1218 (31), 5120-5230.

20. Hewitt, E.H., Lukulay, P., Galushko, S. (2006). Implementation of a rapid and automated high performance liquid chromatography method development strategy for pharmaceutical drug candidates. J. Chromatogr. A, 1107 (1-2), 79-87.

21. Xiao, K.P., Xiong, Y., Zhu, L.F., Rustum, A M. (2007). Efficient method development strategy for challenging separation of pharmaceutical molecules using advanced chromatographic technologies. J. Chromatogr. A, 1163 (1-2), 145-156.

22. Golusko, J., Mekšs, P., Shyshkina, I., Galushko, S. (2008). Prediction of Retention in Gradient Reversed -Phase Liquid Chromatography Using Chemical Structure and Column Characteristics. Latvian J. Chem., 2, 132-142.

23. Mengerink, A.Y., Peters, R., Wal, Sj. van der, Claessens, H.A., Cramers, C.A (2002). Analysis of linear and cyclic oligomers in polyamide-6 without sample preparation by liquid chromatography using the sandwich injection method: III. Separation mechanism and gradient optimization. J. Chromatogr. A, 949 (1-2), 307-326.

24. Hughes, A.B. (2006). Amino Acids, Peptides and Protein in Organic Chemistry. John Wiley&Sons Ltd.

25. Mant, C.T., Zhou, N.E., Hodges, R.S. (1992). Amino acids and peptides. J. Chromatogr., 13, B76-B87.

26. Thomas, M.D. (1997). Textbook of Biochemistry with Clinical Correlations, 4th ed., John Wiley&Sons Ltd.

Latvian Journal of Chemistry

The Journal of Riga Technical University

Journal Information


All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 241 166 13
PDF Downloads 92 76 10