Application of Computer Modeling to Predict the Chromatographic Analytes Behavior

Автори

This paper analyzes the capabilities of QSRR. Moreover, we make an insight into brief theoretical information on this method development and provide a list of issues to be solved by dint of it and the issues that may arise during obtaining QSRR models. We present the classification of descriptors and software used in construction of models and a list of basic mathematical algorithms rejecting irrelevant descriptors. The advantages and disadvantages of existing QSRR models used in HPLC method are pointed out. Some examples of the QSRR method application to define differences in mechanisms of analytes separation in comparison of separation capability and classification of chromatographic columns are given. It is shown that prediction of chromatographic behavior of substances in Ag-HPLC may be made both using standard approaches of QSRR method and computer modeling of the interaction between analyte and Ag – stationary phase using modern quantum-chemical methods.

Publication year: 
2012
Issue: 
5
УДК: 
543.544.543.422.6
С. 146—152. Бібліогр.: 34 назви.
References: 

1. G. Frenking and N. Frohlich, “The Nature of the Bonding in Transition — Metal Compounds”, Chem. Rev., vol. 100, pp. 717—774, 2000.
2. B. Nikolova-Damyanova, “Retention of lipids in silver ion high-performance liquid chromatography: Facts and assumptions”, J. Chromatog. A, vol. 1216, pp. 1815—1824, 2009.
3. K. Heberger, “Quantitative structure — (chromatographic) retention relationships”, Ibid, vol. 1158, pp. 273—305, 2007.
4. R. Kaliszan, “QSRR: Quantitative Structure-(Chromatographic) Retention Relationships”, Chem Rev., vol. 107, pp. 3212—3246, 2007.
5. F. Ignatz-Hoover et al., “QSRR Correlation of Free-Radical Polymerization Chain — Transfer Constants for Styrene”, J. Chem. Inf. Comput. Sci., vol. 41, pp. 295—299, 2001.
6. A.R. Katritzky et al., “QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects”, Analytical Chemistry, vol. 72, pp. 101—109, 2000.
7. R. Todeschini and V. Consonni, Handbook of Molecular Descriptors. WILEY-VCH, Germany: Weinheim, 2000, 347 pp.
8. B.d.S. Junkes et al., “Prediction of the chromatographic retention of saturated alcohols on stationary phases of different polarity applying the novel semi—empirical topological index”, Analytica Chimica Acta, vol. 477, pp. 29—39, 2003.
9. M.I. Skvortsova et al., “Molecular similarity concept and its use for predicting the properties of chemical compounds”, Rus. Chem. Rev., vol. 75, no. 11, pp. 961—979, 2006.
10. T. Hancock et al., “A performance comparison of modern statistical techniques for molecular descriptor selection and retention prediction in chromatographic QSRR studies”, Chemom. Intell. Lab. Syst., vol. 76, pp. 185—196, 2005.
11. P.P. Sadek et al., “Study of retention processes in reversed — phase high — performance liquid chromatography by the use of the solvatochromic comparison method”, Analytical Chem., vol. 57, pp. 2971—2978, 1985.
12. N.S. Wilson et al., “Column selectivity in reversed — phase liquid chromatography I. A general quantitative relationship”, J. Chromatogr. A, vol. 961, pp. 171—193, 2002.
13. M.H. Abraham et al., “Determination of sets of solute descriptors from chromatographic measurements”, Ibid, vol. 1037, pp. 29—47, 2004.
14. J. Zhao and P.W. Carr, “A comparative study of the chromatographic selectivity of polystyrene—coated zirconia and related reversed — phase materials”, Analytical Chem., vol. 72, pp. 302—309, 2000.
15. J. Li et al., “Quantitative structure—retention relationship studies using immobilized artificial membrane chromatography I: Amended linear solvation energy relationships with the introduction of a molecular electronic factor”, J. Chromatogr. A, vol. 1132, pp. 174—182, 2006.
16. E.P. Vonk et al., “Quantitative structure—retention relationships in reversed — phase liquid chromatography using several stationary and mobile phases”, J. Sep. Sci., vol. 26, pp. 777—792, 2003.
17. M. Vitha, P.W. Carr et al., “The chemical interpretation and practice of linear solvation energy relationships in chromatography”, J. Chromatogr. A, vol. 1126, pp. 143— 194, 2006.
18. L.R. Snyder et al., “The hydrophobic — subtraction model of reversed — phase column selectivity”, Ibid, vol. 1060, pp. 77—116, 2004.
19. T. Baczek and R. Kaliszan, “Comparative characteristics of HPLC columns based on quantitative structure — retention relationships (QSRR) and hydrophobic — subtraction model”, Ibid, vol. 1075, pp. 109—115, 2005.
20. T. Baczek and R. Kaliszan, “Predictive approaches to gradient retention based on analyte structural descriptors from calculation chemistry”, Ibid, vol. 987, pp. 29—37, 2003.
21. M.A. Al-Haj et al., “Quantitative structure—retention relationships with model analytes as a means of an objective evaluation of chromatographic columns”, J. Chromatogr. Sci., vol. 39, pp. 29—38, 2001.
22. L.R. Snyder and J.W. Dolan, “The linear — solvent — strength model of gradient elution”, Adv. Chromatogr. (N.Y.), vol. 38, pp. 115—187, 1998.
23. A. Nasal et al., “Chromatographic retention parameters in medicinal chemistry and molecular pharmacology”, Curr. Med. Chem., vol. 10, pp. 381—426, 2003.
24. S. Ong and P. Pidgeon, “Thermodynamics of Solute Partitioning into Immobilized Artificial Membranes”, Analytical Chem., vol. 67, pp. 2119—2128, 1995.
25. M.A. Al-Haj et al., “Mechanism of separation on cholesterol — silica stationary phase for high — performance liquid chromatography as revealed by analysis of quantitative structure — retention relationships”, J. Pharmac. and Biomed. Analysis, vol. 18, pp. 721—728, 1998.
26. M. Jezierska et al., “Comparative study of surface topography of high performance liquid chromatography columns in terms of hydrophobicity”, Chromatographia, vol. 51, pp. 111—118, 2000.
27. A. Sandi et al., “Characterization of reversed — phase columns using the linear free energy relationship. III. Effect of the organic modifier and the mobile phase composition”, J. Chromatogr. A, vol. 893, pp. 215—234, 2000.
28. M. Turowskiet al., “Selectivity of stationary phases in reversed — phase liquid chromatography based on the dispersion interactions”, Ibid, vol. 911, pp. 177—190, 2001.
29. B. Damyanova et al., “Computational probes into the basis of silver ion chromatography: I. Silver (I) ion complexes of unsaturated fatty acids and esters”, Theochem, vol. 589, pp. 239—249, 2002.
30. Експериментальне і квантово-хімічне дослідження термодинаміки комплексоутворення метилбензолів з іоном срібла (І) / В.Н. Родіонов, Б.В. Черняєв, І.А. Левандовський та ін. // Наукові вісті НТУУ “КПІ”. — 2005. — № 1. — С. 107—115.
31. Експериментальне і квантово-хімічне дослідження термодинаміки комплексоутворення метилнафталінів із сріблом (І) / В.Н. Родіонов, Б.В. Черняєв, І.А. Левандовський та ін. // Наукові вісті НТУУ “КПІ”. — 2005. — № 3. — С. 143—152.
32. Квантово-химическая интерпретация переориентации диалкилцис-9,10-эндофумаратов на серебросодержащей неподвижной фазе / В.Н. Родионов, Б.В. Черняєв, И.А. Левандовский и др. // Теорет. и экспериментальная химия. — 2005. — 41, № 1. — С. 7—11.
33. I.A. Levandovskiy et al., “Computational and QSAR Study of the Alkylnaphthyl Ketones Adsorption on Silver- Ion Stationary Phase”, J. Mol. Mod., vol. 16, no. 3, pp. 513—522, 2010.
34. Левандовський І.А. Комп’ютерне моделювання хроматографічної поведінки алкілароматичних сполук на срібловмісній нерухомій фазі // Тези доп. ХІІІ Конф. молодих учених та студентів-хіміків південного регіону України, 3—5 листопада 2010 р., Одеса. — Одеса, 2010. — С. 15.

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