Modeling The Capacity Factor of Analytes in Micellar Electrokinetic Chromatography Using Computational Descriptors Modeling capacity cactor of MEKC
Iranian Journal of Pharmaceutical Sciences,
Vol. 1 No. 1 (2005),
15 January 2005
,
Page 53-57
https://doi.org/10.22037/ijps.v1.39443
Abstract
A multiple linear regression model is proposed to calculate capacity factor of analytes using structural features computed using HyperChem software. The
chemical descriptors of analytes were computed using HyperChem software and regressed against the experimental capacity factors of analytes collected from the literature. The absolute average percentage deviation (AARD) and individual percentage deviation (IPD) were calculated as accuracy criteria. The accuracy of the proposed method was compared with that of a previously reported linear solvation energy relationship (LSER). The proposed method was tested on ten experimental data sets and mean ± standard deviation of AARDs were 48.5 ± 20.4 and 130.1 ± 79.7, respectively, for the proposed and LSER models in which the mean difference was statistically significant (p<0.01). The distribution of IPDs sorted in three subgroups, i.e. £ 45%, 45%-90%, and >90 %, shows the superiority of the proposed model over the LSER. A significant improvement in capacity factor modeling was achieved and the improvement factor is about 2.7. The descriptors
could be easily computed and the calculations are straightforward. Therefore, the model is suggested to be employed in practice, however, the efforts should be continued until providing more accurate models.
- Capacity factor
- Micellar electrokinetic chromatography
- Modeling
How to Cite
References
[2] McKillop AG, Smith RM, Rowe RC, Wren AC., Modeling and prediction of electrophoretic mobilities in capillary electrophoresis: Separation of alkylpyridines., Anal. Chem. 1999; 71: 497-503.
[3] Jalali-Heravi M, Garkani-Nejad Z., Prediction of electrophoretic mobilities of alkyl- and alkenylpyridines in capillary electrophoresis using artificial neural networks., J. Chromatogr. A 2002; 971: 207-215.
[4] Liang HR, Vuorela H, Vuorela P, Riekkola MJ, Hiltunen R., Prediction of migration behaviour of flavonoids in capillary zone electrophoresis by means of topological indices., J. Chromatogr. A 1998; 798: 233-242.
[5] Li Q, Dong D, Jia R, Chen X, Hu Z, Fan BT., Development of a quantitative structure-property relationship model for predicting the electrophoretic
mobilities., Comp. Chem. 2002; 26: 245-251.
[6] Jouyban A, Yousefi BH., A quantitative structure property relationship study of electrophoretic mobility of analytes in capillary zone electrophoresis.,
Comput. Biol. Chem. 2003; 27: 297-303.
[7] Roses M, Rafols C, Bosch E, Martinez AM, Abraham MH., Solute-solvent interactions in micellar electrokinetic chromatography. Characterization of sodium dodecyl sulfate-Brij 35 micellar systems for quantitative structureactivity relationship modeling. J. Chromatogr. A 1999; 845: 217-226.
[8] Kelly KA, Burns ST, Khaledi MG., Prediction of retention in micellar electrokinetic chromatography from solute structure. 1. Sodium dodecyl sulfate micelles. Anal. Chem. 2001; 73: 6057- 6062.
[9] Taillardat-Bertschinger A, Carrupt PA, Testa B., The relative partitioning of neutral and ionized compounds in sodium dodecyl sulfate micelles measured by micellar electrokinetic capillary chromatography. Eur. J. Pharm. Sci. 2002; 15: 225-234.
[10] Fuguet E, Rafols C, Bosch E,, Abraham MH, Roses M., Solute-solvent interactions in micellar electrokinetic chromatography. III. Characterization of the selectivotyy of micellar electrokinetic chromatography systems. J. Chromatogr. A 2002; 942: 237-248.
[11] HyperChem 7.0., Molecular mechanics and quantum chemical calculations package, 2002, HyperCube Inc., Ontario, Canada.
[12] Fletcher R., Practical methods of optimization, 1980, Wiley, New York, USA.
[13] Dewar MJS, Zoebish EG, Healy EF, Stewart JJP., Development and use of quantum mechanical molecular models. 76. AM1: a new general purpose quantum mechanical molecular model., J. Am. Chem. Soc. 1985; 107: 3902-3909.
[14] Abraham MH, Chadha HS Leitao RAE, Mitchell RC, Lambert WJ, Kaliszan R, Nasal A, Haber P., Determination of solute lipophilicity, as log P(octanol) and log P(alkane) using poly(styrene–divinylbenzene) and immobilised artificial membrane stationary phases in reversed-phase high-performance liquid chromatography.,
J. Chromatogr. A 1997; 766: 35-47
- Abstract Viewed: 234 times
- IJPS_Volume 1_Issue 1_Pages 53-57 Downloaded: 162 times