Prediction of Electrophoretic Mobility of Analytes Using Abraham Solvation Parameters by Different Chemometric Methods

Title:Prediction of Electrophoretic Mobility of Analytes Using Abraham Solvation Parameters by Different Chemometric Methods

Volume: 13 Issue: 4

Author(s): Samin Hamidi, Ali Shayanfar, Hossein Hamidi, Elnaz Mehdizadeh Aghdam and Abolghasem Jouyban*

Affiliation:

• Pharmaceutical Analysis Research Center and Faculty of Pharmacy University, Tabriz University of Medical Sciences, P.O. Box: 51664, Tabriz,Iran

Keywords: Electrophoretic mobility, capillary zone electrophoresis, quantitative structure-mobility relationship, Abraham solvation parameters, multiple linear regression, artificial neural network, adaptive neuro-fuzzy inference system.

Abstract: Background: Quantitative structure-mobility relationships are proposed to estimate the electrophoretic mobility of diverse sets of analytes in capillary zone electrophoresis using Abraham solvation parameters of analytes, namely the excess molar refraction, polarizability, hydrogen bond acidity, basicity, and molar volume. Multiple linear regression (MLR) as a linear model, adaptive neuro-fuzzy inference system (ANFIS), and artificial neural network (ANN) methods were used to evaluate the nonlinear behavior of the involved parameters. The applicability of the Abraham solvation parameters to the mobility prediction of analytes was studied employing various datasets consisting of organic acids, benzoate derivatives, pyridines, and ammoniums.

Methods: To evaluate the simulation ability of the proposed models, datasets were subdivided into training and test sets in the ratio of 3:1. To evaluate the goodness of fit of the models, squared correlation coefficients (R2) between experimental and calculated mobilities were calculated.

Results: R2 values were better than 0.78 for all datasets except for organic acids, in which the ANFIS model showed better ability to predict their mobility than that of MLR and ANN. In addition, the accuracy of the models is calculated using mean percentage deviation (MPD) and the overall MPD values for test sets were better than 15% for all models.

Conclusion: The results showed the ability of the developed models to predict the electrophoretic mobility of analytes in capillary zone electrophoresis.

Cite this article as:

Hamidi Samin, Shayanfar Ali, Hamidi Hossein, Aghdam Mehdizadeh Elnaz and Jouyban Abolghasem*, Prediction of Electrophoretic Mobility of Analytes Using Abraham Solvation Parameters by Different Chemometric Methods, Current Analytical Chemistry 2017; 13 (4) . https://dx.doi.org/10.2174/1573411012666160815101243

DOI https://dx.doi.org/10.2174/1573411012666160815101243	Print ISSN 1573-4110
Publisher Name Bentham Science Publisher	Online ISSN 1875-6727