alexa Simulation of Frontal Protein Affinity Chromatography Using MATLAB | OMICS International
ISSN: 2157-7048

Journal of Chemical Engineering & Process Technology
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Research Article

Simulation of Frontal Protein Affinity Chromatography Using MATLAB

Patricia Guerrero-German1*, Rosa Ma. Montesinos-Cisneros2 and Armando Tejeda-Mansir3
1Department of Chemical Engineering and Metallurgy, University of Sonora, L. Blvd Encinas and Rosales, Hermosillo, Sonora, Mexico
2Department of Mathematics, University of Sonora, L. Blvd Encinas and Rosales, Hermosillo, Sonora, Mexico
3Department of Scientific and Technological Research, University of Sonora, Luis Encinas and Rosales Blvd, Hermosillo, Sonora, Mexico
Corresponding Author : Patricia Guerrero-German
Department of Chemical Engineering and Metallurgy
University of Sonora. L. Blvd Encinas and Rosales
Hermosillo, Sonora, Mexico
Tel: 52(662)259-2106
E-mail: [email protected]
Received May 21, 2012; Accepted July 02, 2012; Published July 05, 2012
Citation: Guerrero-German P, Montesinos-Cisneros RM, Tejeda-Mansir A (2012) Simulation of Frontal Protein Affinity Chromatography Using MATLAB. J Chem Eng Process Technol 3:138. doi:10.4172/2157-7048.1000138
Copyright: © 2012 Guerrero-German P, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

In this study a transport model that includes axial dispersion in the bulk liquid, pore diffusion, external film resistance and finite kinetic rate, was used to mathematically describe a frontal affinity chromatography system. The corresponding differential equations system was solved in a simple and accurate form by using the numerical method of lines implemented in MATLAB. The solution was compared with experimental data from literature and the analytic Thomas solution. The frontal affinity chromatography of lysozyme to Cibacron Blue Sepharose was used as a model system. A good fit to the experimental data was obtained with the simulated runs of the transport model using this methodology. This approach was used to perform a parametric analysis of the experimental frontal affinity system. The solution of the transport model results in simple way to predict frontal affinity performance as well a better understanding of the fundamental mechanisms responsible for the separation.

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