Protein adsorption on ion exchange adsorbers: A comparison of a stoichiometric and non-stoichiometric modeling approach.

Adsorption isotherm Colloidal particle adsorption model Mechanistic modeling Protein purification Scaled particle theory Steric mass action model

Journal

Journal of chromatography. A
ISSN: 1873-3778
Titre abrégé: J Chromatogr A
Pays: Netherlands
ID NLM: 9318488

Informations de publication

Date de publication:
13 Sep 2021
Historique:
received: 17 04 2021
revised: 02 07 2021
accepted: 05 07 2021
pubmed: 21 7 2021
medline: 14 10 2021
entrez: 20 7 2021
Statut: ppublish

Résumé

For mechanistic modeling of ion exchange (IEX) processes, a profound understanding of the adsorption mechanism is important. While the description of protein adsorption in IEX processes has been dominated by stoichiometric models like the steric mass action (SMA) model, discrepancies between experimental data and model results suggest that the conceptually simple stoichiometric description of protein adsorption provides not always an accurate representation of nonlinear adsorption behavior. In this work an alternative colloidal particle adsorption (CPA) model is introduced. Based on the colloidal nature of proteins, the CPA model provides a non-stoichiometric description of electrostatic interactions within IEX columns. Steric hindrance at the adsorber surface is considered by hard-body interactions between proteins using the scaled-particle theory. The model's capability of describing nonlinear protein adsorption is demonstrated by simulating adsorption isotherms of a monoclonal antibody (mAb) over a wide range of ionic strength and pH. A comparison of the CPA model with the SMA model shows comparable model results in the linear adsorption range, but significant differences in the nonlinear adsorption range due to the different mechanistic interpretation of steric hindrance in both models. The results suggest that nonlinear adsorption effects can be overestimated by the stoichiometric formalism of the SMA model and are generally better reproduced by the CPA model.

Identifiants

pubmed: 34284263
pii: S0021-9673(21)00521-5
doi: 10.1016/j.chroma.2021.462397
pii:
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

462397

Informations de copyright

Copyright © 2021. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors affiliated to GoSilico declare that the software ChromX used in this study is a commercial product of GoSilico. The presented research does not depend on the usage of ChromX, the model can be implemented in any kind of modeling software.

Auteurs

Till Briskot (T)

GoSilico GmbH, Kriegsstr. 240, Karlsruhe 76135, Germany; Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 2, Karlsruhe 76131, Germany.

Tobias Hahn (T)

GoSilico GmbH, Kriegsstr. 240, Karlsruhe 76135, Germany.

Thiemo Huuk (T)

GoSilico GmbH, Kriegsstr. 240, Karlsruhe 76135, Germany.

Jürgen Hubbuch (J)

Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 2, Karlsruhe 76131, Germany. Electronic address: juergen.hubbuch@kit.edu.

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Classifications MeSH