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Prediction of Partition Coefficients for Peptides in Aqueous Two-Phase Systems

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Chromatographic and Membrane Processes in Biotechnology

Part of the book series: NATO ASI Series ((NSSE,volume 204))

Abstract

A model is proposed for the prediction of partition coefficients in aqueous two-phase systems. Hydrophobicities of constituent molecules are used to predict the partitioning behavior of more complex molecules. To examine the applicability of this model, several specific compounds, including butyl acetate, aspartame, and several amino acids and peptides, were partitioned in poly(ethylene glycol) (PEG)/magnesium sulfate (MgSO4) aqueous two-phase systems. The partitioning data for the constitutent compounds were used to calculate hydrophobicities, which were then used to estimate hydrophobicities of the larger compounds. The partition coefficients were successfully predicted from these estimated hydrophobicities.

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Author information

Authors and Affiliations

  1. Center for Bioprocess and Product Development, University of Virginia, Charlottesville, VA, 22903-2442, USA

    Mark A. Eiteman & John L. Gainer

  2. Department of Chemical Engineering Thornton Hall, University of Virginia, Charlottesville, VA, 22903-2442, USA

    Mark A. Eiteman & John L. Gainer

Authors
  1. Mark A. Eiteman
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  2. John L. Gainer
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Editor information

Editors and Affiliations

  1. Department of Chemical Engineering, University of Porto, Porto, Portugal

    Carlos A. Costa

  2. Department of Chemical Engineering, Technical University of Lisbon, Lisbon, Portugal

    Joaquim S. Cabral

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© 1991 Springer Science+Business Media Dordrecht

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Eiteman, M.A., Gainer, J.L. (1991). Prediction of Partition Coefficients for Peptides in Aqueous Two-Phase Systems. In: Costa, C.A., Cabral, J.S. (eds) Chromatographic and Membrane Processes in Biotechnology. NATO ASI Series, vol 204. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3470-5_18

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  • DOI: https://doi.org/10.1007/978-94-011-3470-5_18

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-5535-2

  • Online ISBN: 978-94-011-3470-5

  • eBook Packages: Springer Book Archive

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