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A quantitative model for partition in aqueous multiphase systems.

G Johansson, A Hartman

    European Journal of Biochemistry
    |March 16, 1976
    PubMed
    Summary
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    A new model predicts how charged molecules partition in aqueous multiphase systems based on electrical potential and molecular charge. This model accurately describes experimental data for various molecules and biological samples.

    Area of Science:

    • Biochemistry
    • Physical Chemistry
    • Separation Science

    Background:

    • Aqueous multiphase systems (AMS) are widely used for separating biomolecules.
    • Understanding the partitioning behavior of charged molecules in AMS is crucial for optimizing separation processes.
    • Existing models may not fully account for the influence of electrical potential and molecular charge.

    Purpose of the Study:

    • To develop a comprehensive model for predicting the partition coefficients of charged molecules in aqueous multiphase systems.
    • To relate partition behavior to electrical potential differences, molecular net charges, and uncharged partition coefficients.
    • To validate the model using experimental data from various charged molecules and biological mixtures.

    Main Methods:

    • Development of a theoretical model incorporating electrical potential, net charge, and uncharged partition coefficients.

    Related Experiment Videos

  • Application of the model to analyze experimental partition data for small molecules (chromate, pyridine) and biomolecules (ribonuclease A, hemoglobin, yeast lysate).
  • Comparison of model predictions with experimental data in complex three-phase systems (poly(ethylene glycol), dextran, Ficoll, water).

    • Main Results:

    • The developed model accurately predicts the partition coefficients of charged molecules in aqueous multiphase systems.
    • The model successfully describes experimental data for a diverse range of compounds, including proteins and enzyme mixtures.
    • Deviations from the model suggest pH-dependent ion uptake and highlight differences in protein solvation and enzyme forms.

    Conclusions:

    • The model provides a robust framework for understanding and predicting charged molecule partitioning in AMS.
    • The model's ability to fit experimental data demonstrates the significant role of electrical potential and molecular charge.
    • The study reveals insights into protein solvation and the heterogeneity of enzymes in biological mixtures.