Computational model for effects of ligand/receptor binding properties on interleukin-2 trafficking dynamics and T

E M Fallon1, D A Lauffenburger

  • 1Department of Chemical Engineering, Biotechnology Process Engineering Center, and Division of Bioengineering & Environmental Health, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

Biotechnology Progress
|October 12, 2000
PubMed

Insights

A computational model predicts that modifying interleukin-2 (IL-2) binding affinity can enhance T cell proliferation. This approach aids in designing improved cytokine therapies and bioreactors.

Area of Science:

  • Immunology and Biotechnology
  • Computational Biology
  • Cellular Dynamics

Background:

  • Multisubunit cytokine receptors, like the interleukin-2 receptor (IL-2R), regulate hematopoietic cell proliferation and differentiation.
  • Cytokine-receptor trafficking dynamics impact cellular responses via receptor downregulation and ligand depletion.
  • Ligand-receptor binding properties govern these trafficking dynamics.

Purpose of the Study:

  • To develop a computational model for IL-2 receptor (IL-2R) trafficking dynamics.
  • To predict T cell proliferation responses to IL-2 based on trafficking dynamics.
  • To identify beneficial cytokine/receptor binding properties for therapeutic applications.

Main Methods:

  • Developed a computational model with kinetic equations for IL-2 and IL-2R binding, internalization, and postendocytic sorting.
  • Incorporated experimentally derived dependence of T cell proliferation rate on these properties.
  • Simulated IL-2R trafficking dynamics under varying binding affinities.

Main Results:

  • Model predicts reduced IL-2 depletion by decreasing IL-2 binding affinity to the IL-2R betagamma subunit relative to the alpha subunit at endosomal pH.
  • Enhanced sorting of IL-2 to recycling over degradation was observed.
  • An IL-2 analogue with altered binding properties demonstrated increased potency for T cell proliferation.

Conclusions:

  • Computational modeling can predict optimal cytokine-receptor binding properties.
  • Altering IL-2 binding affinity can enhance T cell proliferation responses.
  • This approach aids in developing molecular design criteria for cytokine therapies and hematopoietic cell bioreactors.

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