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Structure-informed theoretical modeling defines principles governing avidity in bivalent protein interactions.

Reagan Portelance1, Anqi Wu1, Alekhya Kandoor1

  • 1Department of Biomedical Engineering and the Department for Genome Sciences, University of Virginia, Charlottesville, Virginia, United States of America.

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Summary

Tandem SH2 domains mediate high-affinity protein interactions. Computational and experimental methods predict their recruitment, revealing conserved structures optimized for avidity in cell signaling.

Keywords:
BLISH2 domainsaviditybiolayer interferometrybivalentcomputational biologyphosphotyrosineprotein interactions

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Structural Biology

Background:

  • Tandem SH2 domains mediate high-affinity interactions in phosphotyrosine signaling via avidity with bisphosphorylated partners.
  • Challenges have limited the exploration of tandem SH2 domain avidity.

Purpose of the Study:

  • To predict and test tandem SH2 domain recruitment using computational modeling and experimental approaches.
  • To understand the evolutionary optimization of tandem SH2 domain spacing for avidity.

Main Methods:

  • Utilized advances in computational modeling and experimental techniques.
  • Performed structure-based analysis of SH2 domain spacing.
  • Interrogated conserved domain spacing experimentally.

Main Results:

  • Theoretical models indicate maximum avidity with closely spaced or flexibly linked phosphotyrosine sites and moderate monovalent affinities.
  • Structure-based analysis revealed conserved 3D spacing of SH2 domains across families, suggesting evolutionary optimization.
  • Combined structural and experimental data accurately predicted high-affinity interactions of tandem SH2 domain recruitment to EGFR C-terminal tail.

Conclusions:

  • The developed approaches accurately predict tandem SH2 domain recruitment and high-affinity interactions.
  • Conserved SH2 domain spacing suggests evolutionary optimization for avidity.
  • These methods provide a foundation for predicting multivalent protein interactions in cell signaling.