Investigating the effect of different transducer stiffness values on the contactin complex detachment by steered

Parnian Kianfar1, Nabiollah Abolfathi1, Navid Zarif Karimi2

  • 1Department of Biomedical Engineering, Amirkabir University of Technology, Tehran 158754413, Iran.

Insights

This study explored how Contactin4 (CNTN4) and PTPRG proteins bind. Increased pulling speed and stiffness strengthened their adhesion, impacting neuronal network dynamics.

Area of Science:

  • Biophysics
  • Neuroscience
  • Computational Biology

Background:

  • Contactin4 (CNTN4) is an Immunoglobulin Super Family (Ig-SF) cell adhesion molecule vital for neuronal network development, maintenance, and plasticity.
  • Understanding the mechanical properties of CNTN4 interactions is crucial for comprehending neural development and function.

Purpose of the Study:

  • To investigate the adhesion and unbinding mechanisms of the Contactin4-Protein Tyrosine Phosphatase gamma (PTPRG) complex.
  • To determine how external forces, specifically pulling speed and transducer stiffness, influence the complex's rupture force and dissociation rates.

Main Methods:

  • Utilized Steered Molecular Dynamics (SMD) simulations to apply uniaxial force and induce unbinding of the CNTN4-PTPRG complex.
  • Performed simulations varying transducer stiffness (three values) and pulling speeds (five values) to probe force-induced detachment.
  • Calculated dissociation rates using Bell's theory based on derived rupture forces and loading rates.

Main Results:

  • The unbinding force of the CNTN4-PTPRG complex was found to be dependent on both pulling speed and spring stiffness.
  • Increasing stiffness and pulling speed led to a significant increase in the rupture force required for complex dissociation.
  • Dissociation rates were successfully calculated, correlating with the observed rupture forces and loading rates.

Conclusions:

  • Mechanical forces play a significant role in the adhesion dynamics of the Contactin4-PTPRG complex.
  • The findings provide insights into the force-dependent interactions of cell adhesion molecules relevant to neuronal plasticity.
  • This study establishes a computational framework for analyzing the mechanical stability of protein complexes in biological systems.

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