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Multiscale Simulations of Membrane Adhesion Mediated by CD47-SIRPα Complexes.

Ruihan Hou1,2, Shuanglong Ren1, Rong Wang2

  • 1Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China.

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This study introduces a multiscale modeling approach to simulate cell membrane adhesion, focusing on CD47-SIRPα binding. The method accurately predicts binding dynamics and protein behavior, aiding future research in cellular processes.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Cellular Biophysics

Background:

  • Cell adhesion is crucial for biological functions like tissue formation and immune responses.
  • Cell adhesion involves complex interactions across multiple length scales, from nanometers to micrometers.
  • Accurate computer simulations of cell adhesion require multiscale modeling to capture essential physical processes.

Purpose of the Study:

  • To develop and apply a multiscale modeling approach for studying cell membrane adhesion.
  • To investigate the CD47-SIRPα binding process, which is immunologically significant.
  • To explore both equilibrium and dynamic properties of adhering membranes across relevant length and time scales.

Main Methods:

  • Synergistic use of coarse-grained molecular dynamics (MD) simulations.
  • Mesoscale kinetic Monte Carlo (kMC) simulations.
  • Integration of MD and kMC to cover length scales from 1 nm to 1 μm and time scales from 0.1 ns to 20 s.

Main Results:

  • The multiscale simulations successfully reproduced existing experimental data on CD47-SIRPα mediated membrane adhesion.
  • Quantitative predictions were made regarding binding-induced conformational changes in SIRPα.
  • The study revealed membrane-mediated cooperativity and fluctuation-induced interactions in CD47-SIRPα complexes.

Conclusions:

  • The developed multiscale approach provides a powerful tool for studying cell membrane adhesion.
  • The findings offer valuable insights into the biophysics of CD47-SIRPα interactions.
  • This methodology is adaptable for various membrane proteins and can generate data for experimental validation.