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Mobile obstacles accelerate and inhibit the bundle formation in two-patch colloidal particle.

I Malhotra1, S B Babu1

  • 1Out of Equilibrium Group, Department of Physics, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India.

The Journal of Chemical Physics
|September 1, 2019
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Summary
This summary is machine-generated.

Protein aggregation into bundles drives neurodegenerative diseases. This study models how particle interactions and mobile obstacles can control bundle formation, offering insights into disease inhibition strategies.

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Area of Science:

  • Colloidal science
  • Biophysics
  • Computational modeling

Background:

  • Protein aggregation into bundles is a key factor in neurodegenerative diseases.
  • Understanding the kinetics of self-assembly is crucial for developing therapeutic strategies.

Purpose of the Study:

  • To investigate the self-assembly of two-patch colloidal particles into chains and bundles.
  • To analyze methods for inhibiting or accelerating bundle formation using various obstacle types.
  • To model the role of mobile obstacles in controlling protein aggregation kinetics.

Main Methods:

  • Patchy Brownian cluster dynamics simulations were employed.
  • Kinetics of chain, bundle, and network formation were studied.
  • The influence of inert immobile, mobile aggregating, and mobile repelling obstacles was analyzed.

Main Results:

  • Particle self-assembly transitions from chains to bundles are tunable via patch size and solvent conditions.
  • Inert immobile obstacles slow down bundle formation kinetics.
  • Mobile obstacles with specific attractive/repulsive interactions can inhibit or slightly accelerate bundle formation.

Conclusions:

  • The study provides a model for controlling protein aggregation using mobile obstacles.
  • This work offers potential strategies for inhibiting pathological protein assembly, drawing parallels to peptide P4's effect on insulin fibers.
  • The findings contribute to the understanding of self-assembly processes relevant to disease mechanisms.