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Continuous-time multifarious systems. I. Equilibrium multifarious self-assembly.

Jakob Metson1, Saeed Osat1, Ramin Golestanian1,2

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|September 23, 2025
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Summary
This summary is machine-generated.

Continuous-time simulations reveal a smaller parameter space for reliable multifarious self-assembly compared to discrete-time methods. This approach better identifies structural instabilities in large systems, enhancing understanding of component usage in biological self-assembly.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Systems Chemistry

Background:

  • Multifarious assembly models explore efficient component usage in biological self-assembly.
  • These models involve high-dimensional parameter spaces, with reliable self-assembly confined to specific regions.

Purpose of the Study:

  • To investigate multifarious self-assembly using continuous-time Gillespie simulations.
  • To compare the reliability of self-assembly prediction between continuous-time and discrete-time simulation methods.
  • To analyze the stability of assembled structures against chimera formation.

Main Methods:

  • Continuous-time Gillespie simulation.
  • Discrete-time Monte Carlo simulation.
  • Analysis of structural stability and chimera formation.
  • Development of physical arguments for parameter space boundary prediction.

Main Results:

  • Continuous-time simulations identified a smaller parameter space for reliable multifarious self-assembly than discrete-time simulations.
  • Continuous-time simulations effectively expose structural instabilities in large systems.
  • Discrete-time simulations are slower in revealing these instabilities, especially for larger system sizes.
  • Good agreement was found between continuous- and discrete-time simulations in the remaining state space.

Conclusions:

  • Continuous-time simulations offer a more sensitive method for studying multifarious self-assembly and its stability.
  • The findings enhance the understanding of parameter space boundaries and component usage in self-assembly systems.
  • This work provides a more robust framework for predicting reliable self-assembly.