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

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.