Accounting for diffusion in agent based models of reaction-diffusion systems with application to cytoskeletal...

Area of Science:

• Computational Biology
• Biophysics
• Molecular Modeling

Background:

• Diffusion is fundamental to biochemical reactions within cellular compartments.
• Molecular crowding significantly impacts particle interactions and diffusion dynamics.
• Accurate modeling of diffusion is crucial for understanding cellular processes.

Purpose of the Study:

• To develop and validate a computational agent-based model for simulating diffusion in 3D solutions.
• To investigate the impact of molecular crowding on effective diffusion.
• To explore algorithms for multi-particle diffusion and the influence of cellular geometry on diffusion directionality.

Main Methods:

• Agent-based modeling (ABM) to simulate particles with varying properties (size, diffusion coefficients, affinity) and environmental factors (viscosity, geometry).
• Validation using Langevin dynamics simulations and comparison with experimental data.
• Development and testing of algorithms for handling multiple, size-varying particles within discrete cells.

Main Results:

• The ABM successfully mimics natural diffusion behavior and accurately models the effects of molecular crowding.
• Simulations show good agreement with Langevin dynamics and experimental findings.
• A refined algorithm was proposed to accurately model diffusion of multiple particles of varying sizes.
• Cellular structural geometry, such as actin filaments in filopodia and lamellipodia, was shown to direct diffusion.

Conclusions:

• The developed agent-based model provides a realistic framework for studying molecular diffusion in complex biological systems.
• The model accurately captures the influence of molecular crowding and cellular architecture on diffusion.
• Findings highlight the importance of considering discretization errors and structural geometry in diffusion modeling.