Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

Area of Science:

• Computational chemistry
• Biophysics
• Soft matter physics

Background:

• Complex reaction-diffusion processes are vital in cellular networks and self-assembly.
• Existing multiscale methods combine mesoscopic Green's Function Reaction Dynamics (GFRD) with microscopic molecular dynamics (MD).
• Anisotropic interactions in biomolecular systems necessitate the inclusion of orientational dynamics.

Purpose of the Study:

• To extend the multiscale MD-GFRD approach to incorporate orientational dynamics.
• To develop a novel algorithm for simulating systems with anisotropic interactions.
• To enable large-scale simulations of complex biological systems like protein signaling networks.

Main Methods:

• Developed a novel multiscale algorithm integrating rotational Brownian dynamics with GFRD.
• Focused the algorithm on Brownian dynamics for illustration, noting its generic applicability.
• Validated the algorithm using a simple patchy particle model.

Main Results:

• Successfully extended the multiscale MD-GFRD method to include orientational dynamics.
• Demonstrated the algorithm's capability through simulations with a patchy particle model.
• Validated the algorithm's performance and accuracy.

Conclusions:

• The rotational Brownian dynamics MD-GFRD multiscale method enhances the simulation of systems with anisotropic interactions.
• This approach significantly improves the efficiency of modeling complex reaction-diffusion processes.
• The method opens new possibilities for large-scale simulations of biomolecular systems, particularly protein signaling networks.