A computational kinetic model of diffusion for molecular systems.

Area of Science:

• Biophysics
• Computational Biology
• Molecular Dynamics

Background:

• Biomolecular transport involves complex intra- and extra-protein steps.
• Extra-protein steps, crucial for solute approach and admittance, occur at the 10-100 nm scale.
• The cellular environment, including protein geometry and electrostatics, significantly influences these steps.

Purpose of the Study:

• To develop a particle-based kinetic model for simulating solute diffusion in complex cellular environments.
• To accurately capture solute energetics and mobility at a relevant resolution.
• To extend the timescale of transport process simulations beyond the limits of molecular dynamics.

Main Methods:

• Utilized a Markov State Model framework for a particle-based kinetic diffusion model.
• Generated input data, including diffusion coefficients and potential of mean force maps, from molecular dynamics simulations.
• Represented systems using discrete states defined by Voronoi grid cells and a density function.

Main Results:

• Validated the diffusion model and Brownian motion algorithm across various parameter values.
• Demonstrated the model's capability to describe transport processes beyond microsecond durations.
• Applied the method to simulate ion diffusion around and through the ecMscS channel.

Conclusions:

• The proposed model provides a viable approach for simulating biomolecular transport at biologically relevant timescales.
• This method enhances the understanding of solute diffusion in intricate protein-associated environments.
• The model is applicable to various biological systems, including ion channels like ecMscS.