A methodology of quantifying membrane permeability based on returning probability theory and molecular dynamics...

Area of Science:

• Computational Chemistry
• Physical Chemistry
• Biophysics

Background:

• Estimating substrate permeability across membranes is crucial for understanding transport phenomena.
• Molecular dynamics (MD) simulations offer a powerful tool for investigating molecular behavior.
• Existing methods may require significant computational resources for accurate permeability predictions.

Purpose of the Study:

• To develop a novel theoretical approach for calculating membrane permeability coefficients using MD simulations.
• To adapt the returning probability (RP) theory for describing permeation processes.
• To investigate the concentration dependency of permeability for different substrates.

Main Methods:

• Reformulation of returning probability (RP) theory to model membrane permeation.
• Utilizing molecular dynamics (MD) simulations to calculate thermodynamic and kinetic quantities.
• Application to ethanol and methylamine permeation at varying concentrations (infinitely dilute and 1 mol%).

Main Results:

• The proposed method accurately estimates permeability coefficients, showing good agreement with brute-force MD simulations.
• At 1 mol% concentration, ethanol exhibited a higher permeability coefficient (0.12 ± 0.01 cm s⁻¹) than methylamine (0.069 ± 0.006 cm s⁻¹).
• Ethanol's permeability shows a greater concentration dependency due to its sensitive free-energy barrier within the membrane.

Conclusions:

• The adapted RP theory provides a rigorous and efficient method for estimating membrane permeability.
• The study elucidates the distinct concentration-dependent behaviors of ethanol and methylamine permeation.
• This theoretical framework enhances the understanding of substrate transport mechanisms across biological membranes.