Sampling efficiency of the counting method for permeability calculations estimated with the inhomogeneous...

Area of Science:

• Molecular dynamics simulations
• Membrane transport phenomena
• Computational biophysics

Background:

• Permeability is crucial for chemical separation and biological transport.
• The counting method uses membrane crossings in molecular dynamics (MD) simulations to predict permeability.
• Understanding the limitations of this method is essential for accurate predictions.

Purpose of the Study:

• Investigate conditions leading to insufficient statistics in the counting method for permeability prediction.
• Derive an equation to understand the correlation between flux and permeant solubility.
• Assess the impact of permeant trapping and membrane properties on simulation accuracy.

Main Methods:

• Derivation of a compartmental model equation based on the inhomogeneous solubility-diffusion (Smoluchowski) model.
• Running coarse-grained molecular dynamics (MD) simulations for 16 dipalmitoylphosphatidylcholine bilayer membrane systems.
• Analysis of permeant types and their solubility variations within the simulation box.

Main Results:

• Membrane crossings are rare events not only due to high energy barriers but also deep free energy wells (permeant traps).
• Permeant traps lead to high permeability but can cause poor statistics for the counting method.
• The composition rule for permeability also applies to fluxes; membrane thickness introduces uncertainty in calculations for highly permeable membranes.

Conclusions:

• High membrane permeability does not guarantee sufficient sampling efficiency for the counting method.
• Caution is advised for permeants with significant solubility variations across the simulation box.
• In drug design, high membrane permeability might indicate a risk of permeant trapping, potentially reducing drug efficacy.