Access resistance in protein nanopores. A structure-based computational approach

Area of Science:

• Biophysics
• Computational Biology
• Nanotechnology

Background:

• Interfacial effects significantly influence ion transport in biological nanopores.
• Access resistance (AR) quantifies ion diffusion limitations from bulk solution into nanopores.
• Existing analytical AR estimates rely on simplified, idealized nanopore models.

Purpose of the Study:

• To accurately calculate AR in protein channels using their atomic structures.
• To investigate the impact of charged residues, pore geometry, and concentration gradients on AR.
• To compare numerical AR calculations with experimental data and assess analytical model accuracy.

Main Methods:

• Utilized atomic structures of five protein channels.
• Employed a mean-field approach solving 3D Poisson and Nernst-Planck equations.
• Accounted for protein ionization, pore mouth geometry, and ion concentration gradients.

Main Results:

• Numerical AR calculations provide a more accurate representation than analytical predictions at physiological concentrations.
• Analytical models tend to overestimate AR for biological channels.
• Investigated AR dependence on aperture size in single- and multi-pore channels, noting AR enhancement in three-pore systems.

Conclusions:

• Detailed atomic and geometric features of protein channels significantly affect access resistance.
• Mean-field calculations offer a more precise method for determining AR compared to simplified analytical models.
• Understanding AR is critical for accurate modeling of ion transport in biological systems.