Rapid and Accurate Determination of Nanopore Ionic Current Using a Steric Exclusion Model

Area of Science:

• Biophysics
• Computational Biology
• Nanotechnology

Background:

• Nanopore sensing is crucial for biomolecule detection.
• Current methods for nanopore design rely on intuition.
• A computational method is needed to link nanopore/analyte geometry to current blockades.

Purpose of the Study:

• To develop a computationally efficient and accurate method for predicting nanopore conductance.
• To establish a link between atomic-scale pore and analyte geometry and ionic current blockades.

Main Methods:

• Developed the Steric Exclusion Model (SEM) for nanopore conductance.
• Combined finite element solver with nanopore conductance mapping.
• Validated SEM against all-atom molecular dynamics simulations.

Main Results:

• SEM is orders of magnitude more efficient than all-atom MD.
• SEM accurately predicts ionic current blockades for proteins, DNA, and amino acids.
• SEM accounts for atomic structure of nanopores and analytes.

Conclusions:

• SEM offers a robust, inexpensive, and accurate approach for nanopore sensing.
• SEM can guide nanopore design and analyte characterization.
• SEM is expected to be integral to future nanopore sensing development.