Simulating Nanopore Sensor Dynamics Over Long Times Scales

Abstract

Nanopores of both synthetic and biological origin hold broad potential for single-molecule sensing applications. We present a Brownian kinetic model that combines: (1) analyte diffusion kinetics; (2) electrophoretic drift; (3) and convective electroosmotic flow. This approach provides insight into analyte behavior over relatively long time scales (microsecond to millisecond).The simulation utilizes a distributed computer network to model these three kinetic factors in beta-cyclodextrin (βCD)-modified αHL. The structure of this modified channel is simplified to a three-dimensional reflecting solid, whereby diffusing analytes are individually tracked as they migrate above the pore and through the lumen. Based on measurements of diffusion constants, electrophoretic mobility, and electroosmotic flow rates through the nanopore, the simulator follows trajectories of particles located at different positions relative to the mouth of the pore. We present data collected over a range of applied transmembrane potentials and estimate the probability of capturing analytes as a function of distance relative to the pore. The timing of analyte arrival at the βCD detection site is also described. The results highlight the dominance of thermal diffusion and illustrate the relative contribution of each of the three kinetic factors in the production of detection events.View Large Image | View Hi-Res Image | Download PowerPoint Slide