PPDiffuse: A Quantitative Prediction Tool for Diffusion of Charged Polymers in a Nanopore

Nanopore-based sensing of charged biopolymers is a powerful single-molecule method. In aconventional nanopore experiment, a single biological (proteinaceous) or solid-state nanopore perforates a thin membrane that is wetted by, and electrically isolates, two opposing reservoirs of electrolyte solution. A potential is applied across the membrane via external electronics coupled to the electrolyte reservoirs with electrochemical electrodes, actuating the system. The electric field set up by the applied potential in the nanopore and its immediate environment plays two roles: supporting an ionic current through the nanopore, which reports on the properties of the pore and its contents; and acting on analyte molecules to attract them to, and drive them into, the nanopore. The presence of a large biopolymer in the pore modulates the ionic current ( ). The duration of the ionic current modulation corresponds to the length of time the polymer spends in the pore from capture to its ultimate escape, either by retraction to the reservoir from which it was captured, or by translocation to the opposite reservoir . The probabilities of retraction or translocation, or splitting probabilities, and the corresponding distributions of escape times ( esc ), are particularly sensitive to the size and charge of the analyte molecule and have been the focus of much theoretical, computational, and experimental effort. An underlying physical framework in which the distribution of escape times is modeled as a first-passage time from a one-dimensional potential is quantitatively predictive for a wide range of experiments. The complexity of this potential for the general case, however, requires calculations to guide experimental design that can be tedious to implement. PPDiffuse is intended to remove this burden from the nanopore research community and enable convenient, rational design of nanopore experiments with complex substrates such as polypeptides.