Stochastic sensing of biomolecules in a nanopore sensor array.

In this study, we demonstrate that a pattern-recognition stochastic sensor can be constructed by employing an array of protein pores modified with a variety of non-covalent bonding sites as effective sensing elements. The collective responses of each of the individual component nanopores to a compound produce diagnostic patterns characterized by event dwell time, amplitude, and voltage dependence, which can independently or collectively serve as (an) analyte signature(s). With an increase in the dimensionality of the signal, the nanopore sensor array provides enhanced resolution for the differentiation of analytes compared to a single-pore configuration. This allows identification of a target analyte from a mixture or the potential for simultaneous detection. The pattern-recognition nanopore method is envisaged for further development as a miniaturized and automated sensing technique, which could find potential use as a laboratory or clinical tool for routine sensor applications, including environmental monitoring, drug discovery, medical diagnosis, and homeland security.