Unidirectional single-file transport of full-length proteins through a nanopore.

The electrical current blockade of a peptide or protein threading through a nanopore can be used as a fingerprint of the molecule in biosensor applications. However, threading of full-length proteins has only been achieved using enzymatic unfolding and translocation. Here we describe an enzyme-free approach for unidirectional, slow transport of full-length proteins through nanopores.

Mapping the conformational energy landscape of Abl kinase using ClyA nanopore tweezers.

Protein kinases play central roles in cellular regulation by catalyzing the phosphorylation of target proteins. Kinases have inherent structural flexibility allowing them to switch between active and inactive states. Quantitative characterization of kinase conformational dynamics is challenging.

Modifying the pH sensitivity of OmpG nanopore for improved detection at acidic pH.

The outer membrane protein G (OmpG) nanopore is a monomeric β-barrel channel consisting of seven flexible extracellular loops. Its most flexible loop, loop 6, can be used to host high-affinity binding ligands for the capture of protein analytes, which induces characteristic current patterns for protein identification. At acidic pH, the ability of OmpG to detect protein analytes is hampered by its tendency toward the closed state, which renders the nanopore unable to reveal current signal changes induced by bound analytes.

A Selective Activity-Based Approach for Analysis of Enzymes with an OmpG Nanopore.

Many enzymatic activity assays are based on either (1) identifying and quantifying the enzyme with methods such as western blot or enzyme-linked substrate assay (ELISA) or (2) quantifying the enzymatic reaction by monitoring the changing levels of either product or substrate. We have generated an outer membrane protein G (OmpG)-based nanopore approach to distinguish enzyme identity as well as analyze the enzyme's catalytic activity. Here, we engineered an OmpG nanopore with a peptide cut site inserted into one of its loops to detect proteolytic behavior.

Growing Echo-State Network With Multiple Subreservoirs.

An echo-state network (ESN) is an effective alternative to gradient methods for training recurrent neural network. However, it is difficult to determine the structure (mainly the reservoir) of the ESN to match with the given application. In this paper, a growing ESN (GESN) is proposed to design the size and topology of the reservoir automatically.