Nanopore Sequencing

Molecular dynamics and multiscale simulations of peptide-pore interactions are combined with machine learning methods for analysis.

Biological macromolecules fulfil vital tasks in the human body. As energy suppliers, metabolic actors, biorobots or signalling messengers between the organs and for many other metabolic processes, they are essential. This makes it all the more important to research their effects and structures in order to better understand diseases, for example, and to optimise the precise mode of action and development of drugs.

In the last decade, researchers have succeeded in developing an efficient and cost-effective method for sequencing the building blocks of DNA and RNA with single-molecular resolution and maximum accuracy. Building on this milestone, the nanodiag BW future cluster aims to extend this method of macromolecule sequencing to proteins and peptides.

In this technique, the analyte is located in a salt solution, which is separated by an impermeable lipid membrane layer. This membrane also has a nanopore that connects the two separate halves and thus represents the only means of transporting atoms, ions and molecules to the other side. An externally applied electrical voltage now leads to electrophoretic transport of ions and analyte. The presence of the analyte in the nanopore ultimately results in a temporary reduction of the empty current, i.e. the ion flow in the absence of any molecules to be analysed, due to various atomistic interactions with all possible participants.

Translocation of peptides through an aerolysin nanopore
Translocation of peptides through an aerolysin nanopore

Application of ML methods

Information on the duration d strength of this so-called blockade current is used to draw conclusions about the sequencing of the protein or peptide to be analysed using state-of-the-art machine learning algorithms. This involves experimentally analysing specific sequencing data in order to identify characteristics that can be traced back to different analytes. As part of the nanodiag BW cluster, our goal is to create software that loads the training data, carefully analyses it and extracts salient features to enable reproducible and transparent data evaluation.

All-atom and multiscale simulations

In order to understand the effects of analyte transport on the ionic current at the atomic level, we carry out molecular dynamic and multiscale simulations of peptide-pore interactions. The knowledge gained will be used to optimise the pore proteins, which will ultimately enable higher quality measurement results.

Black Forest Nanopore Meeting

During the Black Forest Nanopore Meeting, we present a poster titled "Using Molecular Dynamics Simulation as a Microscope of the Peptide's Translocation Process through an Aerolysin Nanopore", where we show the latest results of the SRASKYRRRR peptide translocation through a wild-type aerolysin pore. An example of such a translocation is shown in the video below, which can be downloaded and viewed on your smartphone and other devices.

Translocation Visualization



If you have any questions regarding molecular dynamics simulations, please contact Michel Mom. Our contact person for questions about machine learning is Julian Hoßbach. The contact details can be found below.


This image shows Michel Mom

Michel Mom


PhD Student

This image shows Julian Hoßbach

Julian Hoßbach


Master Student

To the top of the page