RTG Speaker Seminar: Prof. Dr. Herre Jelger Risselada - Dortmund University

In this presentation, I will delve into how biomolecules can detect alterations in liquid interface properties, including membrane curvature, lipid membrane composition, and liquid order. I will illustrate how the integration of computational interface physics using coarse-grained molecular simulations, evolutionary algorithms, and machine learning techniques is now rapidly advancing our ability in deciphering amino acids sequences that can sense distinct membrane interface properties such as curvature, elevated levels of cholesterol, and liquid order (often being associated with the concept of lipid rafts).

I will demonstrate how these recent advancements already resulted in the discovery of highly effective antiviral peptide sequences. These peptides are designed to specifically target the membrane interface of small enveloped viruses, leveraging their unique structural characteristics. Furthermore, I will demonstrate how the potential presence of membrane-binding residues/regions within your studied protein can be quantitatively identified via our publicly accessible server ( https://pmipred.fkt.physik.tu-dortmund.de), all within a matter of seconds. Within this context, I will briefly illustrate how this predictive capability is now exploited to enhance the transport of medications across the blood-brain barrier.
Finally, our latest research has uncovered the first selective liquid-ordered phase binding sequence. These sequences are hypothesized to be pivotal in the recognition of cholesterol-enriched domains potentially present in cellular membranes, a concept that has long been a subject of speculation.