QBI presents a seminar with Janina Sörmann, Senior Research Associate in the Department of Drug Design and Pharmacology at the University of Copenhagen in Denmark.

Dr. Sörmann's research focuses on understanding ion channels and channelopathies through electrophysiological and biophysical methods. She is currently applying deep learning to streamline the drug discovery process for ligand gated ion channels. She studied potassium ion channels at the University of Oxford, where she linked sleep apnea to impaired gating mechanisms in a K2P channel and found a potential therapeutic in collaboration with Bayer AG. Dr. Sörmann furthermore probed and optimised nanobodies against K2P channels. Additionally, her early research involved studying microbial rhodopsins to engineer optogenetic tools. Beyond academia, she worked in the pharmaceutical industry, developing assays and contributing to the discovery of novel therapeutics.

Talk Title: Leveraging Deep Learning Tools to Design hASIC1a Modulators

Stroke is a leading cause of death and adult disability. Acid-sensing ion channels (ASICs) in the central nervous system contribute to tissue damage after ischemic stroke but are underexplored therapeutic targets due to the lack of potent, selective, and stable inhibitors. Dr. Sörmann's group designed de novo miniproteins capable of inhibiting hASIC1a by integrating deep learning tools in the drug discovery process and combining it with functional analysis in automated patch clamp experiment. These computationally designed modulators offer high specificity, efficacy, and cost-effective synthesis, broadening accessibility for stakeholders.

Hosted by Willow Coyote-Maestas