Experiments 2024
Janina Sormann
Leveraging deep learning to develop therapeutics for K2P channel-related neural disorders
Postdoc
University of Copenhagen
Two-pore-domain K+ (K2P) channels regulate membrane potential and neuronal excitability. The K2P family includes 15 subtypes, each with distinct functions. Malfunction in these channels is associated with disorders such as depression, chronic pain, epilepsy, sleep apnea, and migraines, making them relevant therapeutic targets. However, their structural similarity poses challenges in developing treatments that selectively target specific K2P subtypes. By leveraging recent advancements in deep learning for protein biology, I aim to design lead compounds capable of modulating these channels in a subtype-selective way. Combined with functional analysis, this work will deliver novel drug candidates and precision tools for neuroscience.