Erik Lindahl

Erik Lindahl

Professor of biophysics

Wallenberg Scholar

Institution:
Stockholm University 

Research field:
Structure and function of ligand-gated ion channels, in particular in the human nervous system

Examine structure and function of membrane proteins

As a Wallenberg Scholar, Erik Lindahl seeks to answer questions concerning ligand-gated ion channels in our nervous system, for example why they are so sensitive to their surroundings, why they respond differently to drugs and whether it is possible to find ways to selectively influence specific receptors.

Ligand-gated ion channels control molecular signaling between nerve cells. They are strongly influenced by molecules such as alcohol and cholesterol and they are targets for drugs such as benzodiazepines, anesthetics and the only molecule approved to treat postpartum depression.

Erik Lindahl and his research team have developed some of the world's most widely used computer programs in structural biology, which they use to understand the extreme diversity of ligand-gated receptors in the nervous system and to determine the functions of less studied variants.

Studies of the neurotransmitter GABA

GABA is one of the most important neurotransmitter molecules in vertebrates. The research team will use cryo-electron microscopy to determine structures of the previously less studied GABA-rho receptor and other variants that occur in the retina and uterine tissue. They want to understand how five different subunits assemble into receptors whose properties depend on which genes the subunits correspond to, and how the assembly is controlled. Among other things, they will use computer simulations to model how the membrane proteins move between different states, to understand why they have such different sensitivities both to GABA and drugs, but also to understand how the lipids in the surrounding membrane strongly influence the function either positively or negatively.

They further intend to develop methods to combine simulations with cryo-electron microscopy to predict how membrane proteins move, specifically by using machine learning to directly predict movement from microscopy images. To understand structure and dynamics on cellular scale, they will develop methods to combine tomography with modeling.

The researchers expect to be able to explain e.g. why the function of receptors in the nervous system depends so critically on the membrane environment, why the receptors often appear in clusters, and develop new tools for structure on mesoscopic scales.