Tobias Madl

My laboratory is interested in understanding the general mechanisms of how disordered proteins mediate signal transfer via an intricate network of protein interactions and post-translational modifications. We work at the interface of structural biology, biophysics, cell biology and medicine to study the molecular mechanisms of key regulatory processes involved in signaling. Nuclear magnetic resonance (NMR) and biophysical methods are the primary tools employed in our laboratory that allow us to study the structural and dynamical properties of signaling proteins and their interactions under native-like solution conditions. Our efforts focus primarily on the highly conserved Wnt signaling pathway, intersected pathways, and the nuclear import of RNA-binding proteins. Distortions in these pathways lead to a plethora of diseases, including cancers and neurodegenerative disorders, and are linked to ageing. We aim to reveal the molecular mechanisms underlying interactions of disordered proteins to provide insight into the intricate link between their function, regulation and human diseases. We use metabolic phenotyping to obtain systemic insight into the molecular outcome of distortions in signaling pathways in cell-based assays, in vivo model systems and patients. This allows us to bridge the gap between atom and patient and vice versa and to obtain new insights into disease mechanisms and diagnosis. To be able to study large and dynamic biomolecular complexes involved in signal transduction, the Madl group employs and develops an integrated structure determination protocol in which they combine NMR spectroscopy, SAXS/SANS, complementary techniques (i.e. MS, EM, FRET) and modeling strategies which are especially suited to study the structure of large and dynamic biomolecules and biomolecular complexes. Next to molecular dynamics programs widely used in the NMR community, their computational focus is on the integration of novel techniques in the Rosetta de novo structure prediction framework. Several approaches have been developed and applied to challenging biological systems in the last few years.