Energy landscapes and time resolved EM

In contrast to the other methods of structural biology cryo EM can easily distinguish the signal coming from individual molecules and thus it has the potential that each of these particles can get assigned its constitutional and conformational state. This allows EM to infer thermodynamic properties such as free energies for the molecule directly by counting. Thus, cryo EM can serve as powerful biophysical tool that can outcompete most other tools in terms of achievable detail. We are developing schemes and software tools to facilitate this analysis. However, to gain a full understanding of a molecular machine, not only thermodynamic aspects are important, but also kinetics needs to be considered. While it is not possible to follow a single molecule in time with cryo EM it is possible to make time series experiments of molecular ensembles. To achieve this, we are building new devices for time resolved sample preparation of cryo EM grids.

Molecular motors

Almost all cellular functions are driven by molecular machines. In contrast to man-made machines these machines are mostly fueled by the random thermal noise power of the surrounding medium. Thus, the design of molecular machines must be fundamentally different to the directly fueled macroscopic machines. It is our aim to elucidate the architectural principles that allow to make use of this unusual energy source. As examples we are working on AAA-Motors such as the proteasome and motors used for genome folding such as cohesin.

The functional mechanisms and regulation of the proteasome

Cell division and differentiation depend on the proteasomal degradation of regulating proteins like securin or myc. However, how does the proteasome recognizes and distinguishes substrates is still largely unknown. Prerequisite for degradation of a target is its posttranslational modification with a ubiquitin chain. However, ubiquitin is a versatile signal. Summarized as the ubiquitin code, thousands of diverse polyubiquitin chain topologies can be formed with different lengths and linkages. However, how the proteasome selectively distinguishes between these topologies is unclear, as the early substrate-binding and initiation steps have previously been invisible to conventional approaches. This is due to the efficient rate of catalysis by the proteasome and additional editing of ubiquitin chains by proteasome associated factors. To elucidate these mechanisms the Haselbach lab is employing structural and biophysical techniques. On a broader perspective the Haselbach lab is interested in the proteasome’s regulation and adaptation in stress and disease states and is looking into different proteasomal states under those conditions.