Research

Life is movement - driven by cellular processes that are controlled by molecular machines made of proteins. Our goal is to understand these processes at the atomic level by gaining time-resolved insights into the structure and dynamics of molecular machines. This not only enables new insights into the development of diseases, but also the development of targeted drugs and therapies. Furthermore, these insights contribute to protein engineering by helping to design customised proteins with specific functions.

Since an in-depth understanding of these processes requires a combination of different perspectives, we develop computer-aided strategies that combine biophysical and biochemical experimental data with modern bioinformatics algorithms. The result is a holistic picture of the structure and functional cycles of molecular machines - from atomic details at the electron level to higher-level molecular structures.

Our methodology is based on three central steps:

1. Structural modelling: experimental data is converted into static structural models using bioinformatics methods or predicted using artificial intelligence (AI).
2. Precise refinement: Active centres are analysed with a resolution of less than 1 Å, while quantum chemistry/molecular dynamics (QM/MM) simulations identify intermediate states that are difficult to access experimentally.
3. Dynamic simulations: The refined snapshots are combined to use molecular dynamics (MD) simulations to map the motions and mechanisms of molecular machines in their natural environment.

This strategy provides insights with the highest spatial and temporal resolution into the interplay between local processes such as chemical reactions at the active centres and global conformational changes that control cellular function. The insights gained provide mechanistic hypotheses and help to design targeted experiments that validate our structural and dynamic models.

• Investigation of molecular mechanisms of oncological target structures, e.g. the Ras protein, which malfunctions in around 20% of all oncological diseases, or the proteasome responsible for protein recycling, which is attacked as a drug target during chemotherapy.
• Findings on the conversion of light into chemical energy during photosynthesis in order to breed more resistant plants in the long term that bind more CO2 and thus counteract climate change.
• Investigation of RNA-protein complexes
• Development of hybrid quantum and molecular mechanical (QM/MM) methods for calculating the physical properties of proteins. These methods are used to simulate fast processes with high spatial and temporal resolution and to validate them with experimental data, e.g. from spectroscopy.
• Theoretical spectroscopy
• Light-switchable proteins