About the team

Thematically, we are working at the interface of chemical biology, proteostasis, and gene control. We aim to innovate novel chemical strategies that allow us to better understand fundamental principles of transcription regulation and the ubiquitin-proteasome system. In particular, we are fascinated by the concept of chemical neomorphs: small molecules that can endow proteins with novel functions to ultimately rewire cellular circuits. Our current focus is on molecules that act as molecular glue degraders, inducing proximity between a target protein of interest and an E3 ubiquitin ligase to prompt ubiquitination and proteasomal degradation of the target protein. However, we are keen to expand this concept towards other cellular functions, particularly focusing on small molecules that can functionally hijack transcriptional circuits or co-opt the DNA damage response pathway.

Our research strategy is inspired and driven by high-throughput and unbiased technologies such as quantitative proteomics, (nascent) transcriptomics and particularly functional genomics. We are further excited to augment the interpretability and predictability of these large-scale datasets via artificial intelligence and machine learning methods. Connecting the derived insights with synthetic chemistry enables us to understand the mechanism of action of proteins, protein complexes or small molecules both on a holistic but also mechanistic level. Our long-term vision is that these fundamental and mechanistically grounded insights will lay the foundation for downstream therapeutic innovation and the development of novel medicines.

Research focus

Chemical reprograming of biological circuits for cancer therapy, innovation of novel therapeutic modalities, autonomous ligand discovery, AI-enabled functional genomics

Project description

Several project directions are available within the wider area of expertise of the lab, and interest and background of a candidate will be taken into consideration when matching them with the best project.

Currently, a big emphasis of the lab is to functionalize AI-designed protein binders as perturbation agent in functional genomics experiments. This will allow us to identify novel targets for cancer therapeutics (including immune-oncology) that reach beyond the well-established principle of loss-of-function.

Candidate’s Profile and Skills

We are open to candidates with diverse backgrounds in biology/biochemistry, chemistry, bioinformatics as well as machine learning.