Monte Rosa Therapeutics raises $100m in follow-on funding

Published date:
May 21 2024

Monte Rosa Therapeutics (GLUE) has raised $100m in follow-on investment, co-led by new biotech VC Dimension. The company is poised to realise near, middle, and long-term clinical catalysts in large, well-scoped therapeutic areas like oncology, inflammation, and immunology. Powering this translation is a discovery engine on the precipice of inflection across fidelity and scale – largely driven by advances in geometric deep learning, high-throughput experimental biology, and next-generation proteomics.

When new ways to treat disease begin to find clinical success, it’s a call for celebration. Optimism is inevitable when approaches like gene editing and antibody-drug conjugates (ADCs) provide new hope for those afflicted by illness. Following decades of research, targeted protein degraders (TPDs) are finally hitting their stride. 

Many small molecule drugs bind to and temporarily inhibit proteins involved in disease. TPDs completely destroy target proteins by routing them to the proteasome – the body’s protein disposal system. This differentiated mechanism means TPDs can be effective at smaller, less frequent doses and attack proteins elusive to standard inhibitors. Excitingly, these concepts are increasingly bearing out in human trials

Proteolysis targeting chimeras (PROTACs) and molecular glue degraders (MGDs) are the two dominant TPD formats. Dimension's research suggests MGDs can more readily benefit from existing medicinal chemistry optimisation techniques, are simpler to scalably manufacture, have superior drug-like properties, and extend to targets historically inaccessible to PROTACs such as proteins lacking bindable surface pockets. 

Unfortunately, MGDs have proven difficult to develop. Most have been discovered by accident. Compared to PROTACs, MGDs sometimes struggle with selectivity, meaning they can degrade proteins other than their intended target. 

Founded in 2018, Monte Rosa has evolved a compelling MGD discovery engine – one that combines principles of rational design with fit-for-purpose technology to (a) overcome selectivity obstacles, (b) advance beyond the known alphabet of intra-target degradation motifs (i.e., degrons) to “non-canonical” degrons, and (c) expand the repertoire of usable E3 ligases – key proteins involved in a cell’s degradation machinery. Critically, this engine has quickly advanced multiple therapeutic assets in a capital efficient manner.  

The core of Monte Rosa’s discovery process revolves around protein surfaces. Like a surveyor maps the contours of the Earth, Monte Rosa’s computational platform scans the exteriors of target proteins and E3 ligases. As pioneers in applied geometric deep learning, Monte Rosa encodes the 3D geometry, flexibility, and physicochemical properties of each patch of a protein’s surface. 

By focusing on surfaces, Monte Rosa can find non-obvious complementarity between the degradation machinery and degrons on target proteins. The company combines surface-aware MGD generation algorithms and high-throughput screening (HTS) capabilities to discover molecules that can stabilise complementary protein-ligase interactions. 

Monte Rosa has advanced an initial wave of assets that should step-wise validate the platform’s ability to rationally design selective MGDs in the near term, extend to non-canonical degrons and novel ligases in the medium term, and explore adjacent modalities similarly undergoing translational success such as degrader-antibody conjugates (DACs) in the long term.