Versant's Monte Rosa reels in $96M to bankroll 'molecular glue' treatments for cancer, other diseases

Creating drugs that harness the body’s protein-degrading processes is not a new idea; companies like Arvinas are using this approach to destroy disease-causing proteins rather than simply blocking their function. But Monte Rosa Therapeutics is taking a different tack with molecular glues, and it’s just raised $96 million to do so.

Other protein degradation players are working on the hypothesis that destroying disease-causing proteins is a better approach than inhibiting them. Arvinas, for example, is developing drugs called proteolysis targeting chimeras, or PROTACs, to degrade the androgen and estrogen receptors, which are major drivers of prostate cancer and breast cancer, respectively. And Kymera Therapeutics is working on degraders of scaffolding kinase IRAK4 and transcription factor STAT3, both of which play a role in cancer.

But what all those targets have in common is they can be inhibited by traditional drugs.

Rather than “redrugging the druggable,” as CEO Markus Warmuth, M.D., puts it, Monte Rosa wants to go after undruggable targets, meaning those that have been inaccessible because drug developers lacked the technology to tackle them.

“PROTACs cannot go after the undruggable space because whatever PROTAC you make needs an active site on the target you’re intending to degrade,” Warmuth said. “And that is different for molecular glues.”

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As their name suggests, molecular glues stick proteins to each other. Unlike PROTACs, which contain one region to bind to a target protein and another that binds to enzymes that play a role in protein degradation, molecular glues change the surface of those enzymes to stick to target proteins.

“They work by allosterically changing the receptor surface of E3 ligases to attract a protein target,” Warmuth said, referring to enzymes that tag proteins with ubiquitin for degradation by a protein complex called a proteasome. "We have a singular focus on finding these molecules that reshape the surface of an E3 ligase and thereby attract otherwise undruggable targets.”

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The best-known molecular glue meds are thalidomide and its successor molecule lenalidomide—aka Bristol Myers Squibb’s blood cancer drug Revlimid—which both reshape an E3 ligase receptor called cereblon, Warmuth said.

“We felt inspired by that story, but the discovery of these molecules was somewhat serendipitous,” he added. Monte Rosa will use its drug discovery platform to find molecular glues and their potential targets in a systematic way.

The new funding, drawn from a laundry list of backers including Aisling Capital, New Enterprise Associates, GV and founding investor Versant Ventures, will bankroll the development of that platform and its expansion into diseases beyond cancer as well as push programs into the clinic.

“We are now very close to having a clinical candidate selected, so we are most likely entering IND-enabling studies by the end of the year. We’re planning to enter clinical trials by the end of next year,” Warmuth said.

Monte Rosa isn’t divulging the target of that lead program just yet, but the company did disclose a breast cancer program as a possible lead when it launched in May of this year.

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“I can say the molecule goes after a target that is synthetic lethal for a very well-validated oncogenic transcription factor,” Warmuth said, synthetic lethality being the interaction between two genes that causes cell death when both are inactivated. In cancer cells, one of the genes is inactivated by a mutation; the other will be switched off by a drug.

Beyond its lead program, the sky’s the limit for this technology.

“One space this approach could work well is transcription factors as targets, so you could argue almost any disease that is driven by transcription factors will be interesting for us: immunology, neuroscience, but also rare diseases are high on our list,” Warmuth said, adding that transcription factors aren’t the only target Monte Rosa could go after.

“We have developed an algorithm and applied machine learning to predict targets, and we see everything from cell surface receptors to signaling molecules and enzymes all the way down to transcription factors or proteins complexed with those transcription factors,” he said.