How a Google DeepMind Spin-off Hunts Hidden Drug Targets
Isomorphic Labs, the Google DeepMind spinout behind AlphaFold, has built an AI system called the Isomorphic Drug Design Engine (IsoDDE) that hunts for hidden binding sites on proteins where new medicines might attach. The company raised $2.1 billion in funding, one of the largest biotech rounds ever, and signed drug-discovery deals with Novartis and Eli Lilly. Its engine predicts not only where a drug molecule binds to a protein but how tightly it binds, including pockets that stay invisible until the right molecule arrives.
Key Takeaways
- For more than a decade, artificial intelligence has been touted as a way to dramatically accelerate drug discovery .
Yet despite billions of dollars in investment, relatively few AI-designed medicines have made it to patients.
- Going Beyond AlphaFold AlphaFold2 and AlphaFold3 were massive leaps forward for computational biology.
Why weren't those models sufficient for actually designing drugs?
- That said, in the years since the AF3 release, multiple groups have evaluated it along the axis of pocket novelty.
And you could see that as the pocket distance grows away from the training set, the model performance decreases.
- You don't just need to predict where the ligand binds with the protein, but also potentially how it binds, how tightly it binds, and a plethora of other properties about the ligand and how the ligand interacts with the rest of the proteins in the body.
IsoDDE is a unified computational system that lends itself to a number of different endpoints.
- [Editor's note: Some drugs use cereblon to mark disease-causing proteins for destruction by the cell.]
Stats & Key Facts
- #The company raised $2.1 billion in funding, one of the largest biotech rounds ever, and signed drug-discovery deals with Novartis and Eli Lilly.
- #The company has signed major drug-discovery partnerships with Novartis and Eli Lilly and recently raised US $2.1 billion in funding .
For more than a decade, artificial intelligence has been touted as a way to dramatically accelerate drug discovery . Yet despite billions of dollars in investment, relatively few AI-designed medicines have made it to patients. That's partially because the timelines for careful drug testing can't be easily compressed-and partially because drug development is just really hard.
Isomorphic Labs , the Google DeepMind spin-off that's building on DeepMind's Nobel Prize-winning work on protein structure prediction , may be making the most progress. The company has signed major drug-discovery partnerships with Novartis and Eli Lilly and recently raised US $2.1 billion in funding . In February, it published a technical report describing its new Isomorphic Drug Design Engine, a system created to discover the "pockets" on proteins where drugs can bind and in general to predict how proteins and drug molecules interact.
IEEE Spectrum spoke with Adrian Stecuła , a group leader in the machine learning organization at Isomorphic Labs, about how close AI may be to becoming a practical tool for designing new medicines. Going Beyond AlphaFold AlphaFold2 and AlphaFold3 were massive leaps forward for computational biology. Why weren't those models sufficient for actually designing drugs?
For more details please read the original article at IEEE Spectrum AI.
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