• Email Bluesky Facebook LinkedIn Reddit Whatsapp X The AI tool includes predictions of how proteins interact with potential therapeutic molecules.Credit: Isomorphic Labs Nearly two years after Google DeepMind released an updatedAlphaFold3 geared at drug discovery, its biopharmaceuticals spin-off, Isomorphic Labs, announced an even more powerful artificial-intelligence model - and they’re keeping it all to themselves. • Isomorphic Labs, based in London, touted the capacities of its ‘drug-discovery engine’ - which it calls IsoDDE - in a 27-pagetechnical report, released on 10 February. • Achievements, including precise predictions of how proteins interact with potential drugs and antibody structures, have impressed scientists working in the field. • Yet unlike the AlphaFold AI systems for predicting protein structure - which were made accessible to other researchers and described in depth in journal articles1,2- IsoDDE is proprietary, and the technical paper offers scant insight into how to achieve similar results. • AlphaFold is five years old - these charts show how it revolutionized science AlphaFold is five years old - these charts show how it revolutionized science “It’s a major advance, on the scale of an AlphaFold4,” referring to an unreleased future generation of Google DeepMind’s technology, says Mohammed AlQuraishi, a computational biologist at Columbia University in New York City who is working to develop fully open-source versions of AlphaFold. • “The problem, of course, is that we know nothing of the details.” Drug-protein interactions AlphaFold 3 was developed with drug discovery in mind.

Article Summaries:

  • Isomorphic Labs, a London‑based spin‑off of Google DeepMind, unveiled its proprietary drug‑discovery AI, IsoDDE, in a 27‑page technical report released on 10 February. The model claims to outperform AlphaFold 3 and open‑source rivals such as MIT’s Boltz‑2 in predicting protein‑drug binding affinity and antibody‑target interactions, including for molecules far outside its training data. Unlike AlphaFold, IsoDDE remains closed‑source, offering limited detail on its architecture or training data. While the scientific community praises the performance, the lack of transparency hampers efforts to replicate or build open‑source alternatives.

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