The Ledger
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ESMC model search generates novel antibodies achieving therapeutic-grade binding affinity levels
“What we're able to see is that, you know, you can search ESMC and you can actually find antibodies that are reaching the level of affinity that are, I should say, are really at the level of affinity that is needed for therapeutic function and activity.”
Rives: ESMC is state of the art among open models for multimer prediction
“Yeah, I mean, I think we're state of the art for open models.”
AI cell simulations will enable parallel reasoning across millions of biological hypotheses
“We're gonna have increasingly capable and accurate digital representations of molecules, genomes, cells, ultimately physiology. That's where you want to get. We're gonna have to go up that, that complexity scale, the levels of biological complexity that requir…”
Scaling protein models by orders of magnitude unlocks emergent biological capabilities
“So our team has really explored that idea over a number of different years, and we've really kind of, I think, seen the scaling curve and really seen as we have increased models by an order of magnitude kind of in each generation that, you know, there's this e…”
Sparse autoencoders found a single learned feature for nucleophilic elbows in ESMC
“You know, what we found basically is that the model has a kind of a single feature for this nucleophilic elbow and is activating across these like very evolutionarily diverse families, you know, really completely different structural topologies, proteins that …”
Incorporating metagenomic training data eliminated diminishing returns in ESMC protein foundation models
“And then, you know, what we saw basically is, is, is there are no longer diminishing returns to scale. So that's really saying that ESM two was kind of data limited rather than compute limited for ESMC.”
Rives: ESMC Has Been Used to Successfully Design scFv Antibodies
“We've been able to use this to actually now go and design many protein binders, but I think sort of most excitingly, we've been able to use this to actually design antibodies, SCFVs, and we're seeing really, I think, exciting success rates and a small number o…”
Rives: Meta FAIR trained the first protein transformer language model
“And so my team, when we were at MetaFair, trained really the first transformer language model for protein biology.”
Biohub predicted 3D structures for 1.1 billion proteins from global sequence databases
“So we put together kind of all the world's largest protein sequence databases. And so that kind of amounts to 6.8 billion non-redundant proteins, and then we've resolved predicted structures for 1.1 billion of those, and we've also computed features across all…”
Rives: ESMC Added Billions of Metagenomic Sequences Beyond UniRef
“ESM-II is trained on Uniref. And for ESMC, we added metagenomics. So we added billions more sequences to the training data.”
Feng Zhang's laboratory used the ESM atlas to discover novel gene editors
“Actually, the first version of the ESM atlas was used by Fang Zhang's group to find A new gene editing system.”
Rives: ESMFold 2 yields atomic resolution predictions in seconds without MSAs
“So the other thing about ESM fold two is a really fast model because it doesn't require the multiple sequence alignment. So You know, you can do inference kind of, you know, directly from the sequence it takes seconds, you know, you can get an atomic resolutio…”
Rives: Existing Tech Can Scale Biological Data 10x–100x Before Hitting Limits
“I think with current technology, you know, we can definitely kind of get, get data, 10 X to a hundred X where it is today with like relatively reasonable investments, you know, but then to get another 10 X or more in there, that's going to require, require a l…”