Romain Lacombe
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rlacombe.bsky.social
Romain Lacombe
@rlacombe.bsky.social
AI/ML⚡️& ChemE 🧪 @ Stanford.
Past: founder Plume Labs (acquired by AccuWeather).

Don’t be fooled by the tweets that I’ve got
I’m still I’m still @rlacombe on X (and here).

-> https://romainlacombe.com
That’s a bit of relief at least! 🐚🦪
April 5, 2025 at 7:23 AM
Pierre Clostermann during WWII
April 2, 2025 at 9:51 AM
Thanks to Hannah @wastyk.bsky.social & Will at InterfaceBio for advice on sactipeptides, and to the authors of AlphaFold 2 & 3, ESMFold, Boltz-1 (@gcorso.bsky.social), and more!

📝 Link to paper: biorxiv.org/content/10.1...

💻 Link to code: github.com/rlacombe/Sac...
Non-Canonical Crosslinks Confound Evolutionary Protein Structure Models
Evolution-based protein structure prediction models have achieved breakthrough success in recent years. However, they struggle to generalize beyond evolutionary priors and on sequences lacking rich ho...
biorxiv.org
March 27, 2025 at 8:18 PM
Excited to be presenting this work at the
@stanfordbiosci.bsky.social workshop on Experimental Design in AI for Science next week!

More info on the event here: edai4science.github.io
Experimental Design: AI for Science
edai4science.github.io
March 27, 2025 at 8:18 PM
These results highlight the limits of the (extremely successful) evolutionary approach to protein structure prediction.

We will likely need physics-informed models to reach accurate 3D structure predictions on rare PTMs and out-of-domain proteins beyond evolutionary priors.
March 27, 2025 at 8:18 PM
No model achieved crosslink distances near the experimentally observed 1.8Å sulfur-to-α-carbon bond length, with average performance at 10-12Å.

Most models incorrectly predicted disulfide bonds instead of thioether crosslinks, highlighting their reliance on evolutionary priors.
March 27, 2025 at 8:18 PM
We evaluate 6 leading protein structure predictors—AlphaFold 2 and 3, Boltz-1, ESMFold, OmegaFold, and RoseTTAFold 2—on the 10 known sactipeptides.

All models exhibit limited performance, with an average GDT-TS of only 11.5% for known sactipeptides and 12.6% for unknown ones.
March 27, 2025 at 8:18 PM
This helps us probe how deep learning models generalize beyond evolutionary priors.

We introduce a new, zero-shot benchmark for structure models: measuring how the 3D conformations predicted for sactipeptides match the geometry imposed by their known thioether crosslinks.
March 27, 2025 at 8:18 PM
These non-canonical crosslinks are challenging and underrepresented in structural datasets. Crucially, *only 5* of the 10 known sactipeptides have a resolved 3d conformation with a PDB entry. *But* their 2d crosslink structure is known, which constrains possible 3d geometries!
March 27, 2025 at 8:18 PM
Evolution-based protein structure prediction models have revolutionized structural biology but struggle with rare post-translational modifications (PTMs). We evaluate them on sactipeptides, a rare class of 10 known peptides with unique sulfur-to-α-carbon thioether crosslinks.
March 27, 2025 at 8:18 PM
Pre-ordered! 🛍️🤞
March 25, 2025 at 6:00 PM
Oooh that looks beautiful! When can we pre-order?
March 25, 2025 at 5:26 PM
Anecdotally, @dcrainmaker.com has a treasure trove of GPS accuracy tests in land and marine conditions for most watches and trackers on the market.
March 25, 2025 at 1:04 AM
This guy is *such* a jerk. Ugh! Only good thing is it’s out in the open for anyone to see.
December 15, 2024 at 7:31 AM