Today I became a British citizen! 🇬🇧

#ISMBECCB2025 is over! Back to London tomorrow after a science feast, a talk, and a selfie with John Jumper. Not too bad!

However, these novel domain combinations comprise only a small fraction (0.3%) of ESM-only clusters. The remainder are mostly low-quality predictions (53%), fragments (16%), known domains with potential unknown extensions (19%), or without identifiable domains (9.3%).

@yewonhan.bsky.social identified 11,941 novel multi-domain combinations!
We found membrane-associated domains (e.g., TonB dependent receptor), highlighting domain recombination rather than new folds as a driver of structural innovation in ESMatlas.

ESM-only clusters contain ZERO novel folds using the TED workflow. Re-modelling discarded domains (2.3M) with ColabFold revealed 1 novel fold; unlike AFDB’s >7k novel folds, hinting at a saturating fold space or ESMfold limitations.

With MGnify environmental labels, we computed the lowest common biomes per structural cluster, revealing protein adaptations unique to specific environments, especially extreme ones like hyperthermal, hypersaline, and glaciers.

We annotated ESMatlas with MMseqs2 taxonomy (93% coverage) and computed the lowest common ancestors (LCA). Most LCAs are at the superkingdom level, indicating structures shared across domains. Avg. clusters/genus: Bacteria 1,557; Archaea 723; Viruses 17; Eukaryotes 2 (sampling bias).

Aria is finally home with us today and she’s a healthy ray of sunshine!

While the first few days were scary for both mom and baby, we can’t wait to raise this wonderful little girl together! ❤️

See you in Liverpool at ISMB/ECCB 2025!

Back to Sevilla for a viva!

Very emotional, my flat was in this square, and I loved living there during my PhD ❤️

Today we had the pleasure of listening to a great talk by @gonzaparra.bsky.social at UCL!

Gave a lecture in the same hall where I graduated at the University of Padova, and got to trek up to my mountains!

For those without access to the
Science article, we added a full access link on the TED website (ted.cathdb.info) landing page!

6/6

All data and code to reproduce TED and TED-web are available in Zenodo

zenodo.org/records/1390...

Here you can find per-chain and per-domain annotations, domain interaction data and model weights
4/6 🧵⤵️

Ian Sillitoe made a beautiful web interface for TED (ted.cathdb.info), which allows the community to look up their favourite UniProt Identifier, visualise domain annotations and associated metadata on quality and interactions.

3/6 🧵⤵️

Compared to our bioRxiv version, we processed TED redundant in the same fashion as TED100, swapping the previous multi-chain approach with a single-chain approach.

Each of the 214M chains in TED is now being treated equally, identifying 365 million protein domains.

2/6 🧵⤵️

My dad travels a lot for work to Milan, here are his favourite picks!