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Ieva Pudžiuvelytė

@ievapudz.bsky.social
17 followers 20 following 0 posts

PhD student @biozentrum.unibas.ch‬

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Reposted by Ieva Pudžiuvelytė
Peter Škrinjar @peterskrinjar.bsky.social · 11/05/2026
Now published in NSMB! Paper: doi.org/10.1038/s415... Full PDF: rdcu.be/fhBtI Overview of additions since the preprint👇 (1/5)
doi.org
Evaluating generalization in protein–ligand cofolding methods - Nature Structural & Molecular Biology
This work introduces the Runs N’ Poses dataset for benchmarking deep learning methods on the protein–ligand complex prediction task. It shows that current methods rely on memorization, challenging the...
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Reposted by Ieva Pudžiuvelytė
Daniil Litvinov @daniil-litvinov.bsky.social · 19/03/2026
I'm excited to share *Stoic*, a method for fast and accurate protein complex stoichiometry prediction directly from sequence. Preprint: www.biorxiv.org/content/10.6... 🧵👇(1/10)
biorxiv.org
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Reposted by Ieva Pudžiuvelytė
Janani Durairaj (Jay) @ninjani.bsky.social · 11/02/2026
A fun little idea that worked surprisingly well, using a structure-informed yet structure-independent alphabet for de novo protein design: www.biorxiv.org/content/10.6... 🧵(1/n)
biorxiv.org
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Reposted by Ieva Pudžiuvelytė
Lorenzo Pantolini @lorenzopantolini.bsky.social · 01/12/2025
Fresh from bioRxiv our latest work introducing The Embedded Alphabet (TEA), a powerful new representation for protein sequences obtained by discretising ESM2 embeddings into 20 characters. Pre-print: www.biorxiv.org/content/10.1... 🧵👇(1/n)
biorxiv.org
Rewriting protein alphabets with language models
Detecting remote homology with speed and sensitivity is crucial for tasks like function annotation and structure prediction. We introduce a novel approach using contrastive learning to convert protein...
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