Riboseek is a fast RNA/DNA search. More sensitive than nhmmer at 250x speed. Structure-aware realignment produces MSAs approaching rMSA quality. Plus 1.7M precomputed RNA MSAs, and an API to search your own 📄 www.biorxiv.org/content/10.6... 💾 github.com/steineggerla... 🌐 search.foldseek.com/riboseek

Great summary and insight into Folddisco. 🧶🧬

ICML is happening in Seoul this year, and I’ve been getting several messages about lab visits. Who else will be in town and would like to meet? @milot.bsky.social lab and mine are planning a dinner on July 7th, after the reception. Let me know if you’re interested!

Does your designed active site already exist in nature? Is an uncharacterized protein hiding a catalytic site or a pocket? Folddisco answers both, searching millions of structures for a 3D motif in seconds. @natbiotech.nature.com 🧬 📄 www.nature.com/articles/s41... 🧵1/7👇

Structural motif search across the protein universe with Folddisco - Nature Biotechnology

Folddisco enables protein structural motif search in million scale databases.

nature.com

Structural motif search across the protein universe with Folddisco - @martinsteinegger.bsky.social go.nature.com/4g8lCb0

Structural motif search across the protein universe with Folddisco - Nature Biotechnology

Folddisco enables protein structural motif search in million scale databases.

go.nature.com

Meet the Folddisco Marv, designed by Hyunbin Kim, who also developed Folddisco.

Folddisco is now published @natbiotech.nature.com. It’s a fast motif search for similar 3D DISCOntinuous residues like catalytic sites or zinc fingers across the entire protein universe. 📄 www.nature.com/articles/s41... 💾 folddisco.foldseek.com​​​​​​​​​​​​​​​​ 🌐 https://search.foldseek.com/folddisco

Structural motif search across the protein universe with Folddisco - Nature Biotechnology

Folddisco enables protein structural motif search in million scale databases.

nature.com

Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · last yr.

Folddisco finds similar (dis)continuous 3D motifs in large protein structure databases. Its efficient index enables fast uncharacterized active site annotation, protein conformational state analysis and PPI interface comparison. 1/9🧶🧬 📄 www.biorxiv.org/content/10.1... 🌐 search.foldseek.com/folddisco

45 novel protein folds in the updated AFESM (AFDB + ESMatlas) manuscript: • 12 high-confidence folds in AFESM • 33 by ColabFold-repredicting 2.3M low-quality domains We show AFDB captures most domains already and ESMfold struggles with novelty 🌏 afesm.foldseek.com 📄 biorxiv.org/content/10.1...

My time in @martinsteinegger.bsky.social's group is ending, but I’m staying in Korea to build a lab at Sungkyunkwan University School of Medicine. If you or someone you know is interested in molecular machine learning and open-source bioinformatics, please reach out. I am hiring! mirdita.org

Mirdita Lab - Laboratory for Computational Biology & Molecular Machine Learning

Mirdita Lab builds scalable bioinformatics methods.

mirdita.org

End-to-end protein design in the browser through evedesign. Generate and interactively explore designs in 2D/3D and export them as codon-optimized DNA. The underlying open source framework (released soon) is build to easily add new methods, more on that soon. 🌐 evedesign.bio

Protein Structure Informed Bacteriophage Genome Annotation with Phold https://www.biorxiv.org/content/10.1101/2025.08.05.668817v1

Folddisco webserver result view update: - Added description texts for AFDB - Integrated TaxoView taxonomy visualization & filter by @sunjaelee.bsky.social - Inter-residue distance clustering by DBSCAN to explore motif diversity. 🌐 search.foldseek.com/folddisco 📄 www.biorxiv.org/content/10.1...

Today at 2 PM at 3DSIG #ISMBECCB2025, @nbordin.bsky.social presents our joint work on metagenomic-scale clustering and novel domain discovery in predicted structures! 📄 www.biorxiv.org/content/10.1... Also check out poster: B-50 lolalign Sensitive structural alignments by Lasse B-123 BFVD by Rachel

Metagenomic-scale analysis of the predicted protein structure universe

Protein structure prediction breakthroughs, notably AlphaFold2 and ESMfold, have led to an unprecedented influx of computationally derived structures. The AlphaFold Protein Structure Database now prov...

biorxiv.org

Our new preprint is out! www.biorxiv.org/content/10.1... In this study, we present the largest systematic analysis of microbiome structure and function, integrating 85K uniformly processed metagenomes from diverse habitats worldwide. @podlesny.bsky.social @jonas-bio.bsky.social @borklab.bsky.social

Planetary microbiome structure and generalist-driven gene flow across disparate habitats

Microbes are ubiquitous on Earth, forming microbiomes that sustain macroscopic life and biogeochemical cycles. Microbial dispersion, driven by natural processes and human activities, interconnects mic...

biorxiv.org

Today at 5pm, @eunbelivable.bsky.social will present her work on the Big Fantastic Viral Database (BFVD) at #ISMB2025 in BOSC. She also has a poster B-123 (tomorrow, 22nd), so please drop by to have ta chat and grab some stickers! 📄 academic.oup.com/nar/article/...

I’m excited to share our #Folddisco preprint! 🚀 We introduce a novel pairwise-geometric feature set and an optimized index structure to enable scalable structural motif search. Dive into our case studies and key results here: www.biorxiv.org/content/10.1...

Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · last yr.

Folddisco detects (partial) motifs, allowing for substitutions and angle-length variations, by utilizing an index storing all residue pairs within 20Å encoded as geometric features. For space efficiency, it omits positions and compresses ids through run-length encoding (1.4TB for 53M structures) 2/9

Folddisco accurately detects discontinuous motifs like zinc fingers and segment-based motifs, previously requiring separate tools. Additionally, we built a SCOPe benchmark by sampling conserved residues from families and measuring the recall up to the first false positive. 3/9

Folddisco builds indexes faster and smaller than previous tools: indexing AFDB50 (53M structures) takes only ~24h vs. ~20 days (extrapolated) for pyScoMotif. Querying a zinc-finger motif across AFDB50 takes just ~13s, up to 48x faster than pyScoMotif. 4/9

Folddisco can annotate proteins: querying a canonical zinc-finger uncovers an uncharacterized oyster protein and metagenomic proteins. It also detects partial catalytic metal sites in E. coli peptide deformylase. All of these hits would be missed by Foldseek or sequence aligners. 5/9

Folddisco can distinguish functional states. We searched GPCR activation motifs (CWxP, NPxxY, DRY), clearly separating active/inactive states. A search in the AFDB shows ~53% active, closely mirroring experimental PDB 54%, suggesting AlphaFold might follow its training conformation distribution. 6/9

Folddisco can be applied for PPI interface searches. When querying an interface between antibody chains (gray/black), it successfully identifies matching interfaces within monomeric antibody fragments (cyan), showcasing its potential to detect novel interaction partners and interfaces. 7/9

We provide a user-friendly Folddisco webserver, enabling instant structural motif searches in PDB, AFDB-Proteomes, AFDB50 (available later today), and ESMatlas (ESM30). Explore it here: search.foldseek.com/folddisco 8/9

Structural motif search across the protein-universe with Folddisco https://www.biorxiv.org/content/10.1101/2025.07.06.663357v1

We've updated our AFESM website to now include biome filtering, allowing exploration of protein structures adapted to specific environments. 🌐 afesm.foldseek.com Read more about the work in the skeetorial 🦋 bsky.app/profile/mart... or our preprint 📄 www.biorxiv.org/content/10.1...

Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · last yr.

AFESM: a metagenomic guide through the protein structure universe! We clustered 821M structures (AFDB&ESMatlas) into 5.12M groups; revealing biome-specific groups, only 1 new fold even after AlphaFold2 re-prediction & many novel domain combos. 🧵 🌐 afesm.foldseek.com 📄 www.biorxiv.org/content/10.1...

We 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. 5/n

ESMatlas uses MGnify environmental labels. Leveraging this, we computed the lowest common biomes per structural cluster, revealing protein adaptations unique to specific environments, especially extreme ones like hyperthermal, hypersaline, and glaciers. 3/n

AFESM: a metagenomic guide through the protein structure universe! We clustered 821M structures (AFDB&ESMatlas) into 5.12M groups; revealing biome-specific groups, only 1 new fold even after AlphaFold2 re-prediction & many novel domain combos. 🧵 🌐 afesm.foldseek.com 📄 www.biorxiv.org/content/10.1...

It's a big collaborative effort by @jingiyeo.bsky.social @yewonhan.bsky.social @nbordin.bsky.social, Andy Lau, Shaun M. Kandathil, @hbkgenomics.bsky.social, Eli Levy Karin, @milot.bsky.social David T. Jones and Christine Orengo. Visit our #RECOMB2025 poster (719) & talk (1 pm at B145 on April 29).

Check out Folddisco poster at #RECOMB2025!

Martin Steinegger 🇺🇦@martinsteinegger.bsky.social · last yr.

Visit our posters at #RECOMB2025 for: Structural: MSAs, Virus DB, Core Genes, Motif Discovery, Multimer Clustering & Search, pLM Foldseek, Environmental analysis Metagenomics: Classification & Metabuli App GPU-based & RNA search, Proteome clustering, Novel Ribozyme discovery & get Marv stickers!

SNU Profs Woon Ju Song & Martin Steinegger (Biology) developed the AI-based SeekRank algorithm to discover enzymes for cancer immunotherapy. doi.org/10.1093/nar/...

Discovery of highly active kynureninases for cancer immunotherapy through protein language model

Abstract. Tailor-made enzymes empower a wide range of versatile applications, although searching for the desirable enzymes often requires high throughput s

doi.org