De novo design of phosphotyrosine peptide binders
Phosphorylation on tyrosine is a key step in many signaling pathways. Despite recent progress in de novo design of protein binders, there are no current methods for designing binders that recognize phosphorylated proteins and peptides; this is a challenging problem as phosphate groups are highly charged, and phosphorylation often occurs within unstructured regions. Here we introduce RoseTTAFold Diffusion 2 for Molecular Interfaces (RFD2-MI), a deep generative framework for the design of binders for protein, ligand, and covalently modified protein targets. We demonstrate the power and versatility of this method by designing binders for four critical phosphotyrosine sites on three clinically relevant targets: Cluster of Differentiation 3 (CD3ε), Epidermal Growth Factor Receptor (EGFR), Insulin Receptor (INSR) and Signal Transducer and Activator of Transcription 5 (STAT5). Experimental characterization shows that the designs bind their phosphotyrosine containing targets with affinities comparable to native binding sites and have negligible binding to non-phosphorylated targets or phosphopeptides with different sequences. X-ray crystal structures of generated binders to CD3ε and EGFR are very close to the design models, demonstrating the accuracy of the design approach. A designed binder to an EGFR intracellular region phosphorylated upon EGF activation co-localizes with the receptor following EGF stimulation in single-particle tracking (SPT) experiments, demonstrating pY specific recognition in living cells. RFD2-MI provides a generalizable all-atom diffusion framework for probing and modulating phosphorylation-dependent signaling, and more generally, for developing research tools and targeted therapeutics against post-translationally modified proteins. ### Competing Interest Statement The authors have declared no competing interest. NIH NCI, 1K99CA293001
Not new, but a new to us update:
The first preprint out of my lab! We joined forces with @kinasekid.bsky.social @jasonzxzhang.bsky.social and David Baker to study protein phosphorylation! Congrats to Isabella from my lab on her first first author paper! tinyurl.com/43jwwfua
29.01.2026 12:57
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It was such a fun journey working with Krishna’s lab and @kinasekid.bsky.social! Really excited to see where this phospho-binder technology goes!
29.01.2026 13:40
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Thrilled to announce our new preprint, “Protein Hunter: Exploiting Structure Hallucination within Diffusion for Protein Design,” in collaboration with @Griffin, @GBhardwaj8 and @sokrypton.org
🧬Code and notebooks will be released by the end of this week.
🎧Golden- Kpop Demon Hunters
13.10.2025 15:45
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We’d love to hear ideas for where phosphorylation - or PTM-specific binders could make a difference. If you’re interested in collaborating, please reach out! (8/8)
30.09.2025 21:55
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This was only possible in a team effort with great people! Thanks @jasonzxzhang.bsky.social, Kejia Wu, Brian Coventry, Gyu Rie Lee, Kody Klupt, Jiuhan Shi, Rafael Brent and the entire @uwproteindesign.bsky.social, with guidance from David Baker and many collaborators. 🙏 (7/8)
30.09.2025 21:55
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Specificity matters. An all-by-all assay showed strong diagonal binding - each binder recognized only its cognate phosphopeptide, with negligible cross-reactivity. (6/8)
30.09.2025 21:55
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Crystal structures of CD3ε and EGFR complexes matched design models within ~2 Å. The intended phosphate-binding motifs were reproduced with atomic accuracy, validating the approach. (5/8)
30.09.2025 21:55
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We tested four sites: CD3ε (TCR), EGFR pY1068 & pY1173, INSR pY1361. In each case, RFD2-MI produced compact proteins that selectively bound the phosphorylated peptide, confirmed by yeast display & BLI with comparable affinities to native phosphorylation binding domains. (4/8)
30.09.2025 21:55
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We built RFD2-MI, an all-atom diffusion model for molecular interfaces based on RFD2. It co-designs binder + peptide and uses 1D conditioning features like hotspots, secondary structure, and solvent exposure to steer phosphate-pocket formation. (3/8)
30.09.2025 21:55
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Existing tools fall short: antibodies can’t always tell sites apart, and natural domains like SH2 struggle with specificity. We needed a way to design de novo binders that are both phosphorylation- and sequence-specific. (2/8)
30.09.2025 21:55
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Phosphorylation on tyrosines control key pathways in immunity, cancer, and metabolism. For the first time, we can now design proteins that specifically recognize individual phosphotyrosines, even in disordered regions. (1/8)
Preprint: www.biorxiv.org/content/10.1...
30.09.2025 21:55
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Celebrating Seattle's 2024 Nobel Prize with Professor David Baker
YouTube video by UW Medicine
Who knew a Nobel Prize win could unlock an entire city? Join us live on YouTube as we celebrate 2024 Nobel Laureate David Baker together with the Mayor of Seattle and many others on March 10th starting at 5 pm (PT)! 🥇🔑🌇
www.youtube.com/live/z8NO4Bg...
07.03.2025 04:55
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A weekend project from a while back -- this little package (with no dependencies) allows you to interact with pymol remotely.
I use it a lot for my protein design workflows together with @biotite.bsky.social.
Just `pip install pymol-remote`
25.11.2024 14:50
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#CompChemSky 🧶🖥️🧬🧪
I wonder, is there any computational approach, that would find protein in PDB according to any arbitrary shape?
06.12.2023 19:23
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Sticker on a laptop saying 'I <3 Biophysics' with all the letters taken form protein structures from the PDB
New sticker design saying 'I <3 Biophysics' with a different heart from SARS-CoV-2 NSP13
I would also be very interested in find some alternative letters, for example a B and P for a new ‘I ❤️ Biophysics’ sticker. Currently its hard to read for some people even with the Howarth and Chroma alphabet. SARS-CoV-2 NSP13 provided an amazing heart btw!
07.12.2023 00:37
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The Praetorius lab for Biomolecular Design at the Institute of Science and Technology Austria (ISTA) is looking for grad students in 2024. If you are interested in protein design at a great institute near Vienna reach out to me!
www.dropbox.com/scl/fi/6iny2...
28.11.2023 01:08
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Update on the Chroma vs RfDiffusion analysis.
ProteinMPNN just doesn't like Chroma's backbones (poor prediction of proteinMPNN generated sequences by ESMFold). Interestingly, Chroma's own sequence design method (which was trained in the context of partially noise backbones) loves it! (1/3)
18.11.2023 19:04
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"Performance and structural coverage of the
latest, in-development AlphaFold model" 🧪🧶🧬
DeepMind & Isomorphic Labs sharing some updates (but no code) on what is presumably alphafold 3, capable of modeling ligands, nucleic acids, antibody-antigen complexes etc
storage.googleapis.com/deepmind-med...
31.10.2023 13:48
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