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1/5 Today, I’m sharing 7yrs of work. I believe we discovered a comprehensive mapping from protein structure to glycan structure, a genetic encoding for specific glycans, and a new paradigm in extracellular biology. biorxiv.org/content/10.110… #Glycotime

Our work validating designed membrane b-barrels in silico is published! It started as Elixir #3DBioinfo meeting discussion (I generated models instead of preparing my talk), then a fun exchange with Sergey Ovchinnikov. Thanks to all! VIB_StructuralBiologyBrussels ELIXIR Belgium onlinelibrary.wiley.com/doi/10.1002/pr…

Today in nature we present the results of our exploration of the soluble protein universe and the design of functional soluble membrane proteins with Casper Goverde Nico Goldbach Bruno Correia 1/6 nature.com/articles/s4158…

Yesterday, I had the chance to present my first spotlight poster at #MoML2024 at Mila - Institut québécois d'IA AI Institute! I presented joint work done with Luisa Kärmer and our amazing advisors, Julia Westermayr and Jens Meiler Lab. Huge thanks to @Esporascicomm for the amazing graphic design work!

And finally, we wanted to explore how good AlphaFold2 is at predicting orthogonality. Turns out it's not that sensitive (it wants to always pair proteins together). However, using physics-based Rosetta metrics we could easily train good predictors for each protein family.

Do you want to publish your genomes to SeqCode ? Maybe my #Snakemake pipeline could be of interest to you! It quickly lets you check if your assemblies reach the required criteria and gives you an easy to read report like this as an output 🙂 github.com/richardstoeckl…

Have you ever wanted to design protein binders with ease? Today we present 𝑩𝒊𝒏𝒅𝑪𝒓𝒂𝒇𝒕, a user-friendly and open-source pipeline that allows to anyone to create protein binders de novo with high experimental success rates. Bruno Correia Sergey Ovchinnikov biorxiv.org/content/10.110…

A new tool arriving with extensive documentation and even an example SLURM script is a rare and much-appreciated exception

Antibodies are highly diverse, but most possible sequences are unstable or polyreactive. In this work led by Milind Jagota, we propose a new source of data for modeling constraints from these properties. Our models show clear improvements in predicting antibody dysfunction.(1/n)

Thrilled to announce Boltz-1, the first open-source and commercially available model to achieve AlphaFold3-level accuracy on biomolecular structure prediction! An exciting collaboration with Jeremy Wohlwend, Saro and an amazing team at MIT and Genesis Therapeutics. A thread!

New preprint retraining ProteinMPNN on proteins from hyperthermophiles to design thermostable proteins (including first experimental validation). Fun project together with Phillip Schlegel and Max Beining. biorxiv.org/content/10.110…

Thanks for the (LLM generated?) highlight, but maybe tone down the sensationalist language a bit😅

🚨 Excited to announce the release of the DL4Proteins notebook series! 🌟 Learn AI for protein design with hands-on Colab tutorials inspired by the groundbreaking work of 2024 Chemistry Nobel Laureates David Baker, Demis Hassabis, & John Jumper. github.com/Graylab/DL4Pro…

I’m excited to share our significantly-updated preprint on de novo antibody design, where we now demonstrate the structurally accurate design of scFvs (in addition to VHHs) with RFdiffusion! biorxiv.org/content/10.110…

Thrilled to announce that this year’s European RosettaCon protein design conference will take place in Ljubljana, Oct 20–22, 2025! Open to all, with a remote keynote by Nobel laureate David Baker. More info coming soon — it’s going to be amazing! Hope to see you there!

I’m happy to announce my latest paper has been released as a preprint on BioRxiv: Predictions from Deep Learning Propose Substantial Protein-Carbohydrate Interplay. This paper was only able to happen thanks to both Jeffrey J. Gray and Ronald Schnaar doi.org/10.1101/2025.0…

Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀