Our paper on generalizable antibody-antigen binding affinity prediction has been featured on the cover of the August Issue of @NatComputSci! 📔🎉

Structure - > sequence models have different phylogenetic (and biochemical) preferences than protein language models. @OllyMCrook

Assessment of blind 3D structure modeling of #RNA and nucleic acid complexes now out in the #CASP16 special issue, led by @RachaelKretsch. We hope this benchmark, paper, metrics, and expert baselines drive much-needed progress by #CASP17 (May 2026)!

I am delighted to share this work, led by Miguel Alcantar and done in collaboration with Amgen, on the OrthoRep-driven evolution of computationally designed minibinders. Here, we focus not only on getting to high affinity, but also on mapping sequence-affinity landscapes of

OpenFold3-preview (OF3p) is out: a sneak peek of our AF3-based structure prediction model. Our aim for OF3 is full AF3-parity for every modality. We now believe we have a clear path towards this goal and are releasing OF3p to enable building in the OF3 ecosystem. More👇

Announcing our new protein design server https://t.co/uu4co1sHhq: • End-to-end protein design for everyone! • Analyze your generated library interactively and on 3D structures • Export codon-optimized DNA sequences for experimental testing. Developed in collaboration

AI models show promise for accelerating antibody drug discovery but can fall short in testing. Research from @OPIGlets, published in Nature Computational Science highlights the need for larger, and more diverse datasets for reliable prediction. 👉 https://t.co/KIYywJ2Q2Q

We're so excited to welcome our 2025 Fellows to Oxford for their first Science Leadership Program convening. And for 2025 Fellow @AlissaHummer, it is a homecoming! Our 2025 Fellows' stories and our Science Leadership Program exemplify our mission.

Immensely grateful to the Schmidt Science Fellowship, my mentors, and all the wonderful & inspiring people I have worked with over the past years.

Excited to be pivoting from molecules to cells for my Schmidt Science Fellowship, advised by @Prof_Lundberg and @WahChiu1! I’m looking forward to building ML models that better reflect how molecules & cells look in real life 🔬

The results are in: top codes in Stanford #RNA 3D Folding @kaggle are competitive with CASP16-leading humans Vfold, beat AlphaFold 3. Top team’s trick was template-based modeling, not #DeepLearning. Congrats: john, odat, Eigen, + all 1706 participants! https://t.co/EgzN3DTKNe

🚨 We’re hiring! The OPIG group is looking for multiple postdocs to join OpenBind, an open science initiative generating foundational structural biology data to power the next era of AI/ML for drug discovery. https://t.co/nCRTFuqadT https://t.co/ShjU5gOul8

Please apply to our tenure-track faculty position at @Stanford_ChEMH! We are searching for a new colleague working at the interface between computation and molecular sciences. See post below and pls forward widely! https://t.co/MPJ6yvTiPl

Announcing our FIRST AI competition: Antibody Developability Prediction Ginkgo Datapoints and @huggingface are teaming up to create the first open benchmark for AI-driven antibody developability modeling, with up to $60k in prizes.

Science delivers medicines, clean air and water, safe food, and smarter choices—saving billions of lives. Proposed cuts to @NIH and @NSF would shutter labs, stall new cures, hurt our economy, and send future scientists elsewhere. Hear from patients saved by science:

Our first pandemic preparedness database, Pox-AbDab, is now available! We present sequence, structural & functional data on antibodies and nanobodies that bind/neutralise orthopoxviruses: DB: https://t.co/5QnYw31zdJ Preprint: https://t.co/VUCKEpqa4z Work led by Henriette Capel

Huge thanks to my co-authors @con__schneider, @LewisChinery, Charlotte Deane @OPIGlets!

More information about the paper:

Link to the paper:

🚨Our August issue is now live and includes research on antibody-antigen binding, molecular screening for zeolite synthesis, psychological experiments with LLMs, and much more! https://t.co/Hi4HjAXndD