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

Characterizing AI-designed proteins requires quantitative biochemistry at massive scale. Enter Amplicon/Protein Bead Display (APB-Display), a fully in vitro platform that quantifies Kd's for >100,000 variants in <3 days (preprint link below!) @Stanford_ChEMH @czbiohub (1/n)

128 double quantum dots, the building blocks that become qubits, tuned automatically across a single silicon chip. 64 devices. No human in the loop. A future quantum computer needs millions of qubits. Automation isn't optional. It's the only path. conductorquantum.substack.co…

NVIDIA cuQuantum and CUDA-Q are making #quantumcomputing more accessible through GPU-accelerated quantum simulations. Check out how @conductorquant's Coda is enabling the next generation of developers to convert ideas into quantum circuits by harnessing these simulations. ➡️ conductorquantum.substack.co…

Conductor Quantum: Coda - Natural language quantum computing producthunt.com/products/con… via @producthunt

Announcing Coda: natural language quantum computing Tell Coda what you want to do. It builds the quantum program and runs it on real quantum hardware. Live on @rigetti, @IonQ_Inc, and @meetIQM quantum computers with simulations via @IBM @qiskit and @nvidia cuQuantum CUDA-Q.

Deep learning is cool...but have you tried ✨logistic regression✨? Using just one round of sorting, these models predict affinity boosts and design nanobodies up to ~2500× better. Great work Steffanie, Eddie & team! 🧠🧬 biorxiv.org/content/10.64898…

New paper “Proteome-wide model for human disease genetics” is now live at Nature Genetics: rdcu.be/eRu7K popEVE (pop.evemodel.org) finds the needles in the haystacks of human genetic variation:

1/ Big news: our third BiTS cohort — focused on the Americas and powered by @coeff_giving — is now open for applications! You'll design a large-scale coordinated research program and pitch directly to government agencies and philanthropic funders in Spring/Summer 2026. 👇

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)! doi.org/10.1002/prot.70072

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 diverse evolutionary outcomes. One way we arrive at diverse evolutionary outcomes is through "neutral drift" where we take one binder and diverge it into many by selecting for the maintenance of (but not improvement of) binding. This is very easy to do with OrthoRep because rapid mutation of the binder occurs autonomously. The result is a rich sequence-affinity dataset spanning both a range of sequences and affinities. We are now scaling these approaches, including to antibodies and a broad array of targets, to get the right distribution and volume of data for training generative models for binder design. biorxiv.org/content/10.1101/…

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 evedesign.bio: • 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 between @deboramarks, @thomas_a_hopf, @SteineggerM, Simon d'Oelsnitz, Chris Sander, Artem Gazizov,@haysunny_hi, Milot Mirdita, Sergio Garcia Busto, Jake Reardon

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. 👉 tinyurl.com/rzemvhkz

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. schmidtsciencefellows.org/ne…