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I wrote a review (with Joseph Watson Sidney Lisanza ) on protein design using structure prediction models--i.e. hallucination, inpainting, diffusion. This approach to protein design started as a convenience but has turned out to be surprisingly powerful. cshperspectives.cshlp.org/content/early/…

We love the excitement & results from the community on AlphaFold 3 and are doubling the AF Server daily job limit to 20. Happy to also share that we're working on releasing the AF3 model (incl weights) for academic use, which doesn’t depend on our research infra, within 6 months.

I’m excited to share some of our progress at @Diffuse_Bio today, about a year and a half into our journey! 1/

🥁 Our manuscript "Multistate and functional protein design using RoseTTAFold sequence space diffusion" is finally out Nature Biotechnology! 🧵b/c it's changed a LOT since preprint! New highlights: - High res structures - Conditionally caged peptides - Multistate design

Really exciting work!! It was so fun to collaborate with the Baker lab team Sam Tipps Sidney Lisanza and Jacob Gershon to solve NMR structures of novel folds made with ProteinGenerator :)

I'm sharing my story in a difficult time for Palestinians and Lebanon, where we found refuge after being exiled from Haifa. I want to honor those who suffered the most and never got to live out their dreams—my grandparents, Jido Ali and Taita Khadejeh. I hope they’re proud (1/3)

Multistate and functional protein design using RoseTTAFold sequence space diffusion Nature Biotechnology 🚀 New baker from David Baker!🚀 1/ ProteinGenerator (PG) introduces a novel sequence space diffusion model, improving multistate and functional protein design by simultaneously

Thrilled to share our Nature Biotechnology paper “Multistate and functional protein design using RoseTTAFold sequence space diffusion” nature.com/articles/s4158….

Underappreciated things in this paper: 1. Structure color scheme 2. Sequences come directly from generative model without using MPNN sequence design. 68/96 expression rate on the small monomers with crazy AA compositions, lower (<50%) for repeat proteins.

“Proteins sticking to other proteins is what makes life exist.” 🧬 We explain the science behind AlphaProteo: our AI system for designing protein binders that holds huge potential for biology. ▶️ Hear from Jue Wang, co-lead of the protein design team, David La, research

We explore why framing the generative process in sequence space gives rise to unique forms of guidance for protein sequence and structural attributes. Excited to see this finally out! Sidney Lisanza Sam Tipps Lucas Arnoldt Institute for Protein Design

Didn’t appreciate how forward thinking and so on top of science David was until I graduated. Well deserved and congrats to all! Also big shoutout to the curators of the pdb and casp who without their work none of this would have been possible! Institute for Protein Design Google DeepMind

Now online: We created de novo insulin receptor agonists using computational protein design! Choi Lab Xiaochen Bai Preetham Venkatesh Institute for Protein Design #BakerLab biorxiv.org/content/10.110…

1/🧬 Excited to share PLAID, our new approach for co-generating sequence and all-atom protein structures by sampling from the latent space of ESMFold. This requires only sequences during training, which unlocks more data and annotations: bit.ly/plaid-proteins 🧵

stay tuned for more proper, detailed and exciting cover of this preprint, but whoa i'm so proud of the team Prescient Design and our achievements on <Lab-in-the-loop therapeutic antibody design with deep learning>!

Lab-in-the-loop therapeutic antibody design At Prescient Design Genentech we have spent 3+ years reimagining drug discovery. We built a machine learning system to design and execute experiments. Here's how it works and what we can do 🧵 1/