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MLing biomolecules en route to structural systems biology. Asst Prof of Systems Biology @Columbia. Prev. @Harvard SysBio; @Stanford Genetics, Stats.
Mohammed AlQuraishi
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2mo
Our heavily updated final version of ROCKET for experiment-guided structure modeling is out in @naturemethods! New frontiers like high-throughput fragment screening and mid-res tomography are forcing a rethink of how experiments are modeled. ROCKET+OpenFold proposes a solution👇
Our latest blog takes a behind‑the‑scenes look at the experimental and structural biology work behind #OpenBind’s first data release - from protein production to crystallographic model building and refinement. https://loom.ly/Ydcti7A #StructuralBiology #Crystallography #OpenScience
1mo
The latest blog from #OpenBind introduces a new structure–affinity dataset for the EV‑A71 2A protease, alongside reference benchmarks and guidance on how the community can use and evaluate it across docking, co‑folding, and affinity prediction. https://loom.ly/6xPIRUc #OpenScience #DrugDiscovery #AI
1mo
New preprint on how disagreement among variant effect predictors can help guide prioritization of proteins for experimental analysis Work led by Nicolas F Jonsson in a collaboration with Joe Marsh. Preprint: doi.org/10.64898/202... @vxh357.bsky.social @jmarshlab.bsky.social 1/6
Mohammed AlQuraishi
Tremendously excited to help launch the Open Source for Science Fund, led by a fantastic team with an extraordinary track record of supporting open source software for science.
The CASP experiment is about to start - and is still short on challenging prediction targets. Ligand complexes, RNA, …
2mo
1mo
1mo
Very happy to have had a chance to attack an initially very low-resolution #cryo-EM map with #ROCKET! Thank you again @alisiafadini.bsky.social and all other co-authors of this important work, which truly shows the power of combining experimental structural biology and #AI inference. rdcu.be/fa9YH
2mo
Equivariance is dead! 😢 Or is it? 😈 Genie 3 is out! Our latest protein design model achieves SoTA results for binder design and motif scaffolding, greatly improving on BindCraft and Proteina-Complexa. It does so using all-atom SE(3)-equivariance based on a branched polymer representation👇
OpenBind
OpenBind
Kresten Lindorff-Larsen
Does AlphaFold’s latent space encode only the native state or something like a distribution over conformations? We begin to answer this question with ConforNets, a mechanism for producing diverse states, or very specific ones, via inference-time adaption of OF3p’s latent space👇
1mo
1mo
It's finally out!
Mohammed AlQuraishi
John Chodera
1mo
Mohammed AlQuraishi
Torsten Schwede
Luca Jovine
1mo
Today we're launching the Open Source for Science Fund, a new multi-donor philanthropic fund by Renaissance Philanthropy, seeded by @biohub.org and @wellcometrust.bsky.social, with support from @kavlifoundation.org and @researchsoftware.bsky.social 🧵 os4science.org/news/open-so...
Introducing Genie 3, a generative protein model that substantially advances the state-of-the-art for binder design, increasing in silico success rates by up to 20x on hard multimeric targets. It also debuts a form of inference-time scaling unobserved in other design models. 🧵1/8
A new multi-donor fund by Renaissance Philanthropy seeded by Biohub and Wellcome opens its first call for proposals.os4science.org
Open Source for Science Fund Launches to Power AI-Driven Discovery
1mo
Video
Janani Durairaj (Jay)
Yeqing Lin
Open Source for Science Fund
We introduce ConforNets, a mechanism for conformational control in AlphaFold3 models - SoTA at producing diverse conformations on every multistate benchmark (N=104) - Novel capability: transfer state from one protein to another Outperforms BioEmu, ConforMix and AFsample3 🧵1/8
1mo
Video
Minji Lee
ROCKET 🚀 inference-time optimization of AlphaFold to fit structural data is published! rdcu.be/fa9YH Since our preprint, we’ve pushed it to regimes where other methods break: low resolution, weak signal, real experimental edge cases. Here’s what we learned: 1/15
ROCKET 🚀 inference-time optimization of AlphaFold to fit structural data is published! rdcu.be/fa9YH Since our preprint, we’ve pushed it to regimes where other methods break: low resolution, weak signal, real experimental edge cases. Here’s what we learned: 1/15
2mo
2mo
Is #AI hitting a plateau in structure prediction? Help us find out at CASP17! 🧪🧬 Calling for Targets: Immune Complexes, protein - ligand complexes, RNA/DNA, conformational ensembles, membrane proteins, viral origins, and large complexes. The Rule of Thumb: If AF3 can’t model it, we want it.
Disagreement among variant effect predictors guides experimental prioritization of target proteins https://www.biorxiv.org/content/10.64898/2026.03.18.712765v1
3mo
2mo
Torsten Schwede
Alisia Fadini
Alisia Fadini
bioRxiv Bioinfo