Landing soon: An academic consortium for open-source, statistical structural biology!
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Joined March 2026
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1/5
Ensembles are hot in structural biology!
But here’s a question we don’t ask enough:
What information survives measurement and processing?
In our latest blog, @PilarCossio2 @EmilThomasen and @mhli41 have a think 🤔:
rs-station.github.io/2026/08…
🤖 Made with AI
4/5
Then comes processing.
Cryo-EM preserves molecule-to-molecule variation, but filtering, alignment, classification, and reconstruction can remove or compress that information.
Crucially, a reconstruction can gain spatial resolution while losing ensemble information.
4/5
Then comes processing.
Cryo-EM preserves molecule-to-molecule variation, but filtering, alignment, classification, and reconstruction can remove or compress that information.
Crucially, a reconstruction can gain spatial resolution while losing ensemble information.
Reciprocal Space Station retweeted
OpenBind intends to collect 10,000s of protein-ligand structures & affinities. To prioritize what we collect next, we need cofolding models trained on the latest data. Today we're releasing OpenBind-0 and 717 new ligand-bound structures.
6/ Concretely, we will build:
• Data libraries for diffraction, scattering, imaging, and time-resolved experiments.
• Differentiable forward models that connect experiments to conformations.
• Data-driven tools that turn experiment into structure imbued with dynamics.
7/ Where we're going: teaming up with @open_fold, OpenBind, and cryo-EM + X-ray facilities to make structure beyond the single-structure frontier a reality.
Want in?
We’re an open community of developers.
Join us:
🔗 rs-station.github.io/
slack: reciprocalspa-cfs9659.slack.…
This is the future, the way real proteins work to process information and energy -- we are looking forward to seeing experimental (wet-lab) validation of the designs!
Binder design has come of age thanks to generative models—but how can we access the wider array of dynamic, multistate protein functions, so elegantly employed by nature?
@mihirbafna14 and I are excited to share SwitchCraft, a framework for designing such functions. (1/7)
Reciprocal Space Station retweeted
AlphaFold-like models such as Boltz-2 and AlphaFold3 learn powerful priors over structures from PDB. But how can we make them aware of new X-ray crystallography data?
Introducing CrystalBoltz: end-to-end X-ray structure determination via experiment-guided diffusion.
1/4 🧵
What's the future of structural biology look like? Our very own reciprocal astronaut Alisia Fadini recently joined Jay Chodaparambil, @AdamsCioaba , @RoehmRobin and Derek Low for a panel on the future of SBDD in Boston at #IBA2026 to discuss exactly that!
Amazing work from the #openbind team -- first data and model release from the world's biggest structure generating initiative.
We're looking forward to working together to get those datasets modeled as quickly, automatically, and accurately as possible!
openbind.uk/news/blog-inside…
Want to steer structure predictions to explain data?
Recirpocal astronauts @hlws_bot @mhli41 and coauthors are pushing the frontier with EmbedOpt, showing that not all steerings strategies are made equal!
We, @hlws_bot @PilarCossio2 @JiequnH, are sharing the official code release for EmbedOpt for seamless inference-time steering of protein diffusion models at github.com/rs-station/embedo…,
featuring:
✨ Tutorial on a real CryoEM map (EMDB-63136) (check out the animation below!).
📦 Environment locked with pixi for zero-headache reproducibility.
🛠️ Fully compatible with the new Protenix 2.0 codebase.
📊 All scripts to reproduce the paper's benchmark results are included out-of-the-box.
We are also proud to host this under the Reciprocal Space Station (RSS, @open_rss)—our growing hub for open-source structural biology software! 🌌
Paper: arxiv.org/abs/2602.05285