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@paulschanda.bsky.social

@paulschanda.bsky.social

148 Following1.1k Followers

Passionate for integrated structural biology, including NMR and many more. Particularly interested in protein dynamics, and therefore chaperones, enzymes and mitochondrial protein import. Fortunate to lead a great research team at IST Austria.

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@iomichiamofede.bsky.socialOct 13, 2026, 2:48 PMReposted by @paulschanda.bsky.social

🧲 #NMR is for small proteins... without the right tools.

Our new paper is out now in @jacs.acspublications.org
A shared effort with Rajkumar Singh, Anna Kapitonova, Virgil Aitenbichler, @giorgia-toscano.bsky.social, Barbara Perrone and @paulschanda.bsky.social

Paper: doi.org/10.1021/jacs...
1/🧵

Integrated Solid/Solution NMR Assignment Enables Mapping of Dynamics and Ligand Binding in a 134 kDa Enzyme
@paulschanda.bsky.socialOct 13, 2026, 1:22 PM

📢 Happy to share our latest publication in @jacs.acspublications.org led by Fede Napoli, showing how different #NMR approaches (solution, solid) provide atomic-level insights into a large #enzyme. Advanced methods, elegantly combined. Congrats @iomichiamofede.bsky.social
pubs.acs.org/doi/10.1021/...

@istaresearch.bsky.socialSep 3, 2026, 11:00 AMReposted by @paulschanda.bsky.social

With projects on AI, astrophysics, bacterial immune systems, quantum matter, and optics, five ISTA researchers have secured €9.2 million in highly selective Starting Grants from the ERC @erc.europa.eu​. Read: https://ista.ac.at/en/news/e9-2-million-in-eu-grants-for-ista/

@paulschanda.bsky.socialAug 30, 2026, 5:49 PM

The ICMRBS conference in Davos has been fantastic. Relaxed atmosphere, top science, great opportunities to connect. I'm happy to be part of the #NMR community, a supportive & friendly crowd. Thanks @icmrbs2026.bsky.social for everything! The (short) bike trip back was a nice way to finish the week.

@paulschanda.bsky.socialOct 18, 2025, 6:59 PM

📢 New preprint:
Experiment-guided AlphaFold3 resolves accurate protein ensembles.
doi.org/10.1101/2025...

AlphaFold3 is incredible, but has crucial limitations: it typically collapses to a single conformation, ignoring the inherent dynamics of proteins. And it can be wrong. Here's a solution. 🧵👇

Structures from AlphaFold3 - while often impressively good - tend to fail representing the dynamic ensembles accurately. And often parts of the structure are not correct.
Adding experimental data, directly in AlphaFold's diffusion step, provides physically realistic protein ensembles. This image shows two cases where AlphaFold3-only structures were largely improved by guiding with experimental data.
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