[Jongkees-group.beta] FW: Scientific Guest Speaker cryoEM

[Jongkees, S.A.K. (Seino)]

Seino A. K. Jongkees, Ph.D.
Associate Professor
AIMMS Amsterdam Institute of Molecular and Life Sciences
[Logo][AIMMS FESTIVAL – A festival of molecular science]
T +31 (0)6 5722 7168<tel:+31657227168> | jongkeeslab.com<http://jongkeeslab.com/> | s.a.k.jongkees at vu.nl<mailto:s.a.k.jongkees at vu.nl>
Vrije Universiteit Amsterdam, Chemistry and Pharmaceutical Sciences,
Visiting address: O|2 building O2-03W11, de Boelelaan 1108, 1081 HZ Amsterdam
Postal address: O2 03W11 c/o goederenontvangst, Van der Boechorststraat 3, 1081 BT Amsterdam

From: Hennig, S. (Sven) <s.hennig at vu.nl>
Date: Monday, 19 May 2025 at 09:40
To: Beta Allgrossmann <allgrossmann.beta at vu.nl>, Jongkees, S.A.K. (Seino) <s.a.k.jongkees at vu.nl>
Subject: Scientific Guest Speaker cryoEM
Hi all,
@Seino: could you please forward to interested people from your network. thx.

Each year, we invite scientific cryoEM guest speakes in our Biostructural Elucidation course. This is a Bachelors course and the guest speaker is asked to give a road introduction as well as dive detailed into a few of their research topics.

Please find the details below and I would be glad to see you there.

Cheers Sven



 We are pleased to welcome Alisia Fadini from University of Cambridge, who will be visiting the VU and giving a seminar primarily aimed at structural biology students.



Date: TODAY: Monday, May 19

Time: 13:30–15:15

Location: NU-Theatre 9



Alisia is currently working with the groups of Randy Read (University of Cambridge) and Mohammed AlQuraishi (Columbia University) at the cutting edge of machine learning–driven protein structure prediction.



Title:  ROCKET: an AlphaFold augmentation integrating crystallographic & cryoEM/ET data

Structural biology is in an era of dynamics and macromolecular assemblies, but turning raw experimental data into atomic models at scale remains challenging. We introduce ROCKET: an AlphaFold augmentation that integrates crystallographic and cryoEM/ET data, with room for more! AF-based methods encode rich structural priors but lack a general mechanism for integrating arbitrary data modalities. ROCKET tackles this by optimizing latent representations to fit experimental data at inference time, without retraining. ROCKET integrates experimental likelihood targets within AlphaFold’s differentiable prediction pipeline to optimize MSA profile features. Structure refinement becomes a search in evolutionary space instead of Cartesian space. What does this unlock? ROCKET samples barrier-crossing conformations that standard refinement methods often fail to reach, such as ligand-induced loop rearrangements or domain shifts.

The low-resolution challenge is also particularly key for emerging cryo-ET data. We find that ROCKET remains robust in this regime and extracts different conformations from sub-tomogram averages.

ROCKET performs a new type of structure refinement by optimizing latent representations in evolutionary space. This unlocks possibilities for high-throughput ligand screening, assemblies solved at low resolution, and conformational landscapes – bringing automation towards new frontiers.



After the seminar, there will be a borrel/drinks, offering a chance to chat with the speaker in a more informal setting. Everyone is welcome!







Dr. Sven Hennig

Associate Professor
Structural Chemical Biology
Head of Crystallography

Vrije University Amsterdam
De Boelelaan 1108, O|2 04E05
1081 HZ Amsterdam, Netherlands

email: s.hennig at vu.nl<mailto:s.hennig at vu.nl>
web: svenslab.com


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