I am excited to share that I will be starting my lab @Sanquin Research in Amsterdam this month! Looking forward to do structural biology and use protein engineering to tackle important questions related to 🩸blood🩸 protein complexes in health and disease. 🧬🧫🔬🧪👨‍🔬 #cryoEM

AI for redesigning molecular biology tools like affinity tags. Here's a short demo testing ESMFold2 to redesign the FLAG affinity tag using the anti-FLAG antibody structure (M2, PDB: 8RMO) as a reference. Target to redesign = FLAG: DYKDDDDK ESMFold2 was also tested in the opposite direction, where a new potential FLAG tag binder was designed. AI agents made this presentation for the demo using ChimeraX and the OpenAI text to speech API.

Can someone start a journal called “Cell Atlases” so that the rest of the journals can go back to publishing interesting things?

🚨 HOLY SH*T: Fox News just cut one of their reporters off as they seemed to indicate the shooting was a pre-planned false flag.

My first time at the Dutch society for thrombosis and hemostasis society (NVTH) symposium, looking forward to hear lots of interesting science and get to know the community!

Now that we are in a full-blown oil crisis, can we finally just ban these cancer-causing fumes exhausting combustion engine scooters? Swap it for an electric bike (similar price) or scooter, or even better, an old-fashioned muscle-powered bicycle (cheapest and best for health)!!

Happy lunar new year to all those who celebrate!! 🐴

'New research mostly starts with the arrival of junior group leaders'. Amen @ThijnBrummel!! 🙏

It feels official now... sanquin.nl/en/researchers/re…

Fuck I love this figure. Pure fucking art.

Just got this in the mail from @Addgene, recognizing that 100 labs have now ordered our anti-FLAG-M2 plasmids via their service. @MFPronker @Weiweipeng1992 addgene.org/Joost_Snijder/ pubs.acs.org/doi/full/10.102…

This paper from Harvard and MIT quietly answers the most important AI question nobody benchmarks properly: Can LLMs actually discover science, or are they just good at talking about it? The paper is called “Evaluating Large Language Models in Scientific Discovery”, and instead of asking models trivia questions, it tests something much harder: Can models form hypotheses, design experiments, interpret results, and update beliefs like real scientists? Here’s what the authors did differently 👇 • They evaluate LLMs across the full discovery loop hypothesis → experiment → observation → revision • Tasks span biology, chemistry, and physics, not toy puzzles • Models must work with incomplete data, noisy results, and false leads • Success is measured by scientific progress, not fluency or confidence What they found is sobering. LLMs are decent at suggesting hypotheses, but brittle at everything that follows. ✓ They overfit to surface patterns ✓ They struggle to abandon bad hypotheses even when evidence contradicts them ✓ They confuse correlation for causation ✓ They hallucinate explanations when experiments fail ✓ They optimize for plausibility, not truth Most striking result: `High benchmark scores do not correlate with scientific discovery ability.` Some top models that dominate standard reasoning tests completely fail when forced to run iterative experiments and update theories. Why this matters: Real science is not one-shot reasoning. It’s feedback, failure, revision, and restraint. LLMs today: • Talk like scientists • Write like scientists • But don’t think like scientists yet The paper’s core takeaway: Scientific intelligence is not language intelligence. It requires memory, hypothesis tracking, causal reasoning, and the ability to say “I was wrong.” Until models can reliably do that, claims about “AI scientists” are mostly premature. This paper doesn’t hype AI. It defines the gap we still need to close. And that’s exactly why it’s important.

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination | Nature Methods nature.com/articles/s41592-0…

Hard to think of a better image of how blindly humanity is heading into climate breakdown

On the train to Heidelberg for the @EMBO workshop #computational_structural_biology, excited to hear about the latest developments in the field and share some recent work!

I love the ritual of putting on a pot of coffee if you and me are ever in an 80s sci-fi thriller where we have to pull an all-nighter to decode a message from aliens I will be the guy who puts on the pot of coffee

Utrecht 2025

I would say my biggest takesway from spending the last 8 months singlemindedly studying bioML is that understanding the biology actually is important