Today, we're announcing SAbDab2! In brief: - clean, pre-processed antibody structure data for ML with standardised train/test splits - massive improvements in structure organisation and annotation consistency - support for VNARs and antibody construct annotation - more structures than ever before

New OpenFold3 preview out! (OF3p2) It closes the gap to AlphaFold3 for most modalities. Most critically, we're releasing everything, including training sets & configs, making OF3p2 the only current AF3-based model that is functionally trainable & reproducible from scratch🧵1/9

I’m excited to share my first peer-reviewed publication, and my first first-author paper, "Time in mind: a multidisciplinary review on temporal perception, cognition, and memory" is now published open access in Frontiers in Cognition! www.frontiersin.org/journals/cog... #psychology #science #time

Frontiers | Time in mind: a multidisciplinary review on temporal perception, cognition, and memory

This review examines temporal cognition through the lens of Mental Time Travel (MTT): the subjective experience of recalling past events and using them to co...

frontiersin.org

Predicting protein conformational flexibility remains a major challenge in structural biology. While we can now accurately model static protein structures, understanding their dynamics is still difficult, largely due to a lack of suitable training data.

It’s an exciting time in protein design! 🧬✨ But much of the therapeutic potential—especially for antibodies—remains untapped. Why? 🤔 Antibodies seem like ideal candidates for design! 💉 Here’s a quick thread summarising our new review paper on the state of antibody structure prediction. 👇 1/

Challenges and compromises: Predicting unbound antibody structures with deep learning

Therapeutic antibodies are manufactured, stored and administered in the free state; this makes understanding the unbound form key to designing and imp…

sciencedirect.com