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Congratulations to this year’s #CASP15 winners and participants for their achievements! 🧬 In the two years since #CASP14, we’ve been excited to see the advances being made in predicting protein structures, building on #AlphaFold and bringing in new ideas.

A pleasure and a privilege to be assessor again at #CASP15. A mix of spectacular success and the occasional intriguing failure. Looking forward to hearing from the predictors and discussing future directions. Thanks @AJSimpkin Ronan Keegan Shah Mes David L Murphy Filo and Luc.

Pleased to say @DeepMind has just released a code update to #AlphaFold 2. This includes updated model weights trained on newer data, minor changes to the codebase to inference larger proteins and predictions for the #CASP15 targets. Find out more: github.com/deepmind/alpha…

Standing room only for a really nice talk from Kathryn Tunyasuvunakool of @DeepMind at #BPS2023. Seems the model is getting very good for multimer structures, exciting times! #alphafold

Wonderful talk by Kathryn Tunyasuvunakool on AlphaFold including updates with Multimer at #BPS2023 that are now available. In short 1) trained on more data to include lots more CryoEM data 2) support for up to 20 chain prediction 3) lots of additional tricks (more recycling, etc)

Wow, #AlphaFold 2.3 is producing great results on protein complexes that did not work in 2.1 or 2.2. Previously we would get proteins or peptides not bound at all, or poor iPTM scores & inconsistent results from models 1-5. Now on several systems we get results that make sense.

So happy to see our work going live together with that of Pedro Beltrao and @thesteinegger today @nature! Biozentrum, University of Basel Universität Basel SIB SWISS-MODEL link: nature.com/articles/s4158… link: nature.com/articles/s4158…

#CCP4SW 2024 will be running from 3-5 January 2024 at @nottsvenues . This year's topic is "Decision making in MX - how to be a productive structural biologist". Registration will open soon!!

Today in partnership with Isomorphic Labs, we're sharing progress on the next generation of #AlphaFold. 🧬 Our new model greatly expands coverage of structure prediction beyond proteins to other key biomolecular classes. How could it help scientists? 🧵 dpmd.ai/alphafold-prog…

One of the projects I was working on last months :)

The most exciting project I was working on as a part of the incredible team - mostly focusing on the Server :)

We love the excitement & results from the community on AlphaFold 3 and are doubling the AF Server daily job limit to 20. Happy to also share that we're working on releasing the AF3 model (incl weights) for academic use, which doesn’t depend on our research infra, within 6 months.

To help scientists explore whether a genetic variant is likely pathogenic, and which regions of proteins are functionally important, we've integrated AlphaMissense data by Google DeepMind into Ensembl, UniProt & the AlphaFold database. ebi.ac.uk/about/news/tec…

Want to learn how AlphaMissense analyses missense variants & predicts their potential pathogenicity? Join Google DeepMind & EMBL-EBI next week's webinar to dive in! We'll also explore how this data is used in EMBL-EBI resources 👇🏽

Scientists from 120 countries have now used #AlphaFold Server to complete more than 620,000 jobs - to help test multiple hypotheses, predict complex interactions between proteins and DNA, and more. 🔬 Find out more in nature ↓ nature.com/nature/volumes…

Huge congratulations to @DemisHassabis and John Jumper on being awarded the 2024 Nobel Prize in Chemistry for protein structure prediction with #AlphaFold, along with David Baker for computational protein design. This is a monumental achievement for AI, for computational

The #AlphaFold 3 model code and weights are now available for academic use. We Google DeepMind are excited to see how the research community continues to use AlphaFold to address open questions in biology and new lines of research. github.com/google-deepmin…