ΑΙhub.org
 

DeepMind and EMBL release database of predicted protein structures


by
23 July 2021



share this:

AF-Q8I3H7-F1
T-cell immunomodulatory protein homolog, from the AlphaFold Protein Structure Database, reproduced under a CC-BY-4.0 license.

DeepMind and the European Molecular Biology Laboratory (EMBL) have partnered to produce a database of predicted protein structure models.

The first release covers all ~20,000 proteins expressed in the human proteome, and the proteomes of 20 other biologically significant organisms, totalling over 350k structures. In the coming months they plan to expand the database to cover a large proportion of all catalogued proteins (the over 100 million in UniRef90).

The data is freely and openly available to the scientific community. You can access the AlphaFold Protein Structure Database here.

Back in November, DeepMind reported on their AlphaFold system that was able to predict, with high accuracy, a protein’s 3D structure from its amino acid sequence. We wrote about it here. This database is the next step in the journey, and the collaborators hope that this will be a useful tool for researchers and open up new avenues for scientific discovery.


Another example protein structure from the AlphaFold Protein Structure Database, reproduced under a CC-BY-4.0 license. This is Striatin-interacting protein 1. It plays a role in the regulation of cell morphology and cytoskeletal organization, required in the cortical actin filament dynamics and cell shape. AlphaFold produces a per-residue confidence score (pLDDT) between 0 and 100. The parts of the protein with a pLDDT score of above 90 are shown in dark blue, between 70 and 90 in light blue, between 50 and 70 in yellow, and below 50 in red.

In a recently published Nature article, Highly accurate protein structure prediction with AlphaFold, you can find out more about the neural network-based model and methodology that the AlphaFold team used. In this second Nature article, Highly accurate protein structure prediction for the human proteome, published yesterday, you can read more about the application of AlphaFold to the human proteome.

Find out more

AlphaFold Protein Structure Database
DeepMind blog post
EMBL-EBI news article
Highly accurate protein structure prediction with AlphaFold, Nature article.
Highly accurate protein structure prediction for the human proteome, Nature article.
DeepMind open source code
AlphaFold Colab



tags:


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

AI for Science – from cosmology to chemistry

  01 May 2026
How AI is transforming science, from a day conference at the Royal Society
monthly digest

AIhub monthly digest: April 2026 – machine learning for particle physics, AI Index Report, and table tennis

  30 Apr 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

The Machine Ethics podcast: organoid computing with Dr Ewelina Kurtys

In this episode, Ben chats to Ewelina about the uses of organoids and energy saving computing, differences between biological neurons and digital neural networks, and much more.

#AAAI2026 invited talk: Yolanda Gil on improving workflows with AI

  28 Apr 2026
Former AAAI president on using AI to help communities of scientists better streamline their research.

Maryna Viazovska’s proofs of sphere packing formalized with AI

  27 Apr 2026
Formalization achieved through a collaboration between mathematicians and artificial intelligence tools.

Interview with Deepika Vemuri: interpretability and concept-based learning

  24 Apr 2026
Find out more about Deepika's research bridging the gap between data-driven models and symbolic learning.

As a ‘book scientist’ I work with microscopes, imaging technologies and AI to preserve ancient texts

  23 Apr 2026
Using an array of technologies to recover, understand and preserve many valuable ancient texts.

Sony AI table tennis robot outplays elite human players

  22 Apr 2026
New robot and AI system has beaten professional and elite table tennis players.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence