{"id":78875,"date":"2026-03-16T21:27:11","date_gmt":"2026-03-16T20:27:11","guid":{"rendered":"https:\/\/www.embl.org\/news\/?p=78875"},"modified":"2026-03-23T17:40:21","modified_gmt":"2026-03-23T16:40:21","slug":"first-complexes-alphafold-database","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/science-technology\/first-complexes-alphafold-database\/","title":{"rendered":"Millions of protein complexes added to AlphaFold Database shed light on how proteins interact"},"content":{"rendered":"\n

A new collaboration between EMBL\u2019s European Bioinformatics Institute (EMBL-EBI), Google DeepMind, NVIDIA, and Seoul National University has made millions of AI-predicted protein complex structures openly available through the AlphaFold Database<\/a>. To maximise global health impact, the dataset prioritises proteins important for understanding human health and disease. This is the largest dataset of protein complex predictions currently available.<\/p>\n\n\n\n

Proteins are the building blocks of life. They interact to create protein complexes which fulfil biological functions. By visualising protein interactions, scientists can uncover the molecular mechanisms that drive cell behaviour, identify what goes wrong when someone gets sick, and develop new drugs and therapies. Predicting the structure of protein complexes is extremely challenging because, in nature, proteins change shape and interact in many different ways. <\/p>\n\n\n\n

\u201cScience thrives on collaboration,\u201d said Jo McEntyre, Interim Director of EMBL-EBI<\/a>. \u201cBy making this foundational protein complex dataset openly available to the world, we\u2019re inviting researchers to test, refine, and build on it to drive the next wave of biological discoveries.\u201d<\/p>\n\n\n\n

Protein complexes for global health impact<\/strong><\/h2>\n\n\n\n

The latest AlphaFold Database update spans millions of homodimers \u2013 protein complexes formed of two identical proteins. It focuses on 20 of the most studied species<\/a>, including humans, as well as the World Health Organization\u2019s priority pathogens list<\/a>. This approach aims to bring significant and immediate value for global health challenges.<\/p>\n\n\n\n

\u201cBy expanding the AlphaFold Database to include protein complexes, we are addressing a critical need expressed by the scientific community,\u201d said Anna Koivuniemi, Head of the Google DeepMind Impact Accelerator. \u201cWe hope that by lowering the barrier to these complex predictions, we can empower researchers everywhere to pursue the next wave of discoveries that could ultimately improve human health on a global scale.\u201d<\/p>\n\n\n\n

Scientific expertise meets technical innovation<\/strong><\/h2>\n\n\n\n

The collaboration builds on Google DeepMind\u2019s AI system AlphaFold, which, since 2021, accurately predicted the structure of millions of proteins. To democratise access to AlphaFold predictions, Google DeepMind and EMBL-EBI developed the AlphaFold Database, an open resource that anyone can access. The database has over 3.4 million users from 190 countries. <\/p>\n\n\n\n

Through ongoing dialogue with the scientific community, a clear need emerged to expand the AlphaFold database to include protein complexes. In response to this need, EMBL-EBI, Google DeepMind, NVIDIA, and Seoul National University teamed up, contributing specialist expertise and resources, to calculate and integrate millions of protein complexes into the AlphaFold Database. <\/p>\n\n\n\n

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\n “By making this foundational dataset openly available to the world, we\u2019re inviting researchers to test, refine, and build on it to drive the next wave of biological discoveries.” <\/div>\n \n