A Google artificial intelligence system predicts the structure of almost all known proteins

AlphaFold, an artificial intelligence (AI) system from Google, predicts the structure of nearly every protein known and cataloged by science, which will increase understanding of biology and make it easier for many researchers to meet today’s challenges and future.

DeepMind, responsible for this artificial intelligence, and the European Institute of Bioinformatics of the European Molecular Biology Laboratory (EMBL-EBI) have made, thanks to AI, predictions of the three-dimensional structure of almost all proteins —200 million— from its amino acid sequence; these are freely and openly available in the AlphaFold database.

This database has been expanded approximately 200 times since its inception in 2021, growing from nearly a million protein structures to over 200 million in its latest version, and encompasses nearly every organism on Earth whose genome has been sequenced. , according to reports today a statement from the EMBL.

This expansion includes predicted structures for a wide range of species, including plants, bacteria, animals and other organisms, “opening new avenues of research in the life sciences that will impact the challenges issues such as sustainability, food insecurity and neglected diseases.

Proteins have a unique three-dimensional shape that causes them to fit together, but determining it is a big challenge and here AI is key: its use has created the most comprehensive database of predictions about how they fold.

Fundamental pieces of life, the structure of each protein, which depends on the amino acids that compose it, defines what it does and how it does it, thus its determination provides valuable information for understanding biological processes and progress in various fields .

“AlphaFold now offers a three-dimensional view of the world of proteins,” says Edith Heard, Managing Director of the EMBLwho adds: “The popularity and growth of this database is a testament to the success of the collaboration between DeepMind and EMBL.”

For his part, Demis Hassabis, founder and CEO of DeepMind, a British firm belonging to Alphabet, the parent company of Google, underlines “the speed at which AlphaFold has already become an indispensable tool for hundreds of thousands of scientists in laboratories and universities around the world. world”.

Hassabis hopes this expanded database will open up whole new avenues of scientific discovery.

According to EMBL, AlphaFold has also shown impact in areas such as improving the ability to tackle plastic pollution, understanding Parkinson’s disease, improving bee health, understanding the ice formation or the exploration of human evolution.

“We started AlphaFold hoping that other teams could learn and build on the progress we’ve made, and it was exciting to see this happen so quickly,” said AlphaFold lead scientist John Jumper. at DeepMind.

This is, he points out, “a new era in structural biology and AI-based methods will drive incredible progress.”

For Sameer Velankar, Team Leader of the EMBL-EBI Protein Database in Europe, AlphaFold has spread through the molecular biology community: “In the last year alone, more than a thousand ‘scientific articles have been published on a wide range of research topics using AlphaFold structures’.

“That’s just the impact of one million predictions; imagine the impact of having over 200 million freely accessible protein structure predictions.

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