Friday, October 07, 2022

AI predicts structure of almost all known proteins

AlphaFold, a new system artificial intelligence (AI) of GooglePredicts the structure of nearly all proteins known and cataloged by science, which will enhance the understanding of biology and facilitate the work of many researchers to address current and future challenges.

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

The database has expanded nearly 200 times since its creation in 2021, from nearly one million protein structures to more than 200 million in its latest version, and includes nearly every organism on Earth whose genome has been sequenced. has gone. A statement from EMBL reports today.

This extension 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 on global challenges, such as sustainability, food insecurity and neglected diseases”,

Proteins have a unique three-dimensional shape that allows them to fit into each other, but determining this is a major challenge and here is where AI is important: its use made it possible to create the most complete database of predictions. That’s how they twist.

Fundamentals of life, the structure of each protein, which depends on the amino acids that make up it, defines what it does and how it does so, so determining it is important for understanding biological processes and advancing in various fields. Provides valuable information for

“Alphafold Now Offers a Three-Dimensional View of the Universe of Proteins”Emphasizes EMBL CEO Edith Hurd, who says: “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 closely related to Google’s parent company, Alphabet, highlights “The speed at which AlphaFold has already become an essential tool for hundreds of thousands of scientists in laboratories and universities around the world”,

Hasabis hopes that this expanded database will open entirely new avenues of scientific discovery.

According to EMBL, AlphaFold has also shown its impact in areas such as improving the ability to fight plastic pollution, understanding Parkinson’s, enhancing the health of bees, exploring how ice is made, or human evolution.

“We launched AlphaFold in the hope that other teams can learn from and build on the advances we have made, and it is exciting to see this happen so quickly”John Jumper, AlphaFold scientist and leader at DeepMind.

It is – he underlines- “A new era of more AI-based methods in structural biology is going to drive incredible progress”,

For Samir Velankar, Team Leader of the EMBL-EBI Protein Data Bank in Europe, AlphaFold has spread across the molecular biology community: “In the last year alone, over a thousand scientific articles have been published on a wide range of research topics using alphafold structures”,

“This is just the effect of a million predictions; “Imagine the impact of more than 200 million openly accessible protein structure predictions”.wishes.

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