The AI ​​group claims to have solved one of biology’s “great challenges”

The AI ​​group claims to have solved one of biology’s “great challenges”

The AI ​​group claims to have solved one of biology’s “great challenges”

An artificial intelligence group says its program has successfully predicted the structure of nearly every protein known to science, effectively solving one of biology’s “great challenges” and paving the way for new discoveries and technologies in fields as diverse as medicine, food security and climate science.

DeepMind, an artificial intelligence company owned by Google’s parent company Alphabet, announced Thursday that its AlphaFold program has expanded its open online database to include more than 200 million protein structures.

The vast catalog now encompasses “the entire protein universe,” DeepMind CEO Demis Hassabis said in a news briefing, from the sequenced genomes of nearly every organism on the planet.

Proteins are long and complex chains of amino acids that make up the building blocks of life. Scientists have long sought to unravel how these chains are elegantly twisted and folded into 3D shapes because understanding their structure can provide valuable insights into their function. Knowing the specific shape of a protein and how its various molecules interact can, for example, help researchers narrow down potential targets for medical treatment.

AlphaFold's prediction for the structure of the F20H23.2 protein.  (deep mind)

AlphaFold’s prediction for the structure of the F20H23.2 protein. (deep mind)

AlphaFold’s updated database includes protein structures for plants, bacteria, animals and other organisms, according to DeepMind.

These updates offer “new opportunities for researchers to use AlphaFold to advance their work on important issues, including sustainability, food insecurity and neglected diseases,” Hassabis wrote in a blog post published Thursday on the milestone. .

“By proving that AI could accurately predict the shape of a protein down to atomic precision, on a large scale and in minutes, AlphaFold not only provided a solution to a great 50-year challenge, but also became the first major. proof point of our founding thesis: that artificial intelligence can greatly accelerate scientific discovery and, in turn, advance humanity, “he wrote.

AlphaFold was introduced in 2020, and DeepMind wowed the scientific community last year by unveiling a catalog of structures that included virtually every protein in the human body. The so-called AlphaFold protein structure database, developed in collaboration with the European Molecular Biology Laboratory, included hundreds of thousands of newly predicted protein structures.

According to Hassabis, the rich hoard of information is already being used by researchers around the world to study topics ranging from antibiotic resistance to plastic pollution.

Researchers at the University of Portsmouth in the UK, for example, announced in July 2021 that they are using the database to help design enzymes for recycling certain types of single-use plastics.

“AlphaFold provides us with an exciting new model library to design faster, more stable and cost-effective enzymes for plastic recycling,” said John McGeehan, director of the University of Portsmouth’s Center for Enzyme Innovation, in a statement at the time.

Hassabis said DeepMind is working to further expand its database, with particular emphasis on applications related to drug development, fundamental biology research, climate science, quantum chemistry and fusion.

“AlphaFold is a glimpse into the future,” he wrote, “and what might be possible with computational and artificial intelligence methods applied to biology.”

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