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Google DeepMind unveils next generation of drug discovery AI model- ‘AlphaFold 3’

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Google DeepMind unveils next generation of drug discovery AI model- ‘AlphaFold 3’

in Technology, world
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Google DeepMind unveils next generation of drug discovery AI model- ‘AlphaFold 3’
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DBT Bureau

Bengaluru, 8 May

Google Deepmind in collaboration with its subsidiary Isomorphic Labs has unveiled the third major version of its “AlphaFold” artificial intelligence model- AlphaGold3, that will help scientists to design drugs and target disease more effectively.

“Thrilled to announce AlphaFold 3 which can predict the structures and interactions of nearly all of life’s molecules with state-of-the-art accuracy including proteins, DNA, and RNA. Biology is a complex dynamical system so modelling interactions is crucial,” said Demis Hassabis, Cofounder & CEO of Google DeepMind.

In a paper published in Nature, the company introduced AlphaFold 3, which is considered a revolutionary model that can predict the structure and interactions of all life’s molecules with better accuracy.

According to DeepMind, the new AI model would reduce the time and money needed to develop potentially life-changing treatments.

The company also announced the release of the “AlphaFold server”, a free online tool that scientists can use to test their hypotheses before running real-world tests.

“Google DeepMind’s newly launched AlphaFold Server is the most accurate tool in the world for predicting how proteins interact with other molecules throughout the cell. It is a free platform that scientists around the world can use for non-commercial research. With just a few clicks, biologists can harness the power of AlphaFold 3 to model structures composed of proteins, DNA, RNA, and a selection of ligands, ions, and chemical modifications,” the company said in Nature magazine.

Since 2021, AlphaFold’s predictions have been freely accessible to researchers, that has complemented research in healthcare and drug discovery spaces.

AlphaFold revolutionised computational biology by accurately predicting 3D protein structures from amino acid sequences, transforming research and drug discovery.

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