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       Google DeepMind's Groundbreaking AI for Protein Structure Can Now
       Model DNA
        
 (HTM) Source
        
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       Google spent much of the past year hustling to build its Gemini
       chatbot to counter ChatGPT, pitching it as a multifunctional AI
       assistant that can help with work tasks or the digital chores of
       personal life. More quietly, the company has been working to enhance a
       more specialized artificial intelligence tool that is already a must-
       have for some scientists.
        
       AlphaFold, software developed by Google's DeepMind AI unit to predict
       the 3D structure of proteins, has received a significant upgrade. It
       can now model other molecules of biological importance, including DNA,
       and the interactions between antibodies produced by the immune system
       and the molecules of disease organisms. DeepMind added those new
       capabilities to AlphaFold 3 in part through borrowing techniques from
       AI image generators.
        
       "This is a big advance for us," Demis Hassabis, CEO of Google
       DeepMind, told WIRED ahead of Wednesday's publication of a paper on
       AlphaFold 3 in the science journal _Nature_. "This is exactly what you
       need for drug discovery: You need to see how a small molecule is going
       to bind to a drug, how strongly, and also what else it might bind to."
        
       AlphaFold 3 can model large molecules such as DNA and RNA, which carry
       genetic code, but also much smaller entities, including metal ions. It
       can predict with high accuracy how these different molecules will
       interact with one another, Google's research paper claims.
        
       The software was developed by Google DeepMind and Isomorphic labs, a
       sibling company under parent Alphabet working on AI for biotech that
       is also led by Hassabis. In January, Isomorphic Labs announced that it
       would work with Eli Lilly and Novartis on drug development.
        
       AlphaFold 3 will be made available via the cloud for outside
       researchers to access for free, but DeepMind is not releasing the
       software as open source the way it did for earlier versions of
       AlphaFold. John Jumper, who leads the Google DeepMind team working on
       the software, says it could help provide a deeper understanding of how
       proteins interact and work with DNA inside the body. "How do proteins
       respond to DNA damage; how do they find, repair it?" Jumper says. "We
       can start to answer these questions."
        
       Understanding protein structures used to require painstaking work
       using electron microscopes and a technique called x-ray
       crystallography. Several years ago, academic research groups began
       testing whether deep learning, the technique at the heart of many
       recent AI advances, could predict the shape of proteins simply from
       their constituent amino acids, by learning from structures that had
       been experimentally verified.
        
       In 2018, Google DeepMind revealed it was working on AI software called
       AlphaFold to accurately predict the shape of proteins. In 2020,
       AlphaFold 2 produced results accurate enough to set off a storm of
       excitement in molecular biology. A year later, the company released an
       open source version of AlphaFold for anyone to use, along with 350,000
       predicted protein structures, including for almost every protein known
       to exist in the human body. In 2022 the company released more than 2
       million protein structures.
        
        
        
        
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