DeepMind’s AI has finally shown how useful it can be

"Marcelo Sousa, a biochemist at the University of Colorado Boulder, had spent ten years trying to crack a particularly tricky puzzle. Sousa and his team had collected reams of experimental data on a single bacterial protein linked to antibiotic resistance. Working out its structure, they hoped, would help to find inhibitors that could stop that resistance from building. But, year after year, the puzzle remained unsolved. Then along came AlphaFold. Within 15 minutes, DeepMind’s machine learning system had solved the structure.

It’s the kind of result that could soon be repeated in labs across the world. In a paper published in the journal Nature, DeepMind has released over 350,000 predicted protein structures. Included in that is almost the entirety of the human proteome, the proteins that make up the human body. Within these predicted structures could lie key insights into diseases such as cancer and Alzheimer’s, the possibility of new drugs and even better ways to recycle plastic.

To put that number into context, the Universal Protein database, a collection of all the proteins that science has uncovered thus far, contains over 180 million protein sequences. These protein sequences tell us how the amino acids in a protein are ordered, but that’s only the beginning of the puzzle. To really understand how proteins function in the body, we need to know how that sequence determines the 3D structure of the protein – and that is a much more difficult task than simply knowing the right order of amino acids..." Lire la suite