Proteins tend to adopt their shape without help, guided only by the laws of physics.įor decades, laboratory experiments have been the main way to get good protein structures. How a protein works and what it does is determined by its 3D shape - ‘structure is function’ is an axiom of molecular biology.
Proteins are the building blocks of life, responsible for most of what happens inside cells. AlphaFold might not obviate the need for these laborious and expensive methods - yet - say scientists, but the AI will make it possible to study living things in new ways. In some cases, AlphaFold’s structure predictions were indistinguishable from those determined using ‘gold standard’ experimental methods such as X-ray crystallography and, in recent years, cryo-electron microscopy (cryo-EM). AlphaFold has already helped him find the structure of a protein that has vexed his lab for a decade, and he expects it will alter how he works and the questions he tackles. “It’s a game changer,” says Andrei Lupas, an evolutionary biologist at the Max Planck Institute for Developmental Biology in Tübingen, Germany, who assessed the performance of different teams in CASP. But, this year, the outfit’s deep-learning network was head-and-shoulders above other teams and, say scientists, performed so mind-bogglingly well that it could herald a revolution in biology. It would vastly accelerate efforts to understand the building blocks of cells and enable quicker and more advanced drug discovery.ĪlphaFold came top of the table at the last CASP - in 2018, the first year that London-based DeepMind participated.
The ability to accurately predict protein structures from their amino-acid sequence would be a huge boon to life sciences and medicine. “In some sense the problem is solved.”ĪI protein-folding algorithms solve structures faster than ever “This is a big deal,” says John Moult, a computational biologist at the University of Maryland in College Park, who co-founded CASP in 1994 to improve computational methods for accurately predicting protein structures. The results were announced on 30 November, at the start of the conference - held virtually this year - that takes stock of the exercise. Credit: DeepMindĪn artificial intelligence (AI) network developed by Google AI offshoot DeepMind has made a gargantuan leap in solving one of biology’s grandest challenges - determining a protein’s 3D shape from its amino-acid sequence.ĭeepMind’s program, called AlphaFold, outperformed around 100 other teams in a biennial protein-structure prediction challenge called CASP, short for Critical Assessment of Structure Prediction. Our service is meant to provide convenience and piece of mind even used as an every day or reoccurring help.A protein’s function is determined by its 3D shape. GIGANTIC can most certainly assist handicap individuals and the elderly become more independent without having to deal with everyday obstacles and predicaments. As long as it is NOT requiring a professional or a handyman, you can get help through GIGANTIC. People in the community will make money while helping each other, getting to know each other and caring about each other.Īll families, individuals and businesses will need help with chores, tasks and little jobs regardless of location, be it around the house, inside, outside, at work, etc.
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