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Article: DeepMind AI breakthrough helps solve how diseases invade cells by predicting protein structures

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7 / 10

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Google's AI unit, DeepMind, has made a major breakthrough by developing an AI system called AlphaFold that can accurately predict the 3D structures of proteins. This achievement was recognized at a prestigious scientific competition, solving a critical biological problem likened in importance to mapping the human genome.

Understanding protein structure is vital for biological research, including studying how diseases like Covid-19 invade cells, designing enzymes, and improving agriculture. DeepMind aims to apply its advanced AI to complex scientific challenges, having previously used it for tasks like improving energy efficiency and medical diagnostics.

Main topics: DeepMind's AlphaFold AI, protein structure prediction, implications for disease research and biotechnology.

Original URL

https://www.scmp.com/tech/science-research/article/3112026/deepmind-ai-breakthrough-helps-solve-how-diseases-invade?utm_source=rss_feed

Source Feed

Science & Research - South China Morning Post

Published Date

2020-12-01 01:52

Fetched Date

2026-03-04 14:31

Processed Date

2026-03-04 15:15

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Present

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DeepMind AI breakthrough helps solve how diseases invade cells by predicting protein structures
- Google’s artificial intelligence unit takes a giant step to predict the structure of proteins
- Understanding how proteins will interact with other molecules has implications for research on new diseases like Covid-19
2-MIN READ2-MIN
Google’s artificial intelligence unit took a giant step to predict the structure of proteins, potentially decoding a problem that has been described as akin to mapping the genome.
DeepMind Technologies’ AlphaFold reached the threshold for “solving” the problem at the latest Critical Assessment of Structure Prediction competition. The event started in 1994 and is held every two years to accelerate research on the topic.
Different folds in a protein determine how it will interact with other molecules, and understanding them has implications for discovering how new diseases like Covid-19 invade our cells, designing enzymes to break down pollutants and improving crop yields.
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DeepMind became a subsidiary of Google after a 2014 acquisition and is best known for its gamer AI, teaching itself to beat Atari video games and defeating world-renowned Go players like Lee Sedol. The company’s ambition has been to develop AI that can be applied to broader problems, and it has so far created systems to make Google’s data centres more energy efficient, identify eye disease from scans and generate human-sounding speech.
DeepMind also won the competition in 2018 at the first time of entering, when it accurately predicted the structure of 25 out of 43 proteins.
“These algorithms are now becoming strong enough and powerful enough to be applicable to scientific problems,” DeepMind Chief Executive Officer Demis Hassabis said in a call with reporters. After four years of development “we have a system that’s accurate enough to actually have biological significance and relevance for biological researchers.”
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