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  • TECHNOLOGY FEATURE

Artificial intelligence powers protein-folding predictions

Deep-learning algorithms such as AlphaFold2 and RoseTTAFold can now predict a protein’s 3D shape from its linear sequence — a huge boon to structural biologists.
  1. Michael Eisenstein

    1. Michael Eisenstein is a freelance writer in Philadelphia, Pennsylvania.

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Three dimensional structure of the ring-shaped human nuclear pore complex modelled using AlphaFold

A model of the human nuclear pore complex, built using AlphaFold2 and structural data. Credit: Agnieszka Obarska-Kosinska

Rarely does scientific software spark such sensational headlines. “One of biology’s biggest mysteries ‘largely solved’ by AI”, declared the BBC. Forbes called it “the most important achievement in AI — ever”. The buzz over the November 2020 debut of AlphaFold2, Google DeepMind’s artificial-intelligence (AI) system for predicting the 3D structure of proteins, has only intensified since the tool was made freely available in July.

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Nature 599, 706-708 (2021)

doi: https://doi.org/10.1038/d41586-021-03499-y

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