Science and Nature consider the prediction of protein folding with artificial intelligence to be the scientific breakthrough of 2021. We spoke to two experts about the opportunities and limitations of this ‘giant leap forward’.

One day it will be possible to predict the three-dimensional structure of a protein solely on the basis of its amino acid sequence, predicted biochemist and protein structure expert Christian Anfinsen in his acceptance speech for the 1972 Nobel Prize. Almost fifty years later this prophecy is fulfilled: last year, developers managed to predict protein folding almost perfectly using artificial intelligence (AI).

Previously, determining protein structures required labor-intensive analyses in the lab. Everything changed in July 2021, when the Google DeepMind team published their AlphaFold method in Nature. Shortly thereafter, the Baker Laboratory at the University of Washington (Seattle) followed with their similar method RoseTTAfold in Science. Both methods use a deep learning algorithm and can calculate protein structures relatively quickly and easily. The DeepMind team has since applied AlphaFold to several complete genomes, including that of humans. They predicted the structure of almost every protein in the human body and the nearly complete proteomes of twenty other organisms, including the mouse, fruit fly and Baker’s yeast (Saccharomyces cerevisiae).