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Inside each cell, thousands of different proteins from the mechanism that keeps all living things – from humans and plants to microscopic bacteria – alive and well. Almost all diseases, including cancer, dementia, and even infectious diseases such as COVID-19, are related to how these proteins work.
Because the function of each protein is directly related to its three-dimensional shape, scientists around the world have been working for half a century to find an accurate and fast method that would allow them to discover the shape of any protein.
Today (Monday) researchers from the 14th Community-wide Experiment on Critical Evaluation of Protein Structure Prediction Techniques (CASP14) will announce that an artificial intelligence (AI) solution has been found to the challenge.
Based on the work of hundreds of researchers around the world, an artificial intelligence program called AlphaFold, created by the London-based DeepMind artificial intelligence lab, has been shown to determine the shape of many proteins. It did so to a level of accuracy comparable to that obtained with expensive and time-consuming laboratory experiments.
CASP14 is organized by Dr. John Moult (president), University of Maryland, USA; Dr. Krzysztof Fidelis, UC Davis, USA; Dr. Andriy Kryshtafovych, UC Davis, USA; Dr. Torsten Schwede, University of Basel and SIB Swiss Institute of Bioinformatics, Switzerland; and Dr Maya Topf, Birkbeck, University of London, UK and CSSB (HPI and UKE) Hamburg, Germany.
Proteins are extremely complicated molecules and their precise three-dimensional structure is crucial for the many roles they play, such as insulin which regulates our blood sugar levels and antibodies which help us fight infections. Even small rearrangements of these vital molecules can have catastrophic effects on our health, so one of the most effective ways to understand the disease and find new treatments is to study the proteins involved. “
Dr. John Moult, President, Community Level Experiment on Critical Evaluation of Techniques for Protein Structure Prediction
“There are tens of thousands of human proteins and many billions in other species, including bacteria and viruses, but processing the shape of just one requires expensive equipment and can take years.
“Almost 50 years ago, Christian Anfinsen was awarded the Nobel Prize for showing that it should be possible to determine the shape of proteins based on their sequence of amino acids, the individual building blocks that make up proteins. That’s why our community. of scientists has been working on the biennial CASP challenge. “
Teams taking part in the CASP challenge receive amino acid sequences for a set of approximately 100 proteins. As scientists study proteins in the lab to determine their shape experimentally, around 100 participating CASP teams from more than 20 countries will try to do the same thing using computers. The results are evaluated by independent scientists.
Dr. Fidelis said: “The CASP approach has created intense collaboration between researchers working in this field of science and we have seen how it has accelerated scientific developments.
“Since we first faced the challenge in 1994, we have seen a number of discoveries, each solving one aspect of this problem, so that calculated models of protein structures have become progressively more useful in medical research.”
During the final round of the challenge, DeepMind’s AlphaFold program determined the shape of approximately two-thirds of the proteins with precision comparable to laboratory experiments *. The accuracy of AlphaFold with most other proteins was also high, although not quite at that level.
CASP organizers say this success is based on the results achieved in previous CASP rounds, both by the DeepMind team and other participants, and that other teams taking part in CASP14 have also produced some highly accurate structures during this round.
Dr Kryshtafovych said: “What AlphaFold has achieved is truly remarkable and today’s announcement is a win for DeepMind, but it is also a triumph for the team’s science. The unique and intense way we collaborate with researchers from around the world through CASP and the contribution of many teams of scientists over the years have led us to this breakthrough. “
He adds: “Being able to investigate the shape of proteins quickly and accurately has the potential to revolutionize the life sciences. Now that the problem has been largely solved for individual proteins, the way is open for the development of new methods for determining the shape of complex proteins: collections of proteins that work together to form most of the mechanisms of life and for other applications “.
Professor Dame Janet Thornton, emeritus director of EMBL’s European Bioinformatics Institute (EMBL-EBI), which is not affiliated with CASP or DeepMind, said: “One of the biggest mysteries in biology is how proteins fit together. they fold to create exquisitely unique three-dimensional structures.Every living thing – from the smallest bacteria to plants, animals and humans – is defined and powered by proteins that help it function at the molecular level.
“So far, this mystery has remained unsolved and the determination of a single protein structure has often required years of experimental effort. It is extraordinary to see the triumph of human curiosity, commitment and intelligence in solving this problem. A better understanding of the structures. and the ability to predict using a computer means a better understanding of life, evolution and, of course, human health and disease. “
Source:
Community-wide experiment on the critical evaluation of techniques for protein structure prediction
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