wynalazki: Google DeepMind

Evidence: 89 • authority: 88

No, DeepMind has not solved protein folding. <em> (Please note that this post was updated on 12th Dec 2020 – see below) </em> This week DeepMind has announced that, using artificial intelligence (AI), it has solved the 50-year old problem of 'protein folding'. The announcement was made as the results were released from the 14 ^th and latest competition on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14). The competition pits teams of computational

Evidence: 89 • authority: 88

No, DeepMind has not solved protein folding. <em> (Please note that this post was updated on 12th Dec 2020 – see below) </em> This week DeepMind has announced that, using artificial intelligence (AI), it has solved the 50-year old problem of 'protein folding'. The announcement was made as the results were released from the 14 ^th and latest competition on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14). The competition pits teams of computational

Evidence: 53 • authority: 92

From CASP13 to the Nobel Prize: DeepMind's AlphaFold Journey in Revolutionizing Protein Structure Prediction and Beyond.. Four years ago, at the 14th Critical Assessment of Structure Prediction (CASP14), John Moult made a historic announcement that the long-standing challenge of Protein Structure Prediction- a problem that had confounded scientists for over five decades-had been "solved" for single protein chains. Supporting this groundbreaking statement was a plot depicting the median Global Distance Test (GDT) across 87 out of 92 domains, where AlphaFold2, developed by DeepMind, achieved an unprecedented score of 92.4. The bar chart not only underscored AlphaFold2' s remarkable performanc…

Evidence: 52 • authority: 72

AlphaFold is an artificial intelligence (AI) program developed by DeepMind, a subsidiary of Alphabet, which performs predictions of protein structure. It is designed using deep learning techniques. AlphaFold 1 (2018) placed first in the overall rankings of the 13th Critical Assessment of Structure Prediction (CASP) in December 2018. It was particularly successful at predicting the most accurate structures for targets rated as most difficult by the competition organizers, where no existing template structures were available from proteins with partially similar sequences. AlphaFold 2 (2020) repeated this placement in the CASP14 competition in November 2020. It achieved a level of accuracy muc…

Evidence: 40 • authority: 92

AlphaFold and the Transformation of Structural Biology: Evolution, Applications, Limitations, and Future Directions. The protein folding problem is the challenge of predicting a protein's three-dimensional structure from its amino acid sequence. This problem has been a central challenge in molecular biology for over fifty years. The advent of AlphaFold, a deep learning system developed by DeepMind, represented a paradigm shift in structural biology by demonstrating near-experimental accuracy in protein structure prediction. This review traces the evolution of the AlphaFold family of models, from its breakthrough performance in CASP14 through the expanded capabilities of AlphaFold 3 and the…

Evidence: 35 • authority: 92

Protein structure prediction powered by artificial intelligence: from biochemical foundations to practical applications.. The three-dimensional structure of a protein underpins its biological function, making structure determination and prediction central challenges in structural biology. Although experimental techniques such as X-ray crystallography, nuclear magnetic resonance (NMR), and cryo-electron microscopy (cryo-EM) can yield high-resolution structures, they are limited by low throughput, high cost, and demanding sample preparation. Likewise, traditional computational methods often perform poorly in the absence of homologous templates or under complex folding dynamics. Recent advance…

Evidence: 35 • authority: 72

The Thinking Game is a 2024 documentary film directed by Greg Kohs. It follows Demis Hassabis and the Google DeepMind team as they solve the "grand challenge" of biology—the protein folding problem—using the AI system AlphaFold, while pursuing the broader goal of artificial general intelligence (AGI). The film documents the scientific work that ultimately led to Hassabis and John Jumper being awarded the Nobel Prize in Chemistry in 2024. Following a limited theatrical run, the film was released for free on YouTube in late 2025, where it became a viral phenomenon, amassing over 200 million views in four weeks.

Evidence: 27 • authority: 72

Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology and addresses Levinthal's paradox. Accurate structure prediction has important applications in medicine (for example, in drug design) and biotechnology (for example, in novel enzyme design). Starting in 1994, the performance of current methods is assessed biennially in the Critical Assessment of Structure Predic…

Evidence: 24 • authority: 92

The transformative impact of AI-enabled AlphaFold 3: evolution, current status, and future prospects in structural biology.. The AlphaFold (AF) initiative profoundly impacted structural biology, evidenced by its 2024 Nobel Prize. AlphaFold progressed from AF1 to AF2, which achieved near-experimental accuracy in single-chain protein folding, and then to AF3, expanding predictions to protein-ligand, protein-nucleic acid, and protein-protein complexes. This evolution led to the widespread adoption of AF tools, expanded structural coverage, and greater accessibility through the AlphaFold Database (AFDB), accelerating translational research, especially in structure-based drug discovery (SBDD) an…

Evidence: 24 • authority: 72

Sir Demis Hassabis (born 27 July 1976) is a British artificial intelligence (AI) researcher and entrepreneur. He is the chairman and co-founder of Google DeepMind and the chief scientist of Alphabet, as well as the chief executive officer and co-founder of Isomorphic Labs. Hassabis is also a UK Government AI Adviser. In 2024, Hassabis and John M. Jumper were jointly awarded the Nobel Prize in Chemistry for their AI research contributions to protein structure prediction. Hassabis is a Fellow of the Royal Society and has won awards for his research efforts, including the Breakthrough Prize, the Canada Gairdner International Award and the Lasker Award. He was appointed a CBE in 2017, and knigh…

Evidence: 20 • authority: 92

Comprehensive evaluation of AlphaFold/OpenFold prediction of experimentally unresolved proteins through novel metrics.. Predicting accurate protein structures is essential for understanding molecular mechanisms, interpreting the impact of sequence variation, and supporting translational applications ranging from drug discovery to clinical genomics. Recent advances in deep-learning-based predictors such as AlphaFold2, OpenFold, and AlphaFold3 have transformed structural biology, enabling routine in silico modeling even for challenging or previously uncharacterized proteins. However, systematic benchmarking of these tools-especially for novel targets and single amino acid variants-remains lim…

Evidence: 20 • authority: 72

Protein folding is the physical process by which a protein, after synthesis by a ribosome as a linear chain of amino acids, changes from an unstable random coil into a more ordered three-dimensional structure. This structure permits the protein to become biologically functional or active. The folding of many proteins begins even during the translation of the polypeptide chain. The amino acids interact with each other to produce a well-defined three-dimensional structure, known as the protein's native state. This structure is determined by the amino-acid sequence or primary structure. The correct three-dimensional structure is essential to function, although some parts of functional proteins…