Demis Hassabis, John Jumper, Pushmeet Kohli and Anna Koivuniemi on behalf of the AlphaFold team
[x]
Since 2020, AlphaFold has accelerated the pace of science and fueled a global wave of biological discovery — an achievement recognized with a Nobel Prize
Five years ago, AlphaFold 2 solved the protein structure prediction problem, unlocking new avenues of biological research and providing our first major proof point that AI can be a powerful tool to advance science.
Proteins are the complex, microscopic machines that drive every process in a living cell. Composed of long, unique chains of amino acids, they precisely fold into a 3D structure that largely defines the protein’s function - making knowledge of this shape critical for drug discovery and understanding disease.
p53 is a cellular tumor antigen related to diseases such as cancer. It is one of the most popular proteins in the AlphaFold Protein Database.
If a protein misfolds, it can lose its function and lead to disease, like Alzheimer’s and Parkinson’s. For decades, determining these structures was a monumental task, often taking a year or more of expensive, painstaking experimental work.
At the CASP 14 (Critical Assessment of protein Structure Prediction) competition in 2020, AlphaFold 2 predicted the structures of proteins based just on their amino acid sequences with astonishing accuracy - an achievement widely hailed as a solution to this 50-year-old grand challenge in biology. But the true, lasting impact of this breakthrough came when we put AlphaFold in the hands of the research community.
A global engine for discovery
In 2021, we launched the AlphaFold Protein Database in partnership with EMBL-EBI, which was a tipping point toward AlphaFold becoming a scientific tool adopted around the world. And one year later, we released AlphaFold 2’s predictions for more than 200 million protein structures, achieving what would take hundreds of millions of years to solve experimentally.
The freely available AlphaFold Protein Database has accelerated science on a scale that was previously unimaginable. It has been used by over 3 million researchers in more than 190 countries, including over 1 million users in low- and middle-income countries. Over 30% of AlphaFold-related research is focused on better understanding disease, benefiting human welfare.
The profound scientific and societal value of this work was recognized in 2024 with the Nobel Prize in Chemistry.
Demis Hassabis, John Jumper, Pushmeet Kohli and Anna Koivuniemi on behalf of the AlphaFold team
[x]
Since 2020, AlphaFold has accelerated the pace of science and fueled a global wave of biological discovery — an achievement recognized with a Nobel Prize
Five years ago, AlphaFold 2 solved the protein structure prediction problem, unlocking new avenues of biological research and providing our first major proof point that AI can be a powerful tool to advance science.
Proteins are the complex, microscopic machines that drive every process in a living cell. Composed of long, unique chains of amino acids, they precisely fold into a 3D structure that largely defines the protein’s function - making knowledge of this shape critical for drug discovery and understanding disease.
p53 is a cellular tumor antigen related to diseases such as cancer. It is one of the most popular proteins in the AlphaFold Protein Database.
Video 1
For half a century, scientists struggled to predict how proteins fold. A puzzle at the heart of understanding life and curing disease. Then, five years ago, the AlphaFold team cracked the code.
Real-world transformation
AlphaFold has become a standard tool for scientists tackling some of the world's most pressing issues, from conservation to heart health.
Breeding healthier and stronger honeybees
Scientists in Europe used AlphaFold to understand a key immunity protein in honeybees, Vitellogenin (Vg). These structural insights are now being applied to conservation efforts for endangered bee populations and guiding the development of AI-assisted breeding programs for healthier, more resilient pollinators.
Learn more
Revealing a key protein behind heart disease
Atherosclerosis, caused by “bad cholesterol” (LDL), is the leading cause of global mortality. For decades, the structure of the central protein in LDL, apolipoprotein B100 (apoB100), remained elusive. AlphaFold 2 helped finally reveal its complex, cage-like shape. This long-awaited blueprint gives pharmaceutical researchers the atomic-level detail needed to design new preventative heart therapies.
Learn more
Read more about AlphaFold’s impact
Revolutionizing Research
AlphaFold is also transforming scientific research - broadening access, accelerating timelines and dramatically lowering the cost.
Expanding access
Turkish undergraduate students Alper and Taner Karagöl taught themselves structural biology during the pandemic using online AlphaFold tutorials – with no prior training. They've now published 15 research papers.
This picture shows a water-soluble version of the EAAT1 protein. EAAT1 is a transporter in brain cells that normally sits in the membrane and helps clear the neurotransmitter glutamate. Here, the protein has been redesigned using the QTY method, which swaps water-repelling amino acids with water-friendly ones so it can dissolve in water. The blue coils are the protein, and the surrounding dots are water molecules and salt ions.
Increasing speed of discovery
Cyril Zipfel, professor of Molecular & Cellular Plant Physiology at the University of Zurich and Sainsbury Lab, saw research timelines shrink drastically. They used AlphaFold alongside comparative genomics to better understand how plants perceive changes in their environment, paving the way for more resilient crops.
AlphaFold has been cited in more than 35,000 papers and more than 200,000 papers incorporated elements of AlphaFold 2 in their methodology. It’s also enhancing the quality of work being produced.
An independent analysis of AlphaFold 2’s impact, carried out by the Innovation Growth Lab, suggests that researchers using AlphaFold 2 see an increase of over 40% in their submission of novel experimental protein structures. Those protein structures are more likely to be dissimilar to known structures, encouraging the exploration of uncharted areas of science. Also, research linked to AlphaFold 2 is twice as likely to be cited in clinical articles, and is significantly more likely to be cited by a patent, than typical works in structural biology.
A new era of digital biology
One of the most exciting examples of AlphaFold's impact is Isomorphic Labs – an AI drug discovery company founded in 2021 when the breakthrough model proved to be powerful enough to be applied to rational drug design. Isomorphic Labs has since developed a unified drug design engine to dramatically change how it designs new medicines and speed up scientific discovery with an ambition to one day solve all diseases.
Together with Isomorphic Labs, we developed AlphaFold 3, which offers an unprecedented view into cells that we expect to drive a transformation of the drug discovery process and usher in an era of "digital biology."
The model is designed to predict the structure and interactions of all of life's molecules — not just proteins, but DNA, RNA, and ligands (the small molecules that make up most drugs). It can also generate the joint 3D structures of entire molecular complexes, allowing a holistic view of how a potential drug molecule binds to its target protein, or how proteins interact with genetic material.
The AlphaFold Server is empowering non-commercial researchers globally to harness this technology, accelerating their ability to formulate and test new hypotheses. So far, it’s helped make more than 8 million folds - predictions of structures and interactions - for thousands of researchers around the world.
Video 2
John Jumper, one of the most instrumental scientists behind AlphaFold shares stories about his Nobel win, the tool's unexpected applications, and the shift in architecture from AlphaFold 2 to the more comprehensive AlphaFold 3.
The future of AI for science
Inspired by AlphaFold, we’ve developed a new generation of models to solve problems across biology. AlphaMissense and AlphaGenome use AI to assess the genetic mutations that underpin disease. Our AlphaProteo model can design novel, high-strength protein binders that target diverse molecules – including those associated with cancer and diabetes. These models are deepening our understanding of complex diseases and ultimately driving the development of new treatments.
Biology was our first frontier, but we view AlphaFold as the template for how AI can accelerate all of science to digital speed. From fusion and Earth sciences to scientific discovery as a whole, we’re pursuing the next AlphaFold-like breakthroughs. We’re excited to continue partnering with the global scientific community, empowering researchers everywhere to tackle the biggest challenges facing humanity.
Visit our AlphaFold pageExplore the AlphaFold Protein Structure DatabaseAccess the AlphaFold ServerListen to our podcast with John Jumper
If a protein misfolds, it can lose its function and lead to disease, like Alzheimer’s and Parkinson’s. For decades, determining these structures was a monumental task, often taking a year or more of expensive, painstaking experimental work.
At the CASP 14 (Critical Assessment of protein Structure Prediction) competition in 2020, AlphaFold 2 predicted the structures of proteins based just on their amino acid sequences with astonishing accuracy - an achievement widely hailed as a solution to this 50-year-old grand challenge in biology. But the true, lasting impact of this breakthrough came when we put AlphaFold in the hands of the research community.
A global engine for discovery
In 2021, we launched the AlphaFold Protein Database in partnership with EMBL-EBI, which was a tipping point toward AlphaFold becoming a scientific tool adopted around the world. And one year later, we released AlphaFold 2’s predictions for more than 200 million protein structures, achieving what would take hundreds of millions of years to solve experimentally.
The freely available AlphaFold Protein Database has accelerated science on a scale that was previously unimaginable. It has been used by over 3 million researchers in more than 190 countries, including over 1 million users in low- and middle-income countries. Over 30% of AlphaFold-related research is focused on better understanding disease, benefiting human welfare.
The profound scientific and societal value of this work was recognized in 2024 with the Nobel Prize in Chemistry.
Video 1
For half a century, scientists struggled to predict how proteins fold. A puzzle at the heart of understanding life and curing disease. Then, five years ago, the AlphaFold team cracked the code.
Real-world transformation
AlphaFold has become a standard tool for scientists tackling some of the world's most pressing issues, from conservation to heart health.
Breeding healthier and stronger honeybees
Scientists in Europe used AlphaFold to understand a key immunity protein in honeybees, Vitellogenin (Vg). These structural insights are now being applied to conservation efforts for endangered bee populations and guiding the development of AI-assisted breeding programs for healthier, more resilient pollinators.
Learn more
Revealing a key protein behind heart disease
Atherosclerosis, caused by “bad cholesterol” (LDL), is the leading cause of global mortality. For decades, the structure of the central protein in LDL, apolipoprotein B100 (apoB100), remained elusive. AlphaFold 2 helped finally reveal its complex, cage-like shape. This long-awaited blueprint gives pharmaceutical researchers the atomic-level detail needed to design new preventative heart therapies.
Learn more
Read more about AlphaFold’s impact
Revolutionizing Research
AlphaFold is also transforming scientific research - broadening access, accelerating timelines and dramatically lowering the cost.
Expanding access
Turkish undergraduate students Alper and Taner Karagöl taught themselves structural biology during the pandemic using online AlphaFold tutorials – with no prior training. They've now published 15 research papers.
This picture shows a water-soluble version of the EAAT1 protein. EAAT1 is a transporter in brain cells that normally sits in the membrane and helps clear the neurotransmitter glutamate. Here, the protein has been redesigned using the QTY method, which swaps water-repelling amino acids with water-friendly ones so it can dissolve in water. The blue coils are the protein, and the surrounding dots are water molecules and salt ions.
Increasing speed of discovery
Cyril Zipfel, professor of Molecular & Cellular Plant Physiology at the University of Zurich and Sainsbury Lab, saw research timelines shrink drastically. They used AlphaFold alongside comparative genomics to better understand how plants perceive changes in their environment, paving the way for more resilient crops.
AlphaFold has been cited in more than 35,000 papers and more than 200,000 papers incorporated elements of AlphaFold 2 in their methodology. It’s also enhancing the quality of work being produced.
An independent analysis of AlphaFold 2’s impact, carried out by the Innovation Growth Lab, suggests that researchers using AlphaFold 2 see an increase of over 40% in their submission of novel experimental protein structures. Those protein structures are more likely to be dissimilar to known structures, encouraging the exploration of uncharted areas of science. Also, research linked to AlphaFold 2 is twice as likely to be cited in clinical articles, and is significantly more likely to be cited by a patent, than typical works in structural biology.
A new era of digital biology
One of the most exciting examples of AlphaFold's impact is Isomorphic Labs – an AI drug discovery company founded in 2021 when the breakthrough model proved to be powerful enough to be applied to rational drug design. Isomorphic Labs has since developed a unified drug design engine to dramatically change how it designs new medicines and speed up scientific discovery with an ambition to one day solve all diseases.
Together with Isomorphic Labs, we developed AlphaFold 3, which offers an unprecedented view into cells that we expect to drive a transformation of the drug discovery process and usher in an era of "digital biology."
The model is designed to predict the structure and interactions of all of life's molecules — not just proteins, but DNA, RNA, and ligands (the small molecules that make up most drugs). It can also generate the joint 3D structures of entire molecular complexes, allowing a holistic view of how a potential drug molecule binds to its target protein, or how proteins interact with genetic material.
The AlphaFold Server is empowering non-commercial researchers globally to harness this technology, accelerating their ability to formulate and test new hypotheses. So far, it’s helped make more than 8 million folds - predictions of structures and interactions - for thousands of researchers around the world.
Video 2
John Jumper, one of the most instrumental scientists behind AlphaFold shares stories about his Nobel win, the tool's unexpected applications, and the shift in architecture from AlphaFold 2 to the more comprehensive AlphaFold 3.
The future of AI for science
Inspired by AlphaFold, we’ve developed a new generation of models to solve problems across biology. AlphaMissense and AlphaGenome use AI to assess the genetic mutations that underpin disease. Our AlphaProteo model can design novel, high-strength protein binders that target diverse molecules – including those associated with cancer and diabetes. These models are deepening our understanding of complex diseases and ultimately driving the development of new treatments.
Biology was our first frontier, but we view AlphaFold as the template for how AI can accelerate all of science to digital speed. From fusion and Earth sciences to scientific discovery as a whole, we’re pursuing the next AlphaFold-like breakthroughs. We’re excited to continue partnering with the global scientific community, empowering researchers everywhere to tackle the biggest challenges facing humanity.
Visit our AlphaFold pageExplore the AlphaFold Protein Structure DatabaseAccess the AlphaFold ServerListen to our podcast with John Jumper