HomeAlphaFold 3: Predicting All Life Molecules' Structures and Interactions
Inside every plant, animal, and human cell, there's a bustling world of molecular machines. These machines, made up of proteins, DNA, and other molecules, don't operate solo. It's only by understanding their interactions across countless combinations that we can truly grasp the essence of life's processes.
In a recent paper published in *Nature*, we unveiled AlphaFold 3, a groundbreaking model that predicts the structure and interactions of all life's molecules with unprecedented precision. When it comes to how proteins interact with other molecule types, AlphaFold 3 offers at least a 50% improvement over existing methods. For certain key interactions, we've even doubled the accuracy of our predictions.
We're excited about the potential of AlphaFold 3 to revolutionize our understanding of biology and accelerate drug discovery. Scientists can now tap into most of its capabilities for free through our newly launched AlphaFold Server, a user-friendly research tool. Isomorphic Labs is already partnering with pharmaceutical companies to apply AlphaFold 3 to real-world drug design challenges, aiming to develop new treatments that could change lives.
AlphaFold 3 builds on the success of AlphaFold 2, which in 2020 transformed protein structure prediction. Since then, millions of researchers worldwide have used AlphaFold 2 to make breakthroughs in areas like malaria vaccines, cancer treatments, and enzyme design. AlphaFold has been cited over 20,000 times and recognized with numerous awards, including the Breakthrough Prize in Life Sciences. With AlphaFold 3, we're expanding our focus beyond proteins to a wide range of biomolecules, opening up possibilities for even more groundbreaking science—from developing sustainable materials and resilient crops to speeding up drug design and genomics research.
7PNM - Spike protein of a common cold virus (Coronavirus OC43): AlphaFold 3’s structural prediction for a spike protein (blue) of a cold virus as it interacts with antibodies (turquoise) and simple sugars (yellow), accurately matches the true structure (gray). The animation shows the protein interacting with an antibody, then a sugar. Advancing our knowledge of such immune-system processes helps better understand coronaviruses, including COVID-19, raising possibilities for improved treatments.
How AlphaFold 3 reveals life's molecules
----------------------------------------
Given a list of molecules, AlphaFold 3 generates their joint 3D structure, showing how they fit together. It can model large biomolecules like proteins, DNA, and RNA, as well as smaller molecules, or ligands, which include many drugs. Plus, AlphaFold 3 can predict chemical modifications to these molecules, which are crucial for the healthy functioning of cells and can lead to disease if disrupted.
AlphaFold 3's prowess stems from its advanced architecture and training, which now encompasses all of life's molecules. At its heart is an enhanced version of our Evoformer module, the deep learning architecture that powered AlphaFold 2's success. After processing the inputs, AlphaFold 3 uses a diffusion network, similar to those in AI image generators, to assemble its predictions. This process starts with a cloud of atoms and gradually refines it into the most accurate molecular structure.
AlphaFold 3's predictions of molecular interactions are more accurate than any existing system. As a single model that computes entire molecular complexes holistically, it's uniquely positioned to unify scientific insights.
7R6R - DNA binding protein: AlphaFold 3’s prediction for a molecular complex featuring a protein (blue) bound to a double helix of DNA (pink) is a near-perfect match to the true molecular structure discovered through painstaking experiments (gray).
Leading drug discovery at Isomorphic Labs
-----------------------------------------
AlphaFold 3 opens up new possibilities for drug design by predicting how molecules commonly used in drugs, like ligands and antibodies, interact with proteins to influence human health and disease.
AlphaFold 3 achieves unmatched accuracy in predicting drug-like interactions, including how proteins bind with ligands and how antibodies interact with their target proteins. It's 50% more accurate than the best traditional methods on the PoseBusters benchmark, and it doesn't need any structural information to start. This makes AlphaFold 3 the first AI system to outdo physics-based tools for biomolecular structure prediction. Understanding antibody-protein binding is crucial for insights into the human immune response and for designing new antibodies, which are increasingly important in medicine.
Isomorphic Labs is using AlphaFold 3, along with other in-house AI models, to enhance drug design for both internal projects and collaborations with pharmaceutical partners. This approach helps us tackle new disease targets and find innovative ways to address existing ones that were previously unattainable.
AlphaFold Server: A free and easy-to-use research tool
------------------------------------------------------
8AW3 - RNA modifying protein: AlphaFold 3’s prediction for a molecular complex featuring a protein (blue), a strand of RNA (purple), and two ions (yellow) closely matches the true structure (gray). This complex is involved with the creation of other proteins — a cellular process fundamental to life and health.
Google DeepMind's newly launched AlphaFold Server is the world's most accurate tool for predicting how proteins interact with other molecules in the cell. It's a free platform available to scientists worldwide for non-commercial research. With just a few clicks, biologists can use AlphaFold 3 to model structures made up of proteins, DNA, RNA, and a selection of ligands, ions, and chemical modifications.
AlphaFold Server helps scientists generate new hypotheses to test in the lab, speeding up their research and fostering innovation. Our platform makes it easy for researchers to create predictions, no matter their access to computational resources or their expertise in machine learning.
Experimental protein-structure prediction can take as long as a PhD and cost a fortune. Our previous model, AlphaFold 2, has been used to predict hundreds of millions of structures, a task that would have taken hundreds of millions of researcher-years at the current pace of experimental structural biology.
Sharing the power of AlphaFold 3 responsibly
--------------------------------------------
With each AlphaFold release, we've aimed to understand the technology's broad impact, collaborating with the research and safety community. We take a science-led approach and have conducted thorough assessments to minimize potential risks while maximizing the benefits for biology and humanity.
Building on the consultations we did for AlphaFold 2, we've now engaged with over 50 domain experts, as well as specialist third parties, across biosecurity, research, and industry, to assess the capabilities and potential risks of successive AlphaFold models. We've also taken part in community-wide forums and discussions before launching AlphaFold 3.
AlphaFold Server reflects our commitment to sharing the benefits of AlphaFold, including our free database of 200 million protein structures. We're expanding our free AlphaFold education online course with EMBL-EBI and partnering with organizations in the Global South to equip scientists with the tools they need to speed up adoption and research, especially in underfunded areas like neglected diseases and food security. We'll keep working with the scientific community and policymakers to responsibly develop and deploy AI technologies.
Opening up the future of AI-powered cell biology
------------------------------------------------
7BBV - Enzyme: AlphaFold 3’s prediction for a molecular complex featuring an enzyme protein (blue), an ion (yellow sphere) and simple sugars (yellow), along with the true structure (gray). This enzyme is found in a soil-borne fungus (Verticillium dahliae) that damages a wide range of plants. Insights into how this enzyme interacts with plant cells could help researchers develop healthier, more resilient crops.
AlphaFold 3 brings the biological world into sharp focus. It allows scientists to see cellular systems in all their complexity, across structures, interactions, and modifications. This new perspective on life's molecules reveals their interconnectedness and helps us understand how these connections impact biological functions—like how drugs work, how hormones are produced, and how DNA repair keeps us healthy.
The impact of AlphaFold 3 and our free AlphaFold Server will be seen in how they empower scientists to speed up discoveries across open questions in biology and new research areas. We're just starting to explore AlphaFold 3's potential, and we're excited to see what the future holds.
Update November 11, 2024: As of November 2024, we have released AlphaFold 3 model code and weights for academic use to help advance research. Learn more about AlphaFold tools.
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Comments (40)
0/500
![JustinMitchell]()
How does AlphaFold 3 handle the sheer complexity of all those molecular combinations? Mind-blowing stuff! 🤯
![WalterWalker]()
結構な精度を誇るようだけど、AlphaFoldが分子間相互作用まで予測できるって、これで創薬研究めちゃくちゃ加速しそう！でもAIの”ブラックボックス”予測をどう医療現場に持ち込むか、説明責任や臨床審査の壁は依然として大きいよね...😅 これからの議論の行方が気になるわ。
![ChristopherDavis]()
Je suis impressionné par AlphaFold 3 ! 🧬 Comprendre les interactions moléculaires pourrait révolutionner la médecine, mais ça soulève aussi des questions éthiques sur la modification du vivant. Est-ce qu'on va trop loin ?
![BenBrown]()
Mind-blowing how AlphaFold 3 maps out life's molecular dance! 🧬 Curious if this could speed up drug discovery or just make scientists' heads spin with data overload. What's next, predicting my coffee's molecular vibe? 😄
![WillPerez]()
AlphaFold 3 is mind-blowing! Predicting every molecule's structure feels like unlocking the universe’s blueprint. Can’t wait to see how this reshapes drug discovery! 😮
![ScottPerez]()
AlphaFold 3 es alucinante! Es como tener un microscopio para el mundo molecular. Me ayuda muchísimo en mis proyectos de biología. Ojalá fuera un poco más rápido, pero aún así, ¡herramienta increíble! 🔬🌿
Inside every plant, animal, and human cell, there's a bustling world of molecular machines. These machines, made up of proteins, DNA, and other molecules, don't operate solo. It's only by understanding their interactions across countless combinations that we can truly grasp the essence of life's processes.
In a recent paper published in *Nature*, we unveiled AlphaFold 3, a groundbreaking model that predicts the structure and interactions of all life's molecules with unprecedented precision. When it comes to how proteins interact with other molecule types, AlphaFold 3 offers at least a 50% improvement over existing methods. For certain key interactions, we've even doubled the accuracy of our predictions.
We're excited about the potential of AlphaFold 3 to revolutionize our understanding of biology and accelerate drug discovery. Scientists can now tap into most of its capabilities for free through our newly launched AlphaFold Server, a user-friendly research tool. Isomorphic Labs is already partnering with pharmaceutical companies to apply AlphaFold 3 to real-world drug design challenges, aiming to develop new treatments that could change lives.
AlphaFold 3 builds on the success of AlphaFold 2, which in 2020 transformed protein structure prediction. Since then, millions of researchers worldwide have used AlphaFold 2 to make breakthroughs in areas like malaria vaccines, cancer treatments, and enzyme design. AlphaFold has been cited over 20,000 times and recognized with numerous awards, including the Breakthrough Prize in Life Sciences. With AlphaFold 3, we're expanding our focus beyond proteins to a wide range of biomolecules, opening up possibilities for even more groundbreaking science—from developing sustainable materials and resilient crops to speeding up drug design and genomics research.
How AlphaFold 3 reveals life's molecules ----------------------------------------
Given a list of molecules, AlphaFold 3 generates their joint 3D structure, showing how they fit together. It can model large biomolecules like proteins, DNA, and RNA, as well as smaller molecules, or ligands, which include many drugs. Plus, AlphaFold 3 can predict chemical modifications to these molecules, which are crucial for the healthy functioning of cells and can lead to disease if disrupted.
AlphaFold 3's prowess stems from its advanced architecture and training, which now encompasses all of life's molecules. At its heart is an enhanced version of our Evoformer module, the deep learning architecture that powered AlphaFold 2's success. After processing the inputs, AlphaFold 3 uses a diffusion network, similar to those in AI image generators, to assemble its predictions. This process starts with a cloud of atoms and gradually refines it into the most accurate molecular structure.
AlphaFold 3's predictions of molecular interactions are more accurate than any existing system. As a single model that computes entire molecular complexes holistically, it's uniquely positioned to unify scientific insights.
Leading drug discovery at Isomorphic Labs -----------------------------------------
AlphaFold 3 opens up new possibilities for drug design by predicting how molecules commonly used in drugs, like ligands and antibodies, interact with proteins to influence human health and disease.
AlphaFold 3 achieves unmatched accuracy in predicting drug-like interactions, including how proteins bind with ligands and how antibodies interact with their target proteins. It's 50% more accurate than the best traditional methods on the PoseBusters benchmark, and it doesn't need any structural information to start. This makes AlphaFold 3 the first AI system to outdo physics-based tools for biomolecular structure prediction. Understanding antibody-protein binding is crucial for insights into the human immune response and for designing new antibodies, which are increasingly important in medicine.
Isomorphic Labs is using AlphaFold 3, along with other in-house AI models, to enhance drug design for both internal projects and collaborations with pharmaceutical partners. This approach helps us tackle new disease targets and find innovative ways to address existing ones that were previously unattainable.
AlphaFold Server: A free and easy-to-use research tool
------------------------------------------------------
Google DeepMind's newly launched AlphaFold Server is the world's most accurate tool for predicting how proteins interact with other molecules in the cell. It's a free platform available to scientists worldwide for non-commercial research. With just a few clicks, biologists can use AlphaFold 3 to model structures made up of proteins, DNA, RNA, and a selection of ligands, ions, and chemical modifications. AlphaFold Server helps scientists generate new hypotheses to test in the lab, speeding up their research and fostering innovation. Our platform makes it easy for researchers to create predictions, no matter their access to computational resources or their expertise in machine learning. Experimental protein-structure prediction can take as long as a PhD and cost a fortune. Our previous model, AlphaFold 2, has been used to predict hundreds of millions of structures, a task that would have taken hundreds of millions of researcher-years at the current pace of experimental structural biology. With each AlphaFold release, we've aimed to understand the technology's broad impact, collaborating with the research and safety community. We take a science-led approach and have conducted thorough assessments to minimize potential risks while maximizing the benefits for biology and humanity. Building on the consultations we did for AlphaFold 2, we've now engaged with over 50 domain experts, as well as specialist third parties, across biosecurity, research, and industry, to assess the capabilities and potential risks of successive AlphaFold models. We've also taken part in community-wide forums and discussions before launching AlphaFold 3. AlphaFold Server reflects our commitment to sharing the benefits of AlphaFold, including our free database of 200 million protein structures. We're expanding our free AlphaFold education online course with EMBL-EBI and partnering with organizations in the Global South to equip scientists with the tools they need to speed up adoption and research, especially in underfunded areas like neglected diseases and food security. We'll keep working with the scientific community and policymakers to responsibly develop and deploy AI technologies. Opening up the future of AI-powered cell biology
------------------------------------------------
AlphaFold 3 brings the biological world into sharp focus. It allows scientists to see cellular systems in all their complexity, across structures, interactions, and modifications. This new perspective on life's molecules reveals their interconnectedness and helps us understand how these connections impact biological functions—like how drugs work, how hormones are produced, and how DNA repair keeps us healthy. The impact of AlphaFold 3 and our free AlphaFold Server will be seen in how they empower scientists to speed up discoveries across open questions in biology and new research areas. We're just starting to explore AlphaFold 3's potential, and we're excited to see what the future holds. Update November 11, 2024: As of November 2024, we have released AlphaFold 3 model code and weights for academic use to help advance research. Learn more about AlphaFold tools.
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How does AlphaFold 3 handle the sheer complexity of all those molecular combinations? Mind-blowing stuff! 🤯
結構な精度を誇るようだけど、AlphaFoldが分子間相互作用まで予測できるって、これで創薬研究めちゃくちゃ加速しそう！でもAIの”ブラックボックス”予測をどう医療現場に持ち込むか、説明責任や臨床審査の壁は依然として大きいよね...😅 これからの議論の行方が気になるわ。
Je suis impressionné par AlphaFold 3 ! 🧬 Comprendre les interactions moléculaires pourrait révolutionner la médecine, mais ça soulève aussi des questions éthiques sur la modification du vivant. Est-ce qu'on va trop loin ?
Mind-blowing how AlphaFold 3 maps out life's molecular dance! 🧬 Curious if this could speed up drug discovery or just make scientists' heads spin with data overload. What's next, predicting my coffee's molecular vibe? 😄
AlphaFold 3 is mind-blowing! Predicting every molecule's structure feels like unlocking the universe’s blueprint. Can’t wait to see how this reshapes drug discovery! 😮
AlphaFold 3 es alucinante! Es como tener un microscopio para el mundo molecular. Me ayuda muchísimo en mis proyectos de biología. Ojalá fuera un poco más rápido, pero aún así, ¡herramienta increíble! 🔬🌿
