AlphaFold 3
A
Alphafold 3
Overview :
AlphaFold 3 is a revolutionary AI model that can predict the structures and interactions of life molecules such as proteins, DNA, RNA, and ligands. Compared to existing prediction methods, it achieves at least a 50% improvement in the accuracy of predicting the interactions between proteins and other molecular types, and even doubles the accuracy in some important categories. This model will greatly advance our understanding of the biological world and drug discovery.
Target Users :
[" Scientists and Researchers: Utilize AlphaFold 3 to accelerate and improve drug design, understand new disease targets, and develop new treatment methods."," Pharmaceuticals: Collaborate with Isomorphic Labs to apply AlphaFold 3 to real-world drug design challenges, and develop new treatment methods."," Education and Research Institutions: Conduct non-commercial research using AlphaFold Server without the need for substantial computational resources or machine learning expertise."]
Total Visits: 7.6M
Top Region: US(33.51%)
Website Views : 82.0K
Use Cases
Research for malaria vaccine, cancer treatment, and enzyme design
Assist in understanding coronaviruses, including COVID-19, to increase the likelihood of treatment options
Development of healthier and more resilient crops
Features
Predict the structures of large biological molecules such as proteins, DNA, and RNA.
Simulate small molecules, including many ligands such as drugs.
Simulate chemical modifications between molecules, which control cell health functions.
Use diffusion networks for prediction, starting from atomic clouds and converging through multiple steps to the most accurate molecular structures.
Achieve unprecedented accuracy in predicting drug-like interactions, including the binding of proteins to ligands and antibodies to target proteins.
Provide a free and user-friendly non-commercial research tool for global scientists through the AlphaFold Server.
How to Use
Step 1: Visit the AlphaFold Server
Step 2: Enter the list of molecules to be predicted
Step 3: AlphaFold 3 generates the combined 3D structures of the molecules
Step 4: Observe the predicted structures to understand how molecules combine together
Step 5: Use the predicted results to form new scientific hypotheses
Step 6: Test these hypotheses in the laboratory
Step 7: Adjust the input parameters of AlphaFold 3 based on experimental results
Step 8: Utilize the improved model for more in-depth research
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