In July 2022, DeepMind released the AlphaFold protein structure predictions for all known catalogued proteins. This is a significant contribution to our understanding of biology. Proteins are like tiny machines that have specific functions, and understanding their structures can help in finding cures for diseases and addressing other important issues such as antibiotic resistance, pollution, and climate change. Today, DeepMind is sharing high-quality predictions for the shape of every protein in the human body, as well as for proteins in 20 other organisms that scientists study.
This dataset is a game-changer, comparable to the mapping of the Human Genome. It doubles our knowledge of the human proteome and provides insights into the protein structures of other organisms. This is a huge resource that will have a lasting impact on our understanding of biology and medicine.
AlphaFold 2, developed by DeepMind, uses AI to accurately predict the shape of proteins in minutes, which would otherwise take a long time to determine experimentally. This breakthrough has led to the creation of the AlphaFold Protein Structure Database, which offers the most complete and accurate picture of the human proteome to date. In addition to the human proteome, the database also includes protein structures from other significant organisms.
The database is open-access and will be continuously updated with new information. Scientists around the world can use this resource to accelerate their research and make groundbreaking discoveries. Already, AlphaFold has been used in various studies, including research on neglected diseases and antibiotic resistance.
This achievement is the result of five years of hard work by the AlphaFold team at DeepMind. They have overcome numerous challenges and developed sophisticated algorithms to solve the protein folding problem. With AlphaFold, we have a powerful tool that can revolutionize scientific research and drive new discoveries.
At DeepMind, we believe that AI can revolutionize science and push humanity forward. AlphaFold and the AlphaFold Protein Structure Database are just the beginning. We are excited to see what new breakthroughs and discoveries this technology will enable in the future.
To learn more about AlphaFold and access the database, you can visit the Nature website and read the peer-reviewed papers. You can also explore the open-source code for AlphaFold and access the structures through the EMBL-EBI database. We are eager to hear how AlphaFold has been helpful in your research, so please share your feedback with us at alphafold@deepmind.com.