The researchers made AlphaFold open source and released it a year ago. Since then, the researchers have used the AlphaFold Protein Structure Database (AlphaFold DB) for free use by scientists everywhere. Proteins are the building blocks of life in all living things, depending on them. And because a protein's shape is closely related to what it does, knowing its structure lets you know more about what it does and how it works.

The researchers hoped this new tool would speed up scientific research and discovery worldwide. They also hoped that other teams could learn from the progress made with AlphaFold and build on it to make more important discoveries. This hope has come true much faster than the researchers ever thought was possible. In just one year, more than half a million researchers have used AlphaFold to work more quickly on critical real-world problems like plastic pollution and antibiotic resistance.

In partnership with EMBL's European Bioinformatics Institute (EMBL-EBI), the researchers' released predicted structures for nearly all catalogued proteins known to science. This release will increase the AlphaFold DB from almost 1 million structures to over 200 million structures, which could help us learn a lot more about biology. In addition, this update adds predicted structures for plants, bacteria, animals, and other organisms. This release gives researchers a lot of new ways to use AlphaFold to progress on important issues like sustainability, food security, and diseases that haven't been for a long time.

A recent update to the central protein database, UniProt, means that most pages will now have a predicted structure. In addition, all 200 million structures will also be available for bulk download through Google Cloud Public Datasets. This release makes AlphaFold even more accessible to scientists all over the world.

What AlphaFold has done so far

AlphaFold has been available for a year, and it's incredible to consider the influence and how far researchers have gone to reach this point.

AlphaFold's success was incredibly satisfying for their team because it was the most complex AI system the researcher had ever built, requiring several important new ideas, and because it has had the most acute effects on the world. By showing that AI could accurately predict the shape of a protein down to the atomic level, at scale, and in minutes. AlphaFold not only solved a problem that had been bothering scientists for 50 years, but it also became the first big proof point of their founding thesis. That AI can dramatically speed up scientific discovery and, in turn, improve the world.

The researchers made the code for AlphaFold available to everyone and published two detailed papers in Nature. These papers have more than 4,000 citations. In addition, the researchers worked closely with the world-class EMBL-EBI to make a tool that would help biologists access and use AlphaFold. Together, they made the AlphaFold DB, a searchable database that anyone can use for free. Finally, before releasing AlphaFold, the researchers asked more than 30 experts in biology research, security, ethics, and safety for advice on how to share the benefits of AlphaFold with the world in a way that would help the most people and cause the least harm.

Over 2 million structures have been looked at by more than 500,000 researchers from 190 different countries. Their free structures have public databases like Ensembl, UniProt, and OpenTargets, which millions of people use as part of their daily work.

Conclusion

AlphaFold has brought biology into a time when many different structures exist, letting scientists explore at digital speed. The AlphaFold DB is like a "Google search" for protein structures. It gives researchers instant access to predicted models of the proteins they are studying, so they can focus their efforts and speed up experimental work. AlphaFold has already helped us make remarkable progress on some of the world's biggest problems, like fighting disease and making vaccines. This release is just the beginning of the changes researchers will observe in the coming years. They anticipate that this more extensive database would facilitate the work of a more significant number of experts and provide new avenues for scientific research, such as metaproteomics.