DeepMind Expands Predicted Structures For Nearly All Cataloged Proteins Increasing AlphaFold DB’s Size By Over 200x

Proteins are the foundation for all biological processes in all living things and are the basic building blocks of life. Knowing a protein’s structure also helps understand what it does and how it functions better because a protein’s shape is directly related to its function. 

Last year, DeepMind launched AlphaFold, an AI system that can predict the 3D structure of a protein merely from its 1D amino acid sequence. With AlphaFold, finding a protein’s 3D structure could be done in a matter of seconds as opposed to months or years in the past.

Recently, DeepMind collaborated with EMBL’s European Bioinformatics Institute (EMBL-EBI) and released predicted structures for nearly all cataloged proteins known to science. This work has increased the AlphaFold DB’s size by over 200x, from just under 1 million structures to over 200 million structures, which has the potential to significantly improve the understanding of biology.

With the inclusion of projected structures for plants, bacteria, animals, and other creatures in this release, researchers now have a wealth of new chances to use AlphaFold to further their study on vital topics like sustainability, food insecurity, and unrecognized diseases.

Most pages on the primary protein database UniProt will now have a predicted structure thanks to today’s upgrade. Additionally, all 200+ million structures will be available for mass download via Google Cloud Public Datasets, allowing scientists worldwide greater access to AlphaFold.

To date, more than 500,000 academics have used AlphaFold to speed up research on significant real-world issues, including decomposing plastic waste, safeguarding bees, solving biological problems, and antibiotic resistance, to name a few. 

In terms of their work with AlphaFold, DeepMind is working on projects with the greatest positive social impact, emphasizing programs that had previously received insufficient funding or were ignored. They collaborated with the Drugs for Neglected Diseases Initiative (DNDI) to enhance their research, bringing them one step closer to discovering treatments for life-threatening illnesses like Leishmaniasis and Chagas disease that disproportionately impact individuals in developing nations. 

DeepMind further plans to use AI to solve other fascinating and significant scientific problems, such as climate science, quantum chemistry, and nuclear fusion.

Project: https://alphafold.ebi.ac.uk/

References:

• https://www.deepmind.com/blog/alphafold-reveals-the-structure-of-the-protein-universe
• https://www.ithome.com.tw/news/152207

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