Artificial intelligence company DeepMind has announced a major medical scientific breakthrough in determining the structures of nearly 200 million proteins.
Proteins are not two-dimensional molecules, but have chemical properties that are determined by their three-dimensional shape, but figuring out these shapes is an intensive process.
The breakthrough has major implications for medicine, with the new Google-backed DeepMind research being hailed as having “the potential to dramatically increase our understanding of biology”.
A protein is created by a chain of amino acids, but without knowing how these chains are connected it is not possible to know how they interact with human cells and can be modified.
Last year DeepMind, owned by Google’s parent company Alphabet, shared the fruits of an AI system called AlphaFold that could predict the 3D structure of a protein based on its amino acid sequence one dimensional
A year earlier, PC gamers had to donate some of their computing power to an international effort investigating diseases like COVID-19 and Alzheimer’s to simulate the molecular dynamics of protein folding.
It is such a crucial topic for medical science because the structure of proteins determines chemical reactions in human cells and, by extension and in the whole human body as a whole, but until now only a part of protein structures.
The announcement and DeepMind’s freely shared protein structure database dramatically increase the number of known protein structures from nearly a million to more than 200 million.
It was created together with EMBL’s European Bioinformatics Institute (EMBL-EBI), whose CEO Edith Heard said: “AlphaFold now provides a 3D view of the protein universe.”
“We have been amazed at the rate at which AlphaFold has already become an essential tool for hundreds of thousands of scientists in labs and universities around the world,” said Demis Hassabis, founder and CEO of DeepMind.
“From fighting disease to fighting plastic pollution, AlphaFold has already enabled incredible impact on some of our biggest global challenges,” Hassabis added.
“Our hope is that this expanded database will help countless more scientists in their important work and open up entirely new avenues of scientific discovery.”
The research has been hailed by scientists who have been using AlphaFold models to develop antibodies against malaria and even special enzymes that could break down plastics.
Since its launch, more than 1,000 scientific articles have been published and more than 500,000 researchers from more than 190 countries have accessed the database.
Other areas of research enabled by the database include honey bee health, understanding how ice forms, and neglected diseases such as Chugs disease and leishmaniasis.
“This is just the impact of one million predictions; imagine the impact of having more than 200 million protein structure predictions openly accessible in the AlphaFold database,” said Sameer Velankar, who leads the EMBL-EBI Protein Data Bank team in Europe.