Alphabet (Google's parent company) subsidiary DeepMind has shown that Machine Learning (ML) can predict the shape of protein machinery with unprecedented accuracy, paving the way for researchers to discover new antibodies, enzymes and foods.
The shape of a protein provides very strong clues as to how the protein machinery can be used, but doesn't completely solve this question.
"So we wondered, can we predict what function a protein will perform?" Max Bileschi, a staff software engineer with Google Research's Brain Team, elaborated.
Google described in a Nature Biotechnology article how neural networks outperform state-of-the-art methods in reliably revealing the function of the protein universe's "dark matter."
DeepMind collaborated closely with internationally recognised experts at the EMBL's European Bioinformatics Institute (EMBL-EBI) to annotate 6.8 million additional protein regions in the 'Pfam v34.0 database' release, a global repository for protein families and their functions.
These annotations outnumber the database's expansion over the last decade, allowing the world's 2.5 million life-science researchers to discover new antibodies, enzymes, foods, and therapeutics.
For roughly one-third of all proteins found in all organisms
"Our ML models helped annotate 6.8 million more protein regions in the database," said the researchers.
The company has also launched an interactive scientific article where "you can play with our ML models -- getting results in real time, all in your web browser, with no setup required."
According to researchers, combining deep models with existing methods significantly improves remote homology detection, suggesting that the deep models learn complementary information.
This approach extends the coverage of Pfam by more than 9.5 per cent, exceeding additions made over the last decade, and predicts function for 360 human reference proteome proteins with no previous Pfam annotation.
"The results suggest that deep learning models will be a core component of future protein annotation tools."
