DeepMind describes how Antigravity was used to find an antimicrobial peptide candidate against respiratory tract pathogens
Prepared by Sintelligent with the help of SI. Published in SI: . Updated: .
SI is speeding up the search for new substances against resistant bacteria: a candidate has been found, but laboratory experiments will show whether it becomes a drug.
According to DeepMind's blog, biologists used the Google Antigravity platform to scan millions of proteins of unknown function in the UniProt database, using the ProtNLM model, which predicts function from an amino acid sequence, and found an antimicrobial peptide candidate with predicted activity against pathogens that cause respiratory tract infections. The candidate is undergoing laboratory validation and there are no results yet; this is a technical description of the process, not a confirmed drug. By the authors' estimate, antimicrobial resistance could cause about 10 million deaths a year by 2050.
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