Once-powerful antibiotics are losing their efficacy at a disconcerting pace as bacteria evolve immunity to our drugs. At least 700,000 people around the world now die each year from infections that could formerly be treated with antibiotics. A report last year from the United Nations Interagency Coordination Group on Antimicrobial Resistance warned that if no new major advances are made by 2050, mortality could leap to 10 million deaths a year.
What makes this prognosis all the more dire is that the antibiotic pipeline has slowed to a trickle. In the past two decades, only a few new antibiotics have been found that kill bacteria in novel ways, and rising resistance is a problem for all of them. (Antibiotics are distinct from the type of antiviral drugs that researchers are currently investigating as potential treatments for COVID-19, the disease caused by the novel coronavirus spreading around the world.) Meanwhile, traditional methods of identifying antibiotics by screening natural compounds continue to come up short. Because of this, some researchers are now turning from the wet lab to silicon power in hopes of finding an answer.
In the February 20 issue of Cell, one team of scientists announced that they—and a powerful deep-learning algorithm—had found a totally new antibiotic, one with an unconventional mechanism of action that allows it to fight infections that are resistant to multiple drugs. The compound was hiding in plain sight (as a possible diabetes treatment) because humans didn’t know what to look for. But the computer did.