Scientists are using AI to find a drug that kills bacteria responsible for many drug-resistant infections

Scientists are using AI to find a drug that kills bacteria responsible for many drug-resistant infections

Scientists have found a drug that could fight drug-resistant infections – and they did it using artificial intelligence.

Using a machine learning algorithm, researchers from Massachusetts Institute of Technology (MIT) and Canada’s McMaster University have identified a new antibiotic capable of killing a type of bacteria responsible for many drug-resistant infections.

The compound kills Acinetobacter baumannii, a species of bacteria often found in hospitals. It can lead to pneumonia, meningitis and other serious infections.

The microbe is also one of the main causes of infections in wounded soldiers in Iraq and Afghanistan.


Using an artificial intelligence algorithm, researchers from MIT and McMaster University have identified a new antibiotic capable of killing a type of bacteria (Acinetobacter baumannii, rose) responsible for many drug-resistant infections. (Christine Daniloff/MIT; Acinetobacter baumannii image courtesy of CDC)

In recent decades, many pathogenic bacteria have become increasingly resistant to antibiotics, while few new antibiotics have been developed.

MIT said in a statement that the researchers identified the drug from a catalog of nearly 7,000 potential drug compounds using a machine learning model they trained to assess whether a compound chemical would inhibit the growth of the bacteria.

In order to get training data for the model, they first exposed bacteria grown in a lab dish to about 7,500 different chemical compounds to see which ones might inhibit the growth of the microbe. They fed the structure of each molecule into their model and told it whether each structure could inhibit bacterial growth.

WITH campus

People walk through the Massachusetts Institute of Technology campus in Cambridge, Massachusetts, Wednesday, June 2, 2021. (Photographer: Adam Glanzman/Bloomberg via Getty Images)

Once the model was trained, it was used to analyze a set of 6,680 compounds it hadn’t seen before, and the researchers narrowed down 240 results to test experimentally, focusing on compounds with different structures from those of existing antibiotics or formation molecules. data. These tests led to nine antibiotics, including one very powerful.


The compound, initially explored as a potential diabetes drug, was found to be extremely effective in killing bacteria. However, it had no effect on other species of bacteria.

The university noted that a “narrow-spectrum” killing capability is desirable because it minimizes the risk that bacteria will quickly spread resistance against the drug. Additionally, the drug would likely spare the beneficial bacteria that live in the human gut and help suppress opportunistic infections.

The McMaster University Bandstand

The McMaster University booth at the Metro Toronto Convention Centre. (RJ Johnston/Toronto Star via Getty Images)

Scientists named the drug abaucin and showed in mouse studies that it could treat wound infections caused by the bacteria. In laboratory tests, it has also been shown to be effective against a variety of drug-resistant strains of Acinetobacter baumannii isolated from human patients. The drug has been shown to kill cells by interfering with a process known as lipoprotein trafficking in additional experiments. Cells use it to transport proteins from inside the cell to the cell envelope.


A lab at McMaster University is currently working for others to optimize the medicinal properties of the compound and hopefully develop it for eventual use in patients.

The study authors also plan to use their modeling approach to identify potential antibiotics for other types of drug-resistant infections.

The results were published Thursday in the journal “Nature Chemical Biology.”


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