Scientists use AI to find drug that kills bacteria responsible for many drug-resistant infections

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

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

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

The microbe is also a leading cause of infections in wounded soldiers in Iraq and Afghanistan.

PARALYZED MAN REGAINS THIS ‘SIMPLE PLEASURE’ THANKS TO AI ‘DIGITAL BRIDGE’

Using an artificial intelligence algorithm, researchers at MIT and McMaster University have identified a new antibiotic that can kill a type of bacteria (Acinetobacter baumannii, pink) that is responsible for many drug-resistant infections. (Christine Daniloff/MIT; Acinetobacter baumannii image courtesy of CDC)

Over the past decades, many pathogenic bacteria have become increasingly resistant to antibiotics, while few new antibiotics have been developed.

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

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

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

After the model was trained, it was used to analyze a set of 6,680 compounds it had not seen before, and researchers narrowed down 240 hits to test experimentally, focusing on compounds with structures that were different from those of existing antibiotics or molecules from the training data. That testing led to nine antibiotics, including one that was very strong. 

AI AND MACHINE MAY SPEED DRUG DEVELOPMENT, MANUFACTURING: FDA

The compound, which was originally explored as a potential diabetes drug, turned out to be extremely effective at killing the bacteria. However, it had no effect on other species of bacteria.

The university noted that a “narrow spectrum” killing ability is desirable because it minimizes the risk of bacteria rapidly spreading resistance against the drug. Further, the drug would likely spare the beneficial bacteria that live in the human gut and help to suppress opportunistic infections.

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

The scientists named the drug abaucin and showed in studies in mice that it could treat wound infections caused by the bacteria. In lab tests, it was also found to work against a variety of drug-resistant Acinetobacter baumannii strains isolated from human patients. The drug was shown to kill cells by interfering with a process known as lipoprotein trafficking in additional experiments. Cells use that to transport proteins from the interior of the cell to the cell envelope. 

CLICK HERE TO GET THE FOX NEWS APP 

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

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

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