Scientists using artificial intelligence have discovered a new antibiotic that can kill deadly superbugs.
According to a new study published Thursday in the scientific journal Nature Chemical Biology, a team of scientists from McMaster University and MIT has discovered a new antibiotic that can be used to kill deadly superbugs in a hospital.
The hacks in question are Acinetobacter baumanniiwhich the World Health Organization has classified as a “severe” threat among the “priority pathogens” – a group of families of bacteria that pose the “greatest threat” to human health.
According to the World Health Organization, bacteria have an intrinsic ability to find new ways to become resistant to treatment and can pass through genetic material that allows other bacteria to become drug-resistant as well.
Bumani It poses a threat to hospitals, nursing homes, patients who need ventilators and blood catheters, as well as those who have open wounds from surgeries.
The bacteria can survive for long periods of time on shared environmental services and equipment, and can often be spread through contaminated hands. In addition to blood infections, Bumani It can cause infections in the urinary tract and lungs.
According to the Centers for Disease Control and Prevention, bacteria can also “colonize” or survive in a patient without causing infections or symptoms.
Thursday’s study revealed that researchers used an artificial intelligence algorithm to screen thousands of antibacterial molecules in an effort to predict new structural classes. As a result of the AI scan, the researchers were able to identify a new antibacterial compound they named abaucin.
“We had a whole bunch of data that was just telling us which chemicals were capable of killing which group of bacteria and which weren’t. My job was to train this model, and all that model was going to do was basically tell us whether the new molecules would be With antibacterial properties or not.
“And then with that, we can just increase the efficiency of the drug discovery pipeline and … hone in on all the molecules that we really want to be interested in,” he added.
After the scientists trained the AI model, they used it to analyze 6,680 compounds it had not encountered before. The analysis took an hour and a half, and ended up yielding several hundred compounds, 240 of which were tested in the lab. Lab tests eventually revealed nine potential antibiotics, including abaucin.
Then the scientists tested the new molecule against Bumani In a rat wound infection model, the molecule was found to inhibit infection.
“This work confirms the benefits of machine learning in the search for new antibiotics,” said Jonathan Stokes, an assistant professor in the Department of Biomedicine and Biochemistry at McMaster University who helped lead the study.
“Using artificial intelligence, we can quickly explore vast regions of chemical space, which greatly increases the chances of discovering fundamentally new antibacterial molecules,” he said.
“We know that broad-spectrum antibiotics are suboptimal and that pathogens have the ability to evolve and adapt to every trick we throw… AI approaches give us the opportunity to dramatically increase our rate of discovery of new antibiotics, and we can do so at a reduced cost. This is a means A mission to explore new antibiotic drugs”.