Using AI, scientists at MIT and McMaster University have discovered a new antibiotic that shows promise in combating drug-resistant infections caused by Acinetobacter baumannii, a bacterium commonly found in hospital settings. This bacterium is known to cause serious infections such as pneumonia and meningitis, and it is a leading cause of infections in injured soldiers. The researchers utilized a machine-learning algorithm to analyze a library of around 7,000 potential drug compounds and identify one that could inhibit the growth of A. baumannii.
The newly discovered antibiotic, named abaucin, demonstrated potent effectiveness against A. baumannii in laboratory tests and also proved successful in treating wound infections caused by the bacterium in mice. Importantly, abaucin displayed a "narrow spectrum" of activity, meaning it targeted A. baumannii specifically without affecting other beneficial bacteria or leading to rapid resistance development. The researchers believe that abaucin's selectivity may be due to slight differences in how A. baumannii performs certain cellular processes compared to other bacteria.
The team plans to further optimize abaucin's medicinal properties in collaboration with researchers at McMaster University for future use in patients. They also intend to employ their modeling approach to identify potential antibiotics for other drug-resistant infections caused by pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa.
The research was supported by various organizations and foundations, including the David Braley Center for Antibiotic Discovery, the Weston Family Foundation, the Audacious Project, and the Canadian Institutes of Health Research, among others.
