Scientists have discovered a new antibiotic powered by artificial intelligence. This antibiotic has potential use against fatal hospital-acquired, treatment-resistant infections.
The process developed by researchers, including those at McMaster University in Canada, could pave the way for discovering new antibiotics to treat many other difficult bacteria.
In the study, published in Nature Chemical Biology, scientists urgently sought to develop new drugs for treatment. Acinetobacter baumannii – According to WHO, it is classified as one of the most dangerous drug-resistant bacteria in the world.
This bacterium is known to cause pneumonia, meningitis, and infected wounds, all of which can be fatal.
It has been found in hospital settings, where it persists on surfaces for long periods of time.
Previous studies have also shown that the pathogen is capable of incorporating antibiotic resistance genes from other bacteria.
However, with the development of new antibiotics, Baumani Traditional chemical screening tests have been difficult to use because traditional methods are time consuming and costly.
In a new study, scientists used AI to predict a previously unknown class of antimicrobial molecules and identified a new compound they named abaucin.
Using AI algorithms, researchers have been able to evaluate hundreds of millions, possibly billions, of molecules with antimicrobial properties.
“This study validates the benefits of machine learning in the search for new antibiotics,” said lead study author Jonathan Stokes in a statement.
“AI allows us to rapidly explore vast regions of chemical space, greatly increasing our chances of discovering fundamentally new antimicrobial molecules,” said Dr. Stokes.
Scientists believe new compound abaucin holds promise because it targets only targets Baumani.
Most antibiotics have broad-spectrum activity that affects all bacteria, potentially destroying the body’s beneficial intestinal bacteria and opening the door to serious infections, including deadly bacteria. there is. Difficult C.
targeting Baumani Researchers say combining new drugs may reduce the likelihood of rapid development of drug resistance and help develop new treatments that are precise and effective.
“We know that algorithmic models work. Moving forward, it will be important to broadly adopt these methods to discover new antibiotics more efficiently and at a lower cost,” said another co-author of the study. said James J. Collin, author of
“AI techniques can greatly improve the discovery rate of new antibiotics and reduce costs.
