MIT discovers a powerful antibiotic using machine learning

Massachusetts Institute of Technology (MIT) researchers have discovered a powerful antibiotic compound using their machine-learning algorithm to counter many of the world’s deadliest bacteria, including some strains that are immune to all known antibiotics. It prevented infections in two different mouse models, according to MIT official release.

An advanced computer model that can screen more than a hundred million chemical compounds was used to design potential antibiotics that can kill dangerous bacteria.

Speaking about the discovery, James Collins, the Termeer Professor of Medical Engineering and Science at MIT stated in a press release: “We wanted to develop a platform that would allow us to harness the power of artificial intelligence to usher in a new age of antibiotic drug discovery. He added that the researchers at MIT revealed this “amazing” molecule which is arguably one of the most potent antibiotics that has ever been discovered.

In their recent study, the researchers also identified several other promising antibiotic compounds, which can be put to the test further. They believe the artificial intelligence could also be used to design new drugs, based on what it has learned about chemical structures that enable drugs to kill bacteria.

According to Collins, the research in the field of antibiotics has hit its breakeven point as very few new antibiotics have been developed. Most of those are slightly different variants of existing drugs. He further claimed that the development is prohibitively costly, requires significant time, and limited to a narrow spectrum of chemical diversity.

He also mentioned that experimentation has become more stringent due to the increasing number of pathogens becoming resistant to existing antibiotics, the official release noted.

Discovery of antibiotics

As per the official release, in laboratory tests against five species of bacteria, the researchers found that eight of the molecules showed antibacterial activity, and two were particularly powerful. The researchers now plan to test these molecules further. They will also screen more such antibacterial activities in the molecules to discover new compounds that are not the variant of the existing ones.

The researchers intend to use their model to design new antibiotics and to optimize existing molecules.

Roy Kishony, a professor of biology and computer science at Technion (the Israel Institute of Technology) commented: “This groundbreaking work signifies a paradigm shift in antibiotic discovery and indeed in drug discovery more generally.”

Amused by the discovery, Kishony, who is not a part of the study, said: “Beyond in silica screens, this approach will allow using deep learning at all stages of antibiotic development, from discovery to improved efficacy and toxicity through drug modifications and medicinal chemistry.”