An MIT team used artificial intelligence to design novel antibiotics, two of which showed promise against MRSA and gonorrhea. With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat bacteria: multi-drug-resistant and (MRSA). The team used two approaches. First, they directed generative AI to design molecules based on a chemical fragment their model had predicted would show antimicrobial activity, and second, they let the algorithms generate molecules without constraints. They designed more than 36 million possible compounds this way and computationally screened them for antimicrobial properties. The top candidates they discovered are structurally distinct from any existing antibiotics, and they appear to work by novel mechanisms that disrupt bacterial cell membranes.

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research team designed more than 36 million possible compounds and computationally screened them for antimicrobial properties. The top candidates they discovered are structurally distinct from any existing antibiotics, and they appear to work by novel mechanisms that disrupt bacterial cell membranes. This approach allowed the researchers to generate and evaluate theoretical compounds that have never been seen before -- a strategy that they now hope to apply to identify and design compounds with activity against other species of bacteria. "We're excited about the new possibilities that this project opens up for antibiotics development. Our work shows the power of AI from a drug design standpoint, and enables us to exploit much larger chemical spaces that were previously inaccessible," says James Collins, the Termeer Professor of Medical Engineering and Science in MIT's Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering, and a member of the Broad Institute.

Artificial intelligence has helped discover a new class of antibiotics that can treat infections caused by drug-resistant bacteria. This could help in the battle against antibiotic resistance, which was responsible for killing more than 1.2 million people in 2019 – a number expected to rise in the coming decades. Testing in mice showed that the new antibiotic compounds proved promising treatments for both Methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus – a bacterium that has developed resistance to the drug typically used for treating MRSA infections. "Our [AI] models tell us not only which compounds have selective antibiotic activity, but also why, in terms of their chemical structure," says Felix Wong at the Broad Institute of MIT and Harvard in Massachusetts. Wong and his colleagues set out to show that AI-guided drug discovery could go beyond identifying specific targets that drug molecules can bind to, and instead predict the biological effect of entire classes of drug-like compounds.

Researchers in the US have used artificial intelligence (AI) to discover a powerful new type of antibiotic capable of killing drug-resistant bacteria. Scientists at MIT trained a machine learning algorithm to analyse the molecular structures of chemical compounds and pick out potential antibiotics. The deep learning model was designed to identify compounds capable of killing bacteria using different mechanisms to those of existing drugs. After analysing some 2,500 different molecules, the AI system identified a new antibiotic compound which, in lab tests, killed many of the world's most problematic disease-causing bacteria, including drug-resistant strains. The new antibiotic compound has been dubbed halicin, named after the the rogue AI system, Hal 9000, from 1968 film 2001: A Space Odyssey.

WASHINGTON – In a first, U.S. researchers have used artificial intelligence to identify a powerful new antibiotic capable of killing several drug-resistant bacteria. Antibiotics have been a cornerstone of modern medicine since the discovery of penicillin, but their effectiveness has seriously diminished in recent years as overuse has led to bacteria becoming resistant. The scientists at MIT and Harvard trained a machine-learning algorithm to analyze compounds capable of fighting infections using different mechanisms than those of existing drugs. Their findings were published in the journal Cell. "Our approach revealed this amazing molecule, which is arguably one of the more powerful antibiotics that has been discovered," said James Collins, a professor of medical engineering at MIT and one of the paper's senior authors.