Researchers have utilized artificial intelligence (AI) to discover a new type of antibiotic that effectively combats drug-resistant bacteria. The antibiotic was tested on mice with experimentally infected superbugs, and it controlled the bacteria’s growth, indicating its potential to create tailored antibiotics against other drug-resistant pathogens. The compound identified by AI was explicitly targeted at the problem pathogen, without harming the beneficial bacteria residing in the gut or on the skin. If more antibiotics exhibit such precision, it could help prevent bacteria from developing resistance. This AI-driven approach to drug discovery significantly reduces the time required to sift through numerous promising compounds, making it an emerging field with great potential.

The study focused on Acinetobacter baumannii, a bacteria commonly found in healthcare settings like hospitals, which can incorporate genes from other organisms and develop resistance to treatment. Acinetobacter baumannii causes challenging-to-treat skin, blood, and respiratory infections. The researchers used high-throughput drug screening to identify 480 compounds that hindered the bacteria’s growth, and AI was employed to train a model that could predict the antibacterial properties of new chemicals.

The search was narrowed down to one compound, RS102895 (renamed abaucin), which appears to work by impeding the movement of bacterial components from inside the cell to its surface. Unlike broad-spectrum antibiotics, abaucin targets Actinetobacter baumannii specifically, reducing the universal selective pressure that drives the quick evolution and sharing of drug-resistance genes among different bacteria species.

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