A study led by the Perelman School of Medicine uses AI to advance antibiotic discovery, analyzing extensive genomic data to identify nearly a million potential compounds. This approach has revealed many promising candidates that could lead to effective new treatments for antibiotic-resistant bacteria.
Researchers at Penn Medicine analyzed genomic data to discover new antibiotics within the global microbiome.
Nearly a century after the groundbreaking introduction of antibiotics such as penicillin, which transformed medicine by tapping into the natural antibacterial properties of microbes, a new study led by the Perelman School of Medicine at the University of Pennsylvania indicates natural-product antibiotic discovery is about to accelerate into a new era, powered by DOI: 10.1016/j.cell.2024.05.013
The team has published their repository of putative antimicrobial sequences, which they call AMPSphere, which is open access and freely available at https://ampsphere.big-data-biology.org/
The research was supported by the National Key R&D Program of China (2020YFA0712403, 2018YFC0910500); the National Natural Science Foundation of China (61932008, 61772368); Shanghai Science and Technology Innovation Fund (19511101404); Shanghai Municipal Science and Technology Major Project (2018SHZDZX01); The Science and Technology Commission of Shanghai Municipality (22JC1410900); The Australian Research Council (FT230100724); the AIChE Foundation; the