Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii

Machine learning was used (Liu, G., Catacutan, D.B., Rathod, K. et al. Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii. Nat Chem Biol (2023). https://doi.org/10.1038/s41589-023-01349-8) to develop new antibiotics against Acinetobacter baumannii. This pathogen often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Machine learning allows for the rapid exploration of chemicals, increasing the probability of discovering new antibacterial molecules. Around 7,500 molecules that inhibited the growth of A. baumannii in vitro were screened. Neutral network was used to predict chemical toxicity through computational modeling. This process discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii. Abaucin could control an A. baumannii infection in a mouse wound model. @ https://www.nature.com/articles/s41589-023-01349-8.epdf?sharing_token=RWd0NhirFpy2b2BGPZP5v9RgN0jAjWel9jnR3ZoTv0PgqDK_eQp8NcAST1F90jpq3WEGXG2Su3RGayoL_4HVm-885WktBHURHlCxulwlcvpyGtITV-DP3D206obw-VwWHxYxnDYB7coCRf0l466lVvYqSrbMGRSnrbQLgtJwzb9l1g8rqpxmCL-4_-k8FciBA9RvvjphptrsdaCOzV6I-g%3D%3D&tracking_referrer=www.bbc.com

 Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii

Nature Chemical Biology – Using a neural network trained on bacterial growth inhibition data, in silico prediction of molecules with activity against Acinetobacter baumannii led to the…

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