Researchers from the Antibiotics-AI Project at MIT have used Artificial Intelligence to identify a class of compounds capable of combating Methicillin-Resistant Staphylococcus aureus (MRSA), a drug-resistant bacterium responsible for over 10,000 deaths annually in the United States. The study utilised deep learning models trained on an expanded dataset of approximately 39,000 compounds to predict antibiotic activity against MRSA, and a Monte Carlo tree search algorithm to decipher the factors influencing the model’s predictions. This breakthrough allowed them to gain insights into the chemical structures associated with antimicrobial activity, and to explain the information used by the AI model in making antibiotic potency predictions. The researchers screened a vast library of around 12 million commercially available compounds, identifying five different compounds with the potential to combat MRSA.
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