2023-12-21 17:45:56
In recent times, many bacteria have become resistant to antibiotics that in the past exterminated them, while very few new antibiotics have been added to the pharmacological arsenal with which to combat microbes.
To help find new antibiotics and combat this growing public health problem, some scientists are seeking the help of artificial intelligence.
Using a type of artificial intelligence known as deep learning, researchers have discovered a class of compounds that can kill a drug-resistant bacteria that causes thousands of deaths each year.
The team, including Felix Wong and James Collins, both from the Massachusetts Institute of Technology (MIT) in the United States, has proven that these compounds can kill methicillin-resistant Staphylococcus aureus (a bacteria also known as MRSA). cultured in a Petri dish and in two mouse models of MRSA infection.
These two compounds also show high toxicity in human cells, making them good drug candidates.
In this image, captured using an electron microscope and then processed in color, the golden balls are MRSA bacteria attacking a human cell, shown in red. (Image: US National Institute of Allergy and Infectious Diseases)
The study is titled “Discovery of a structural class of antibiotics with explainable deep learning.” And it has been published in the academic journal Nature.
For some years now, Collins and his colleagues have been using deep learning to try to find new antibiotics. Before the recent discovery of candidates against MRSA, they found potential drugs against Acinetobacter baumannii, a bacteria commonly found in hospitals, and against other drug-resistant bacteria. (Source: NCYT from Amazings)
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