Scientific research has taken a significant step forward in the battle against antibiotic-resistant bacteria, thanks to artificial intelligence (AI).
Scientists from the Massachusetts Institute of Technology (MIT) have unveiled a new class of compounds capable of defeating methicillin-resistant Staphylococcus aureus (MRSA), which is responsible for over 10,000 deaths annually in the United States. Their research, published in the journal
Nature, demonstrates the effectiveness of these compounds both in laboratory cultures and in mouse models infected with the bacteria. Moreover, these compounds exhibit low toxicity towards human cells, making them valuable drug candidates.
MIT researchers have used AI to discover compounds capable of eliminating multi-drug resistant golden staph, a deadly bacterium, while being safe for human cells.
Image Wikimedia This success is based on the use of deep learning, a type of artificial intelligence, which has identified chemical structures associated with antimicrobial activity among millions of compounds. A key innovation of this study is the researchers' ability to understand the information used by the AI model to predict the antibiotic potency of the molecules, thus facilitating the design of potentially more effective new drugs.
The MIT Antibiotics-AI project, led by James Collins, aims to discover new classes of antibiotics capable of combating seven types of deadly bacteria over a period of seven years. The promising results of this research open exciting prospects for the development of innovative treatments against multi-drug resistant staphylococcus aureus, a bacterium causing skin infections or pneumonia.
The identified compounds appear to act by disrupting the bacteria's ability to maintain an essential electrochemical gradient for many cellular functions.
The researchers have shared their findings with Phare Bio, a non-profit organization, to further analyze the chemical properties and possible clinical use of these compounds. Meanwhile, the James Collins laboratory continues to develop additional drug candidates, illustrating the transformative impact of AI in the discovery of new antibiotics.