Artificial Intelligence Helps Identify New Antibiotic to Fight Deadly Drug-Resistant Bacteria
Scientists have made a breakthrough in the fight against drug-resistant bacteria using artificial intelligence (AI). Researchers from McMaster University in Ontario, Canada, and the Broad Institute of MIT and Harvard have used an AI algorithm to predict molecules that can neutralize the drug-resistant bacteria Acinetobacter baumannii. The team discovered a potential antibiotic named abaucin that can effectively suppress the growth of this stubborn bacteria on the skin of mice. Although the results are preliminary and need validation in larger studies, researchers believe that the approach used to identify the new drug could work in drug discovery.
The Superbug Targeted by Researchers
Acinetobacter baumannii is a superbug that can cause infections in the blood, urinary tract, and lungs. This bacteria commonly invades hospitals and healthcare settings, infecting vulnerable patients on breathing machines, in intensive care units, and undergoing operations. This type of bacteria is resistant to the potent antibiotic carbapenem and infected 8,500 people in hospitals and killed 700 in 2017, according to the Centers for Disease Control and Prevention.
How AI Pinpointed a New Antibiotic
The team evaluated 7,684 drugs and the active ingredients of drugs to find out which ones would be effective against the bacteria grown in the lab. The lab team developed AI models to predict which drugs would have the highest likelihood of antimicrobial activity, narrowing the field to 240 drugs or active ingredients. Researchers then narrowed the field again through testing before discovering a molecule RS102895, renamed abaucin, that appeared to be potent against the superbug.
What’s Next for Abaucin?
According to Jonathan Stokes, lead author on the paper and an assistant professor of biomedicine and biochemistry at McMaster University, researchers are working to optimize the chemical structure of the potential antibiotic. Plans call for doing follow-up research in larger animals and potentially humans if abaucin proves to be effective. Stokes said that it’s important to remember that when developing a drug, it not only has to kill the bacterium but also has to be well-tolerated in humans and get to the infection site and stay there long enough to elicit an effect.
The Advantages of Using Machine Learning Techniques
Researchers said they can screen a much larger volume of potential drugs by using machine-learning techniques. While existing high-throughput screening can evaluate a few million drugs or chemical ingredients at once, algorithms developed from machine learning can assess hundreds of millions to billions of drug molecules. This could help researchers to identify new antibiotics and other drugs faster and more efficiently.
The discovery of a new antibiotic to fight drug-resistant bacteria using artificial intelligence is a significant breakthrough in the field of drug discovery. Although the discovery of abaucin is still in the early stages, the use of AI to identify a potential new drug could revolutionize the way researchers discover new antibiotics and other drugs. AI has the potential to help us tackle some of the biggest challenges facing medicine today, such as drug-resistant bacteria, cancer, and other diseases.
- Artificial intelligence and antibiotic discovery
- Machine learning and hospital-acquired infections
- AI-driven drug development for bacterial infections
- Antibiotic resistance and intelligent drug discovery
- Computer-assisted drug design for combating superbugs
News Source : , USA TODAY
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