AI Foresaw Function of Novel Antibiotic Targeting Inflammatory Bowel disease
HAMILTON, ON – In a groundbreaking convergence of artificial intelligence and biomedical research, scientists at McMaster University have identified a new antibiotic target with the potential to treat inflammatory bowel disease (IBD).Remarkably, an AI model accurately predicted how the antibiotic would function before researchers could experimentally confirm it, marking a significant leap forward in drug discovery. The findings, published in[publicationname-[publicationname-[publicationname-[publicationname-source material needed to complete], offer a promising new avenue for treating the debilitating condition affecting millions worldwide.
IBD, encompassing Crohn’s disease and ulcerative colitis, causes chronic inflammation of the digestive tract, leading to abdominal pain, diarrhea, and fatigue. Current treatments frequently enough involve immunosuppressants with significant side effects, or, in severe cases, surgery. This research focuses on a previously overlooked bacterial enzyme crucial for the survival of Klebsiella pneumoniae, a bacterium increasingly implicated in IBD flare-ups. The AI’s prediction centered on the enzyme’s role in bacterial iron uptake – a function now validated by the McMaster team.
“We were astonished by the accuracy of the AI’s prediction,” explains Dr. Eric Brown, lead investigator and professor in the Department of Biochemistry and Biomedical Sciences at McMaster University. “It essentially told us why inhibiting this enzyme would be effective against Klebsiella pneumoniae in the context of IBD, and then our experiments confirmed it.”
The research team utilized a machine learning model trained on vast datasets of bacterial genomes and biochemical reactions. This allowed the AI to identify the enzyme as a potential drug target and predict its mechanism of action with unprecedented precision. Subsequent laboratory tests demonstrated that inhibiting the enzyme considerably reduced Klebsiella pneumoniae growth and its ability to exacerbate inflammation in preclinical models of IBD.
The next steps involve developing and testing specific inhibitors of the enzyme, with the ultimate goal of creating a new class of antibiotics tailored to treat IBD and possibly other infections caused by Klebsiella pneumoniae. This approach, combining AI-driven prediction with rigorous experimental validation, represents a paradigm shift in antibiotic discovery, offering a faster and more efficient pathway to tackling the growing threat of antibiotic resistance and chronic inflammatory diseases.
