A Stanford team has identified a promising natural molecule against obesity. Unlike current treatments, it appears to avoid certain troublesome side effects.
Scientists used artificial intelligence to discover the BRP molecule among thousands of peptides. This innovative approach allowed them to specifically target metabolic pathways related to appetite, without affecting other bodily functions as similar medications do.
BRP primarily acts in the hypothalamus, a crucial brain region for hunger regulation. Animal tests showed significant reductions in food intake and weight loss, without the nausea or muscle loss observed with other treatments.
The molecule was identified using an algorithm called Peptide Predictor, which analyzes prohormone cleavage sites. This method enabled the selection of 373 prohormones from 20,000 genes, a feat impossible with traditional techniques.
Tests on mice and pigs confirmed BRP's effectiveness. Treated animals lost weight primarily in fat while improving glucose tolerance. No notable side effects were observed, paving the way for human clinical trials.
Researchers now plan to identify BRP's specific receptors and improve its duration of action in the body. These steps are crucial for developing a practical and effective obesity treatment.
This discovery, published in
Nature, represents a major advance in the fight against obesity. With millions affected worldwide, BRP could offer a safer, more targeted alternative to current treatments.
How did artificial intelligence help discover BRP?
The Stanford team developed an algorithm, Peptide Predictor, to analyze prohormone cleavage sites. This tool predicted how a specific enzyme, prohormone convertase 1/3, cleaves prohormones into active peptides.
Traditionally, identifying these peptides required laborious and expensive techniques. Peptide Predictor accelerated this process by automatically analyzing amino acid sequences, reducing time and resources needed.
The algorithm identified 2,683 potential peptides from 373 prohormones. This approach allowed researchers to focus on the most promising peptides, including BRP, without manual isolation.
This method demonstrates how AI can significantly accelerate biomedical research by enabling rapid, precise discoveries that would otherwise be nearly impossible.