Stanford Scientists Discover 'Natural Ozempic' That Suppresses Appetite Without Side Effects

Stanford Medicine researchers have identified a naturally occurring molecule that appears to mimic the appetite-suppressing effects of popular weight loss drugs like Ozempic, but without many of the troublesome side effects that plague current treatments. The molecule, called BRP, demonstrated significant weight reduction in animal studies while avoiding the nausea, constipation, and muscle loss commonly associated with semaglutide-based medications. The discovery, published in Nature, represents a potential breakthrough in obesity treatment and highlights the power of artificial intelligence in drug discovery.

The research team, led by assistant professor of pathology Katrin Svensson, used AI to analyze thousands of potential peptide hormones derived from prohormones. These molecules are initially inactive but can be split into smaller fragments that function as hormones influencing metabolism in the brain and body. The challenge lay in distinguishing useful signaling molecules from the many inactive fragments created during normal protein breakdown, a task that would be extremely difficult using traditional laboratory methods alone.

BRP works through a different but related biological pathway compared to semaglutide, activating distinct groups of neurons in the brain's hypothalamus, which controls appetite and metabolism. While semaglutide targets receptors found throughout the body including the gut and pancreas, causing widespread effects like slowed digestion and blood sugar changes, BRP appears to act specifically in the brain's appetite control center. This targeted approach could explain why the molecule avoids many side effects that limit the tolerability of current weight loss medications.

The team developed a computer tool called Peptide Predictor that scanned all 20,000 human protein-coding genes to identify where prohormones could be cut into active peptides. This algorithm identified 2,683 possible peptides from 373 prohormones, which researchers then tested on lab-grown brain cells. The AI-driven approach proved essential to the discovery, as Svensson noted that traditional methods would have made such comprehensive screening nearly impossible.

Svensson, who has co-founded a company planning to begin human clinical trials soon, emphasized that the molecule's brain-specific action represents a key advantage over existing treatments. The research demonstrates how artificial intelligence can accelerate the discovery of novel therapeutic compounds by efficiently sorting through vast molecular libraries. While the findings are promising, the transition from animal studies to human applications will require extensive clinical testing to confirm both safety and efficacy in treating human obesity.