AI helps Stanford scientists discover “natural Ozempic” without the usual side effects | ScienceDaily

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AI helps Stanford scientists discover “natural Ozempic” without the usual side effects

An AI-discovered natural molecule may deliver Ozempic-like weight loss without nausea, constipation, or significant muscle loss.

Date:<br>July 24, 2026<br>Source:<br>Stanford Medicine<br>Summary:<br>Stanford Medicine researchers have discovered a naturally occurring molecule that may suppress appetite and reduce body weight much like Ozempic, but without several of its common side effects. The molecule, called BRP, acts on a more targeted region of the brain involved in hunger and metabolism rather than affecting tissues throughout the body.<br>Share:

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Scientists have identified a natural molecule that produced Ozempic-like appetite suppression and fat loss in animals without several of the drug’s common side effects. Credit: Shutterstock

Stanford Medicine researchers have identified a naturally occurring molecule that may suppress appetite and reduce body weight in a way that resembles semaglutide, the active ingredient in Ozempic. In animal studies, the molecule also appeared to avoid several problems associated with the drug, including nausea, constipation and substantial muscle loss.

The molecule, known as BRP, works through a different but related metabolic pathway and activates a separate group of neurons in the brain. That distinction could make it a more precise tool for controlling appetite and body weight.

A More Targeted Approach to Appetite Control

"The receptors targeted by semaglutide are found in the brain but also in the gut, pancreas and other tissues," said assistant professor of pathology Katrin Svensson, PhD. "That's why Ozempic has widespread effects including slowing the movement of food through the digestive tract and lowering blood sugar levels. In contrast, BRP appears to act specifically in the hypothalamus, which controls appetite and metabolism."

The hypothalamus is a small region deep within the brain that helps regulate hunger, body temperature, hormone activity and energy use. Because BRP appears to act mainly in this area, it may influence appetite without producing as many effects elsewhere in the body.

Svensson has co-founded a company that plans to begin clinical trials of the molecule in humans in the near future.

Svensson is the senior author of the research, which was published March 5 in Nature. Senior research scientist Laetitia Coassolo, PhD, is the lead author of the study.

Artificial Intelligence Reveals Hidden Peptides

The discovery depended heavily on artificial intelligence, which allowed the researchers to search through proteins belonging to a group known as prohormones.

Prohormones are inactive precursor molecules. They do not perform their final biological function until enzymes cut them into smaller fragments called peptides. Some of these peptides then act as hormones, carrying signals that influence metabolism, appetite and other complex processes in the brain and throughout the body.

A single prohormone can be cut in several different ways, producing many possible peptides. Finding the biologically important ones is difficult because genuine peptide hormones are relatively rare and can be buried among large numbers of ordinary fragments created during normal protein processing and breakdown.

Traditional laboratory methods can isolate and identify peptides, but the process can produce enormous amounts of data. Researchers may need to sort through hundreds of thousands of molecules to find the few that have meaningful effects.

Searching for New Metabolic Signals

The team concentrated on an enzyme called prohormone convertase 1/3. This enzyme cuts prohormones at specific amino acid sequences and has previously been linked to obesity in humans.

One of the peptides produced through this process is glucagon-like peptide 1, or GLP-1. GLP-1 helps regulate hunger and blood sugar, and semaglutide works by copying its effects in the body.

The researchers reasoned that the same enzyme might produce other peptides that influence energy balance and appetite. To find them, they turned to artificial intelligence.

Peptide Predictor

Rather than manually extracting proteins and peptides from tissues and then using methods such as mass spectrometry to identify huge numbers of molecules, the researchers created a computer algorithm called Peptide Predictor.

The program searched all 20,000 human protein-coding genes for the types of sites where prohormone convertases typically cut proteins. The researchers then narrowed the search to genes that produce proteins secreted outside the cell, a common feature of hormones, and that contained at least four possible cleavage sites.

That process reduced the field to 373 prohormones, giving the team a much more manageable group to...