AI Discovers Appetite-Suppressing Peptide with Innovative Mechanism

The regulation of appetite and satiety is a highly intricate process, and pharmacological interventions may target various biological pathways to achieve effective control. Recent advancements in artificial intelligence (AI) have enabled researchers to explore these pathways more efficiently.

Identifying coding regions for proteins in the human genome is relatively straightforward, thanks to decades of bioinformatics tools. However, within these proteins, there often exist peptides that exhibit significant biological activity. A notable example is the glucagon-like peptide-1 (GLP-1), which is synthesized as part of a larger precursor protein consisting of 180 amino acids. Proteolytic enzymes subsequently cleave this precursor to yield various bioactive peptides.

In a groundbreaking study, researchers at Stanford University utilized AI to discover a peptide that mimics the appetite-suppressing effects of GLP-1 in animal models. By training a specialized AI tool to specifically search for prohormonal cleavage sites, the team systematically mapped proteolytic fragments within the human proteome. This led to the identification of over 2,600 potentially bioactive peptides derived from 373 different proteins. Among these was a previously unknown peptide with anti-adipogenic properties, termed BRINP2-related peptide (BRP), consisting of just twelve amino acids. This peptide is cleaved from the BRINP2 protein by proprotein convertase 1 (PCSK1) and is detectable in the brain and cerebrospinal fluid.

In their experiments, the researchers administered the peptide through intramuscular injections to lean mice and miniature pigs prior to feeding. The results showed a remarkable reduction in food intake, with animals consuming up to 50% less within the following hour. Furthermore, in models of obesity, the peptide induced significant weight loss without the common gastrointestinal side effects associated with GLP-1 analogs.

This discovery opens new avenues for the development of anti-obesity therapies that could provide effective appetite regulation without adverse effects. The potential for such treatments could significantly impact public health, addressing the rising prevalence of obesity and its associated complications.

As research continues, understanding the mechanisms by which this peptide operates will be crucial for creating targeted treatments aimed at appetite regulation and weight management. The implications of these findings could lead to innovative strategies in combating obesity and improving metabolic health.