Discovering anti-obesity oligopeptide from functional protein idrs using ai-based computational pipeline

Obesity, as a chronic disease driven by energy imbalance and metabolic dysfunction, has become a global health challenge with an increasing prevalence. Peptides, as biologically active molecules with high potency and low toxicity, play critical roles in regulating diverse physiological and metabolic processes, offering unique therapeutic potential for metabolic and endocrine disorders. In this study, we developed an Artificial Intelligence (AI)-based drug discovery pipeline to identify therapeutic oligopeptide candidates from intrinsically disordered regions (IDRs) of functional proteins. Using this pipeline, we discovered WLP-4, a novel oligopeptide with significant anti-obesity effects. In oil red O staining assays with 3T3-L1 cells, WLP-4 demonstrated superior lipid metabolism-promoting activity compared to the first-line lipid-lowering drug Celastrol. Further, in vivo validation with high-fat diet-induced obesity mouse model, WLP-4 exhibited anti-obesity efficacy comparable to Exendin-4. Additionally, histopathological evaluations of major organs revealed no observable toxicity at therapeutic doses, underscoring the safety of WLP-4. These findings suggest that WLP-4 is a promising therapeutic oligopeptide for anti-obesity and validate the reliability of the computational pipeline. This study provides valuable insights into oligopeptide-based drug discovery and may inspire future efforts to develop treatments for more metabolic diseases.