Despite the increasing prevalence of overweight or obesity in the global population, most of the approved drugs for obesity are still not ideal for long-term use due to severe cardiovascular and/or neurological side effects. Therefore, we designed a library-implemented virtual screening (VS) approach to discover new anti-obesity agents without significant toxicity. The Bayesian classification and 3D pharmacophore model for the VS process were built by using the screening results of our in-house library of natural piper amide-like compounds, which possess a wide range of biological activities and relatively low toxicities. The VS process identified six compounds of different classes with enhanced inhibitory activities against lipid accumulation and without toxicity. Moreover, the most active compound with an oxadiazole scaffold resulted in weight loss and improved the fatty liver condition of mice with overnutrition in animal experiments.
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