Current Alzheimer’s disease therapies offer limited efficacy and are often accompanied by significant side effects, underscoring the urgent need for new treatment strategies. Enhancing autophagy represents a promising therapeutic approach, yet most known autophagy inducers act through the mTOR-dependent pathway, which broadly affects cellular metabolism and proliferation, and their clinical potential is further limited by poor blood-brain barrier (BBB) penetration. To address these twin challenges, an artificial intelligence (AI)-driven platform named DeepDrugDiscovery was developed, shifting the focus from traditional structure-based screening toward a mechanism-centric strategy for identifying mTOR-independent autophagy enhancers with brain penetrability. The platform screened over one million molecules and identified two lead compounds, Ombuin and 2-Hydroxycinnamic acid, which were experimentally shown to clear pathogenic tau and amyloid-β aggregates and restore memory function in both worm and mouse models of Alzheimer’s disease. Notably, Ombuin exhibited robust brain exposure, confirming accurate BBB prediction. Released as an open-source resource, DeepDrugDiscovery demonstrates a scalable, AI-powered pipeline for discovering mechanism-based therapeutics.
