From APOE Genetics to AI-Designed Drug Candidates: An Integrated Pipeline for Oral, Brain-Penetrant ACAT1 Inhibitors in Alzheimer's Disease
For more than 55 million people living with dementia worldwide, no oral disease-modifying treatment is currently available. Alzheimers disease (AD) remains one of the most urgent unmet needs in neurology, with recent genetic evidence estimating that 72-93% of AD burden is attributable to common APOE allelic variation. Mechanistically, the APOE {varepsilon}4 isoform impairs cholesterol transport in the brain, promoting cholesteryl ester accumulation in microglia; these lipid-laden cells lose phagocytic capacity for amyloid-{beta} clearance and autophagy-mediated degradation of phosphorylated tau, linking a single upstream metabolic disruption to both hallmark pathologies of AD. ACAT1/SOAT1, the brains predominant cholesterol-esterifying enzyme, is an attractive therapeutic target: its inhibition reduces cholesteryl ester formation, restoring microglial A{beta} clearance, reducing A{beta} production, and promoting tau degradation via autophagy, supporting a multimodal mechanism not addressed by currently approved therapies. However, prior ACAT inhibitor programs were limited by isoform non-selectivity, excessive lipophilicity, and lack of CNS optimization. Addressing these constraints, we present the CuraGenAI Drug Discovery Platform for the design of oral, brain-penetrant ACAT1-targeted small-molecule candidates. The pipeline integrates scaffold-constrained generative chemistry with multi-objective ADMET optimization across more than 30 criteria. From approximately 6 million generated molecules, multi-stage filtering yielded approximately 7,300 CNS-optimized candidates with predicted oral brain-penetrant profiles distinct from prior ACAT clinical compounds. Three nominated lead candidates showed predicted BBB probabilities >0.93, favorable CNS drug-like physicochemical profiles, and stable ACAT1 binding poses, and are prioritized for synthesis and in vitro validation.