AI-driven discovery of brain-penetrant Galectin-3 inhibitors for Alzheimer's disease therapy

Galectin-3 (Gal-3) has emerged as a critical regulator of neuroinflammation and a promising therapeutic target for Alzheimer's disease (AD). Nevertheless, the development of brain-penetrant small-molecule Gal-3 inhibitors poses a significant challenge. To address this, we employed an artificial intelligence (AI)-driven drug discovery platform, identifying FJMU1887 as a novel Gal-3 inhibitor possessing optimized pharmacokinetic properties and favorable blood-brain barrier (BBB) permeability. Following AI-based virtual screening and structure prioritization, FJMU1887 demonstrated direct binding to Gal-3 with an affinity (Kd) of 1.55 μM, determined by microscale thermophoresis (MST). Crucially, mechanistic studies revealed that FJMU1887 disrupts the Gal-3-TREM2 interaction, as evidenced by fluorescence resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) assays. In vitro, FJMU1887 suppressed inflammatory responses in BV-2 microglial cells, inhibiting TNF-α with an IC₅₀ of 2.36 ± 0.37 μM, without inducing cytotoxicity. Pharmacokinetic assessments via parallel artificial membrane permeability assay for BBB (PAMPA-BBB) and in situ brain perfusion revealed effective blood-brain barrier penetration by FJMU1887, though partial P-glycoprotein-mediated efflux was observed. In vivo, 30-day oral administration of FJMU1887 to 14-month-old 5 ×FAD mice significantly reduced Gal-3 expression, attenuated microglial activation and neuroinflammation, decreased amyloid-β burden, and restored synaptic integrity. Notably, FJMU1887 improved cognitive performance in both 5 ×FAD and oligomeric Aβ-induced cognitive impairment mouse models across multiple behavioral paradigms. Collectively, FJMU1887 represents a brain-penetrant small-molecule Gal-3 inhibitor with dual anti-neuroinflammatory and cognition-enhancing effects, establishing it as a promising lead compound for AD therapy.