Development and Applications of Glycosaminoglycan Microarray Technology

Glycosaminoglycans (GAGs) are structurally diverse, negatively charged polysaccharides that regulate biological processes through interactions with proteins such as growth factors, receptors, and viral proteins. Their variability in chain length and sulfation enables selective recognition, contributing to diseases including cancer and viral infection. However, systematic investigation of GAG–protein interactions remain challenging due to structural heterogeneity and limitations of traditional low-throughput analytical methods. This work advances GAG microarray technology as a high-throughput platform for parallel analysis of GAG–protein binding. Using minimal sample quantities, this approach enabled evaluation of binding selectivity, affinity, and mechanism through three major applications. First, screening of 55 heparan sulfate (HS) mimetics identified a highly sulfated monosaccharide (B31) as the smallest known structure capable of binding the SARS-CoV-2 spike protein across multiple variants (WT, delta, omicron). Binding was validated through on-array and solution-based studies, revealing nanomolar affinity and conserved electrostatic interactions among variants. Second, a reproducible hydrazide-based microarray platform for native GAGs was developed through systematic optimization of immobilization conditions. This enabled consistent attachment of 32 structurally diverse GAGs, ranging from disaccharides to polysaccharides. Finally, this platform was applied to 23 cancer-associated receptors. Detailed studies of three selected receptors insulin-like growth factor 1 receptor (IGF-1R), vascular endothelial growth factor receptor 1 (VEGFR1), and transforming growth factor beta receptor 2 (TGFBR2), revealed distinct binding mechanisms, including competitive, allosteric, and ligand-mediated ternary interactions, demonstrating how GAG structure may modulate receptor interactions. Collectively, this work establishes GAG microarrays as quantitative tools for elucidating GAG–protein interactions and enabling therapeutic discovery.