Carpintero-Fernández, PaulaVarela-Eirín, MartaLacetera, AlessandraGago-Fuentes, RaquelFonseca, EduardoMartín-Santamaría, SonsolesMayán, María D.2026-04-082026-04-082020-04-21Carpintero-Fernandez, P., Varela-Eirin, M., Lacetera, A., Gago-Fuentes, R., Fonseca, E., Martin-Santamaria, S., & Mayan, M. D. (2020). New Therapeutic Strategies for Osteoarthritis by Targeting Sialic Acid Receptors. Biomolecules, 10(4), 637. https://doi.org/10.3390/biom100406372218-273Xhttps://hdl.handle.net/2183/47905[Abstract] Osteoarthritis (OA) is the most common degenerative joint disease characterized by articular cartilage degradation and joint degeneration. The articular cartilage is mainly formed by chondrocytes and a collagen-proteoglycan extracellular matrix that contains high levels of glycosylated proteins. It was reported that the shift from glycoproteins containing α-2,6-linked sialic acids to those that contain α-2,3 was associated with the onset of common types of arthritis. However, the pathophysiology of α-2,3-sialylation in cartilage has not been yet elucidated. We show that cartilage from osteoarthritic patients expresses high levels of the α-2,3-sialylated transmembrane mucin receptor, known as podoplanin (PDPN). Additionally, the Maackia amurensis seed lectin (MASL), that can be utilized to target PDPN, attenuates the inflammatory response mediated by NF-kB activation in primary chondrocytes and protects human cartilage breakdown ex vivo and in an animal model of arthritis. These findings reveal that specific lectins targeting α-2,3-sialylated receptors on chondrocytes might effectively inhibit cartilage breakdown. We also present a computational 3D molecular model for this interaction. These findings provide mechanistic information on how a specific lectin could be used as a novel therapy to treat degenerative joint diseases such as osteoarthritis.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Articular chondrocyteCartilageSialylationOsteoarthritisArthritisMASLPodoplaninGlycoproteinsMolecular modellingjournal articleopen access10.3390/biom10040637