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oai:docta.ucm.es:20.500.14352/1024152025-03-18T13:25:49Zcom_20.500.14352_14col_20.500.14352_15

Exploring the 1,3-benzoxazine chemotype for cannabinoid receptor 2 as a promising anti-cancer therapeutic Gambacorta, Nicola Gasperi, Valeria Guzzo, Tatiana Saverio Di Levada, Francesco Ciriaco, Fulvio Sánchez García, María Cristina Tullio, Valentina Rozzi, Diego Marinelli, Luciana Topai, Alessandra Nicolotti, Orazio Maccarrone, Mauro 577.1 615.9 1,3-Benzoxazin-4-one Inflammation Cancer CB2 Neurodegenerative disorders Neuropathic pain Bioquímica (Biología) Oncología 2403 Bioquímica 3201.01 Oncología The discovery of selective agonists of cannabinoid receptor 2 (CB2) is strongly pursued to successfully tuning endocannabinoid signaling for therapeutic purposes. However, the design of selective CB2 agonists is still challenging because of the high homology with the cannabinoid receptor 1 (CB1) and for the yet unclear molecular basis of the agonist/antagonist switch. Here, the 1,3-benzoxazine scaffold is presented as a versatile chemotype for the design of CB2 agonists from which 25 derivatives were synthesized. Among these, compound 7b5 (CB2 EC50 = 110 nM, CB1 EC50 > 10 μM) demonstrated to impair proliferation of triple negative breast cancer BT549 cells and to attenuate the release of pro-inflammatory cytokines in a CB2-dependent manner. Furthermore, 7b5 abrogated the activation of extracellular signal-regulated kinase (ERK) 1/2, a key pro-inflammatory and oncogenic enzyme. Finally, molecular dynamics studies suggested a new rationale for the in vitro measured selectivity and for the observed agonist behavior. Italian Ministry of University and Research (MUR) University of L'Aquila Università degli Studi di Bari (Bari, Italy) Horizon Europe Seeds Regione Lazio – DTB – Fondi CIPE Depto. de Bioquímica y Biología Molecular Fac. de Ciencias Biológicas TRUE pub 2024-03-20T12:02:07Z 2024-03-20T12:02:07Z 2023-07-14 journal article VoR https://hdl.handle.net/20.500.14352/102415 0223-5234 10.1016/j.ejmech.2023.115647 eng (PRIN 2017-2017BTHJ4R) (CUP: H99J21017390006) (DISCAB GRANT 07_DG_2022_12) (NUMORECA PROJECT) restricted access application/pdf Elsevier