Triazolo[4,5-d]pyrimidin-5-amines based ERK3 inhibitors fail to demonstrate selective effects on adipocyte function

• Published in: Archives of biochemistry and biophysics Vol. 751; p. 109825
• Main Authors: Belykh, Andrei, Hawro, Izabela, Kolczyńska-Matysiak, Katarzyna, Loza-Valdes, Angel, Mieczkowski, Adam, Sumara, Grzegorz
• Format: Journal Article
• Language: English
• Published: United States 01.01.2024
• Subjects: Adipocytes; Lipolysis; Inhibitors; Adipocytes; Triazolo[4,5-d]pyrimidin-5-amines; MAPK6; Metabolism; ERK3
• ISSN: 0003-9861; 1096-0384
• DOI: 10.1016/j.abb.2023.109825

Extracellular signal-regulated kinase 3 (ERK3 also designated MAPK6 - mitogen-activated protein kinase 6) is a ubiquitously expressed kinase participating in the regulation of a broad spectrum of physiological and pathological processes. Targeted inhibition of the kinase may allow the development of novel treatment strategies for a variety of types of cancer and somatic pathologies, as well as preserving metabolic health, combat obesity and diabetes. We chose and synthesized three triazolo [4,5-d]pyrimidin-5-amines proposed previously as putative ERK3 inhibitors to assess their selectivity and biological effects in terms of metabolic state impact in living cells. As it was previously shown that ERK3 is a major regulator of lipolysis in adipocytes, we focused on this process. Our new results indicate that in addition to the previously identified lipolytic enzyme ATGL, ERK3 also regulates hormone-sensitive lipase (HSL) and monoglyceride lipase (MGL). Moreover, this kinase also promotes the abundance of fatty acid synthase (FASN) as well as protein kinase cAMP-activated catalytic subunit alpha (PKACα). To investigate various effects of putative ERK3 inhibitors on lipolysis, we utilized different adipocyte models. We demonstrated that molecules exhibit lipolysis-modulating effects; however, the effects of triazolo [4,5-d]pyrimidin-5-amines based inhibitors on lipolysis are not dependent on ERK3. Subsequently, we revealed a wide range of the compounds' possible targets using a machine learning-based prediction. Therefore, the tested compounds inhibit ERK3 in vitro, but the biological effect of this inhibition is significantly overlapped and modified by some other molecular events related to the non-selective binding to other targets.