In vitro and in silico characterization of the inhibition of Kir4.1 channels by aminoglycoside antibiotics

氨基糖苷类抗生素对 Kir4.1 通道抑制的体外和计算机模拟表征

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作者:Rita Morán-Zendejas, Mayra Delgado-Ramírez, Jie Xu, Belkis Valdés-Abadía, Iván A Aréchiga-Figueroa, Meng Cui, Aldo A Rodríguez-Menchaca

Background and purpose

Aminoglycoside antibiotics are positively charged molecules that are known to inhibit several ion channels. In this study, we have shown that aminoglycosides also inhibit the activity of Kir4.1 channels. Aminoglycosides inhibit Kir4.1 channels by a pore-blocking mechanism, plugging the central vestibule of the channel. Experimental approach: Patch-clamp recordings were made in HEK-293 cells transiently expressing Kir4.1 channels to analyse the effects of gentamicin, neomycin and kanamycin. In silico modelling followed by mutagenesis were realized to identify the residues critical for aminoglycosides binding to Kir4.1. Key

Purpose

Aminoglycoside antibiotics are positively charged molecules that are known to inhibit several ion channels. In this study, we have shown that aminoglycosides also inhibit the activity of Kir4.1 channels. Aminoglycosides inhibit Kir4.1 channels by a pore-blocking mechanism, plugging the central vestibule of the channel. Experimental approach: Patch-clamp recordings were made in HEK-293 cells transiently expressing Kir4.1 channels to analyse the effects of gentamicin, neomycin and kanamycin. In silico modelling followed by mutagenesis were realized to identify the residues critical for aminoglycosides binding to Kir4.1. Key

Results

Aminoglycoside antibiotics block Kir4.1 channels in a concentration- and voltage-dependent manner, getting access to the protein from the intracellular side of the plasma membrane. Aminoglycosides block Ki4.1 with a rank order of potency as follows: gentamicin ˃ neomycin ˃ kanamycin. The residues T128 and principally E158, facing the central cavity of Kir4.1, are important structural determinants for aminoglycosides binding to the channel, as determined by our in silico modelling and confirmed by mutagenesis experiments.

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