Communications ChemistryCell BiologyPeer-reviewed journal article
A small molecule enhances arrestin-3 binding to the β2-adrenergic receptor
Han KurtiD, Ali AkyoliD, Çağdaş Devrim SoniD, Chen ZhengiD, Irene GadoiD, Massimiliano MeliiD, Erica Elisa FerrandiiD, Ivan BassaniniiD, Francesca VasileiD, Vsevolod V. GurevichiD, Aylin NeboliD, Esra ÇağaviiD, Giulia MorraiD, Özge ŞensoyiD
Abstract
G protein-coupled receptor (GPCR) signaling is terminated by arrestin binding to a phosphorylated receptor. Binding propensity has been shown to be modulated by stabilizing the pre-activated state of arrestin through point mutations or C-tail truncation. Here, we hypothesize that pre-activated rotated states can be stabilized by small molecules, and this can promote binding to phosphorylation-deficient receptors, which underly a variety of human disorders. We performed virtual screening on druggable pockets identified on pre-activated conformations in Molecular Dynamics trajectories of arrestin-3, and found a compound targeting an activation switch, the back loop at the inter-domain interface. According to our model, consistent with available biochemical and structural data, the compound destabilized the ionic lock between the finger and the back loop, and enabled transition of the gate loop towards the pre-activated state, which stabilizes pre-activated inter-domain rotation. The predicted binding pocket is consistent with saturation-transfer difference NMR data indicating close contact between the piperazine moiety of the compound and C/finger loops. The compound increases in-cell arrestin-3 binding to phosphorylation-deficient and wild-type {beta}2-adrenergic receptor, but not to muscarinic M2 receptor, as verified by FRET and NanoBiT. This study demonstrates that the back loop can be targeted to modulate interaction of arrestin with phosphorylation-deficient GPCRs in a receptor-specific manner.
- organism: human
- assay: structural biology
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 4
- FWCI
- 1.20
- Field percentile
- top 24%
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