变构调节
G蛋白偶联受体
磷酸化
效应器
生物
逮捕
细胞生物学
信号转导
计算生物学
受体
生物化学
作者
Midhun K. Madhu,Rajesh K. Murarka
标识
DOI:10.1021/acs.jcim.5c01078
摘要
β-Arrestins (βarr1 and βarr2) are key transducers of G protein-coupled receptor (GPCR) signaling, orchestrating both shared and isoform-specific intracellular pathways. Phosphorylation of the receptor C-terminal tail by GPCR kinases encodes regulatory "barcodes" that modulate β-arrestin conformations and interactions with downstream effectors. However, how distinct phosphorylation patterns shape β-arrestin structure and function remains poorly understood. In this study, we integrate all-atom molecular dynamics simulations with machine learning, including graph neural networks, to systematically characterize the barcode-specific conformational landscape of β-arrestins bound to the phosphorylated vasopressin receptor 2 tail (V2Rpp). We find that V2Rpp engages βarr1 more stably than βarr2, mediated by isoform-specific residue contacts that trigger distinct allosteric responses. These include differential interdomain rotations and rearrangements in key structural motifs, potentially facilitating selective effector protein engagement. Furthermore, we identify critical residue networks that transmit phosphorylation signals to effector-binding interfaces in a barcode- and isoform-specific manner. Notably, βarr1 exhibits stronger allosteric coupling between V2Rpp and c-edge loop 2 compared to βarr2, which is consistent with its enhanced membrane association. Together, these findings advance our understanding of the molecular mechanisms by which β-arrestins interpret GPCR phosphorylation signatures, offering a framework that could aid in the design of pathway-selective therapeutics.
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