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Molecular dynamics reveal a novel kinase–substrate interface that regulates protein translation Free
Ming S. Liu1,2,†,*, Die Wang1,†, Hiroyuki Morimoto1,3, Howard C.H. Yim1, Aaron T. Irving1, Bryan R.G. Williams1,4, and Anthony J. Sadler1,4,*
1Centre for Cancer Research, MIMR-PHI Institute of Medical Research, Melbourne, VIC 3168, Australia
2CSIRO – Computational Informatics and Digital Productivity Flagship, Private Bag 10, Clayton South, VIC 3169, Australia
3Department of Anatomy, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Fukuoka 807-8555, Japan
4Department of Molecular and Translational Science, Monash University, Melbourne, VIC 3168, Australia *Correspondence to:Anthony J. Sadler, E-mail: anthony.sadler@mimr-phi.org; Ming S. Liu, E-mail: ming.liu@csiro.au
J Mol Cell Biol, Volume 6, Issue 6, December 2014, 473-485,  https://doi.org/10.1093/jmcb/mju044
Keyword: molecular dynamics, eukaryotic initiation factor 2α (eIF2α), eIF2α kinases, protein kinase R (PKR), protein translation, kinase activity

A key control point in gene expression is the initiation of protein translation, with a universal stress response being constituted by inhibitory phosphorylation of the eukaryotic initiation factor 2α (eIF2α). In humans, four kinases sense diverse physiological stresses to regulate eIF2α to control cell differentiation, adaptation, and survival. Here we develop a computational molecular model of eIF2α and one of its kinases, the protein kinase R, to simulate the dynamics of their interaction. Predictions generated by coarse-grained dynamics simulations suggest a novel mode of action. Experimentation substantiates these predictions, identifying a previously unrecognized interface in the protein complex, which is constituted by dynamic residues in both eIF2α and its kinases that are crucial to regulate protein translation. These findings call for a reinterpretation of the current mechanism of action of the eIF2α kinases and demonstrate the value of conducting computational analysis to evaluate protein function.