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Model of the Interaction between the NF-κB Inhibitory Protein p100 and the E3 Ubiquitin Ligase β-TrCP based on NMR and Docking Experiments

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NF-κB is a major transcription factor whose activation is triggered through two main activation pathways: the canonical pathway involving disruption of IκB-α/NF-κB complexes and the alternative pathway whose activation relies… Click to show full abstract

NF-κB is a major transcription factor whose activation is triggered through two main activation pathways: the canonical pathway involving disruption of IκB-α/NF-κB complexes and the alternative pathway whose activation relies on the inducible proteolysis of the inhibitory protein p100. One central step controlling p100 processing consists in the interaction of the E3 ubiquitin ligase β-TrCP with p100, thereby leading to its ubiquitinylation and subsequent either complete degradation or partial proteolysis by the proteasome. However, the interaction mechanism between p100 and β-TrCP is still poorly defined. In this work, a diphosphorylated 21-mer p100 peptide model containing the phosphodegron motif was used to characterize the interaction with β-TrCP by NMR. In parallel, docking simulations were performed in order to obtain a model of the 21P-p100/β-TrCP complex. Saturation transfer difference (STD) experiments were performed in order to highlight the residues of p100 involved in the interaction with the β-TrCP protein. These results highlighted the importance of pSer865 and pSer869 residues in the interaction with β-TrCP and particularly the Tyr867 that fits inside the hydrophobe β-TrCP cavity with the Arg474 guanidinium group. Four other arginines, Arg285, Arg410, Arg431, and Arg521, were found essential in the stabilization of p100 on the β-TrCP surface. Importantly, the requirement for these five arginine residues of β-TrCP for the interaction with p100 was further confirmed in vivo, thereby validating the docking model through a biological approach.

Keywords: p100; inhibitory protein; trcp; interaction; protein p100

Journal Title: Journal of chemical information and modeling
Year Published: 2017

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