Literature DB >> 26779844

Comparison of the peptide binding preferences of three closely related TRAF paralogs: TRAF2, TRAF3, and TRAF5.

Glenna Wink Foight1, Amy E Keating1,2.   

Abstract

Tumor necrosis factor receptor-associated factors (TRAFs) constitute a family of adapter proteins that act in numerous signaling pathways important in human biology and disease. The MATH domain of TRAF proteins binds peptides found in the cytoplasmic domains of signaling receptors, thereby connecting extracellular signals to downstream effectors. Beyond several very general motifs, the peptide binding preferences of TRAFs have not been extensively characterized, and differences between the binding preferences of TRAF paralogs are poorly understood. Here we report a screening system that we established to explore TRAF peptide-binding specificity using deep mutational scanning of TRAF-peptide ligands. We displayed single- and double-mutant peptide libraries based on the TRAF-binding sites of CD40 or TANK on the surface of Escherichia coli and screened them for binding to TRAF2, TRAF3, and TRAF5. Enrichment analysis of the library sequencing results showed differences in the permitted substitution patterns in the TANK versus CD40 backgrounds. The three TRAF proteins also demonstrated different preferences for binding to members of the CD40 library, and three peptides from that library that were analyzed individually showed striking differences in affinity for the three TRAFs. These results illustrate a previously unappreciated level of binding specificity between these close paralogs and demonstrate that established motifs are overly simplistic. The results from this work begin to outline differences between TRAF family members, and the experimental approach established herein will enable future efforts to investigate and redesign TRAF peptide-binding specificity.
© 2016 The Protein Society.

Entities:  

Keywords:  bacterial surface display; deep mutational scanning; interaction specificity; protein-protein interactions

Mesh:

Substances:

Year:  2016        PMID: 26779844      PMCID: PMC4918428          DOI: 10.1002/pro.2881

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


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