Comprehensive analysis of the human SH3 domain family reveals a wide variety of non-canonical specificities

Joan Teyra1(+), Haiming Huang1,2(+), Shobhit Jain1,3, Xinyu Guan4, Aiping Dong4, Yanli Liu4, Wolfram Tempel4, Jinrong Min4,5, Yufeng Tong4,6, Philip M. Kim1,2,3, Gary D. Bader1,2,3 and Sachdev S. Sidhu1,2,(*)

Abstract

SH3 domains are protein modules that mediate protein-protein interactions in many eukaryotic signal transduction pathways, including cell growth regulation, endocytosis and cytoskeleton control. Canonical SH3 domains act by binding to proline-rich sequences in partner proteins. Although these binding preferences have been confirmed for the majority of SH3 domains studied thus far, a growing number of studies have revealed alternative recognition mechanisms. We have comprehensively surveyed the specificity landscape of human SH3 domains in an unbiased manner using peptide-phage display and deep sequencing. Based on more than 70,000 unique binding peptides, we obtained 154 specificity profiles for 115 SH3 domains, which reveal that roughly half of the SH3 domains exhibit non-canonical specificities and collectively recognize a wide variety of peptide motifs, most of which were previously unknown. Crystal structures of SH3 domains with two distinct non-canonical specificities revealed novel peptide-binding modes through an extended surface outside of the canonical proline-binding site. Our results constitute a significant contribution towards a complete understanding of the mechanisms underlying SH3-mediated cellular responses. To enable future research, we have made publicly available the peptide-binding specificity profiles.

Supplementary Information

Data

Note: PWM and Logo file names are formatted as: Gene_name-Domain_position-PWM_number (e.g. PWM ABL2-1_1-1 has ABL2 gene name, 1/1 domain position, 1 PWM number (out of 2))

Author Information

1The Donnelly Centre, University of Toronto, Toronto, ON, Canada M5S 3E1
2Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada M5S 1A8
3Department of Computer Science, University of Toronto, Toronto, ON, Canada M5S 3G4
4Structural Genomics Consortium, University of Toronto, Toronto, ON, Canada M5G 1L7
5Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada
6Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON Canada, M5S 1A8
(*)To whom correspondence should be addressed. Email: sachdev.sidhu@utoronto.ca
(+)JT and HH contributed equally to the study

Data/SH3Human (last edited 2017-04-25 18:12:58 by ShobhitJain)

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