Deep mutational analysis reveals functional trade-offs in the sequences of EGFR autophosphorylation sites

Autor: Neel H. Shah, John Kuriyan, Aaron J. Cantor
Rok vydání: 2018
Předmět:
inorganic chemicals
Phosphotyrosine binding
0301 basic medicine
Proteome
Protein Conformation
EGFR
DNA Mutational Analysis
specificity
macromolecular substances
environment and public health
Biochemistry
03 medical and health sciences
0302 clinical medicine
deep mutational scanning
Humans
Phosphorylation
Tyrosine
030304 developmental biology
0303 health sciences
Multidisciplinary
Epidermal Growth Factor
biology
Chemistry
Autophosphorylation
Signal transducing adaptor protein
Biological Sciences
Cell biology
ErbB Receptors
SH2
enzymes and coenzymes (carbohydrates)
030104 developmental biology
PNAS Plus
Protein kinase domain
030220 oncology & carcinogenesis
biology.protein
bacteria
Generic health relevance
GRB2
signaling
Tyrosine kinase
Receptor
Signal Transduction
Proto-oncogene tyrosine-protein kinase Src
Zdroj: Cantor, AJ; Shah, NH; & Kuriyan, J. (2018). Deep mutational analysis reveals functional trade-offs in the sequences of EGFR autophosphorylation sites. Proceedings of the National Academy of Sciences of the United States of America, 115(31), E7303-E7312. doi: 10.1073/pnas.1803598115. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/7nb1t9db
Proceedings of the National Academy of Sciences of the United States of America, vol 115, iss 31
Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
0027-8424
Popis: Significance Phosphorylation of tyrosine residues in the cytoplasmic tail of the epidermal growth factor receptor (EGFR) by its kinase domain propagates a rich variety of information downstream of growth factor binding. The amino acid sequences surrounding each phosphorylation site encode the extent of phosphorylation as well as the extent of binding by multiple effector proteins. By profiling the kinase activity of EGFR alongside the binding specificities of an SH2 domain and a PTB domain for thousands of defined phosphorylation site sequences, we discovered that the sequences surrounding the phosphorylation sites in EGFR are not optimal and that discrimination against phosphorylation by cytoplasmic tyrosine kinases such as c-Src and c-Abl is likely to have shaped the evolution of these sequences.
Upon activation, the epidermal growth factor receptor (EGFR) phosphorylates tyrosine residues in its cytoplasmic tail, which triggers the binding of Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains and initiates downstream signaling. The sequences flanking the tyrosine residues (referred to as “phosphosites”) must be compatible with phosphorylation by the EGFR kinase domain and the recruitment of adapter proteins, while minimizing phosphorylation that would reduce the fidelity of signal transmission. To understand how phosphosite sequences encode these functions within a small set of residues, we carried out high-throughput mutational analysis of three phosphosite sequences in the EGFR tail. We used bacterial surface display of peptides coupled with deep sequencing to monitor phosphorylation efficiency and the binding of the SH2 and PTB domains of the adapter proteins Grb2 and Shc1, respectively. We found that the sequences of phosphosites in the EGFR tail are restricted to a subset of the range of sequences that can be phosphorylated efficiently by EGFR. Although efficient phosphorylation by EGFR can occur with either acidic or large hydrophobic residues at the −1 position with respect to the tyrosine, hydrophobic residues are generally excluded from this position in tail sequences. The mutational data suggest that this restriction results in weaker binding to adapter proteins but also disfavors phosphorylation by the cytoplasmic tyrosine kinases c-Src and c-Abl. Our results show how EGFR-family phosphosites achieve a trade-off between minimizing off-pathway phosphorylation and maintaining the ability to recruit the diverse complement of effectors required for downstream pathway activation.
Databáze: OpenAIRE