4.5 Review

High-throughput analysis of peptide-binding modules

期刊

PROTEOMICS
卷 12, 期 10, 页码 1527-1546

出版社

WILEY
DOI: 10.1002/pmic.201100599

关键词

Cell signaling; Interaction profiling; Peptide-array libraries; Protein interaction domains; Protein microarrays; Post-translational modifications; Specificity; Technology

资金

  1. National Science Foundation [MCB-0819125]
  2. University of Chicago Cancer Research Center
  3. University of Chicago Diabetes Research Training Center
  4. Cancer Research Foundation
  5. Canadian Health Institute Research (CIHR)
  6. NIH [TG-GM07183]

向作者/读者索取更多资源

Modular protein interaction domains (PIDs) that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some PIDs such as SH2, 143-3, Chromo, and Bromo domains serve to recognize posttranslational modification (PTM) of amino acids (such as phosphorylation, acetylation, methylation, etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PSD-95/Discs-large/ZO-1 (PDZ) domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate-specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High-throughput (HTP) analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry, or other HTP techniques provides new insight into the potential proteinprotein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective proteinprotein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls associated with HTP analysis of proteinpeptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of PIDs and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions.

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