High‐throughput analysis of peptide‐binding modules

Abstract

Modular protein interaction domains that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some protein interaction domains such as SH2, 14-3-3, Chromo and Bromo domains serve to recognize post-translational modification of amino acids (such as phosphorylation, acetylation, methylation etc.) and translate these into discrete cellular responses. Other modules such as SH3 and 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 analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry or other HTP techniques provides new insight into the potential protein-protein 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 protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls of high-throughput analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of protein interaction domains 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.

The Development and Application of a Quantitative Peptide Microarray Based Approach to Protein Interaction Domain Specificity Space

“…However, consistent with our previous analysis of SH2 domain binding specificity (27), we find that high-affinity interaction overlap is not solely directed by core motif overlap, and subtle combinations of permissive and nonpermissive residues play important roles in defining specificity space. This concept seems to be a general one for PIDs (15), and highlights that selectivity space-as defined by preferred binding motifs where residues are assumed to contribute independently to binding affinity-does not predetermine specificity space, and many physiologically important interactions may be dictated by submotif contextual factors. Because of the low sensitivity, quantitative resolution, or inherent limitations of previous high throughput techniques, such important modulations have remained elusive.…”

“…Going forward, we suggest that models trained incorporating the idiosyncratic contextual binding preferences of single domains are more likely to fully represent ligand binding preferences than those trained from entire PID families. Considering the significant impact of contextual binding information on PID specificity space (15), the combination of larger CPCMA derived interaction data sets with algorithms capable of incorporating residue correlations is therefore an important future application. For instance, when such models are combined with in vivo information more accurate network (re)constructions are possible (14,17).…”

“…Given this, although it is generally true that interactions between a given PID and its ligand are necessary for an interaction to occur in vivo, they are not always sufficient. There are multiple instances where secondary contacts (interactions outside the ligand motif and binding interface of the PID) are also necessary for a biological outcome (5,15,84). These "secondary" interactions can be mediated by alternative regions of the domain containing protein or of the domain itself.…”

“…Tyrosine phosphorylation and its recognition by SH2 domains is a uniquely metazoan adaptation (39), prominently involved in the transduction of growth signals (1,2,40). SH2 domain specificity has been leveraged in multiple contexts to rewire signaling pathways (15), and specificity dysregulation is associated with multiple diseases, including cancer (40 -42). Despite the importance of directing specific signals, many SH2 domains share sequence preferences, resulting in substantial binding crossover over a broad dynamic range of affinities (27).…”

Deciphering Phosphotyrosine-Dependent Signaling Networks in Cancer by SH2 Profiling

“…34,35 Similar to antibodies, modular domains can be used in different binding assay platforms defined by immobilization and detection methods. For example, purified SH2 domain proteins can be arrayed on a solid support and incubated with fluorescently labeled samples in solution (e.g., forward-phase array 36 ), or samples can be arrayed on solid phase and incubated with labeled SH2 domains in solution (e.g., reversephase array 26 ).…”