SH3 interactome conserves general function over specific form

Src homology 3 (SH3) domains bind peptides to mediate protein-protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form.

Bayesian modeling of the yeast SH3 domain interactome predicts spatiotemporal dynamics of endocytosis proteins

A genome-scale specificity and interaction map for yeast SH3 domain-containing proteins reveal how family members show selective binding to target proteins and predicts the dynamic localization of new candidate endocytosis proteins.

SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast two-hybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes.

Significant diversity exists in protein structure and function, yet certain structural domains are used repeatedly across species to execute similar functions. The SH3 domain is one such common structural domain. It is found in signaling proteins and mediates protein–protein interactions by binding to short peptide sequences generally composed of proline. To investigate both the generality and selectivity of peptide binding by SH3 domains, we examined peptide specificity for almost all SH3 domains encoded within the proteome of the budding yeast, Saccharomyces cerevisiae, using a range of experimental methods. We found that although most of the intrinsic binding specificity for SH3 domains can be summarized by the two previously described canonical binding modes, each individual SH3 domain that we studied utilizes unique features of its cognate ligand to achieve binding selectivity. Moreover, some domains exhibit binding specificities that are distinct from the two canonical classes. We integrated peptide-SH3 domain binding data from three complementary screening techniques using a Bayesian statistical model to generate a protein–protein interaction network for the budding yeast SH3 domain family. This network was highly enriched in endocytosis proteins and their interactions. By examining these interactions in detail, we show that our SH3 domain network can be used to predict the temporal localization of several previously uncharacterized proteins to dynamic complexes that orchestrate the process of endocytosis.

A specificity map for the PDZ domain family

PDZ domains are protein–protein interaction modules that recognize specific C-terminal sequences to assemble protein complexes in multicellular organisms. By scanning billions of random peptides, we accurately map binding specificity for approximately half of the over 330 PDZ domains in the human and Caenorhabditis elegans proteomes. The domains recognize features of the last seven ligand positions, and we find 16 distinct specificity classes conserved from worm to human, significantly extending the canonical two-class system based on position −2. Thus, most PDZ domains are not promiscuous, but rather are fine-tuned for specific interactions. Specificity profiling of 91 point mutants of a model PDZ domain reveals that the binding site is highly robust, as all mutants were able to recognize C-terminal peptides. However, many mutations altered specificity for ligand positions both close and far from the mutated position, suggesting that binding specificity can evolve rapidly under mutational pressure. Our specificity map enables the prediction and prioritization of natural protein interactions, which can be used to guide PDZ domain cell biology experiments. Using this approach, we predicted and validated several viral ligands for the PDZ domains of the SCRIB polarity protein. These findings indicate that many viruses produce PDZ ligands that disrupt host protein complexes for their own benefit, and that highly pathogenic strains target PDZ domains involved in cell polarity and growth.

The PDZ domain is a structural domain that functions as a protein–protein interaction module that recognizes specific C-terminal peptide sequences to assemble intracellular complexes important in signaling pathways of multicellular organisms. These modules are associated with human disease and are targets of viruses and other pathogens. By examining peptide specificity and substrate diversity of roughly one half of the PDZ domains known to exist in human and the nematode Caenorhabditis elegans, we were able to show that PDZ domains are more specific than previously appreciated. PDZ domains also remain functional under high mutational pressure, and only a few of the vast number of possible PDZ domain specificities are utilized in nature. These PDZ domain specificities are conserved from human to worm, implying that the specificities evolved early and were reused over evolution instead of being reshaped. The specificity map generated here was used to predict and experimentally confirm new viral PDZ-binding motifs. We present evidence that pathogenic viruses, including avian influenza, bind host PDZ domains via these motifs, thereby competing with signaling by host complexes, which leads to disruption of growth and polarity of the host cells.

A genome-scale specificity map for PDZ domains reveals how family members recognize ligands to assemble signaling complexes and also reveals how viruses target these domains to subvert host cell function.

Intramolecular cooperativity in a protein binding site assessed by combinatorial shotgun scanning mutagenesis

Combinatorial shotgun alanine-scanning was used to assess intramolecular cooperativity in the high affinity site (site 1) of human growth hormone (hGH) for binding to its receptor. A total of 19 side-chains were analyzed and statistically significant data were obtained for 145 of the 171 side-chain pairs. The analysis revealed that 90% of the side-chain pairs exhibited no statistically significant pair interactions, and the remaining 10% of side-chain pairs exhibited only small interactions corresponding to cooperative interaction energies with magnitudes less than 0.4 kcal/mol. The statistical predictions were tested by measuring affinities for purified mutant proteins and were found to be accurate for five of six side-chain pairs tested. The results reveal that hGH site 1 behaves in a highly additive manner and suggest that shotgun scanning should be useful for assessing cooperative effects in other protein-protein interactions.

The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment

A large-scale effort, termed the Secreted Protein Discovery Initiative (SPDI), was undertaken to identify novel secreted and transmembrane proteins. In the first of several approaches, a biological signal sequence trap in yeast cells was utilized to identify cDNA clones encoding putative secreted proteins. A second strategy utilized various algorithms that recognize features such as the hydrophobic properties of signal sequences to identify putative proteins encoded by expressed sequence tags (ESTs) from human cDNA libraries. A third approach surveyed ESTs for protein sequence similarity to a set of known receptors and their ligands with the BLAST algorithm. Finally, both signal-sequence prediction algorithms and BLAST were used to identify single exons of potential genes from within human genomic sequence. The isolation of full-length cDNA clones for each of these candidate genes resulted in the identification of >1000 novel proteins. A total of 256 of these cDNAs are still novel, including variants and novel genes, per the most recent GenBank release version. The success of this large-scale effort was assessed by a bioinformatics analysis of the proteins through predictions of protein domains, subcellular localizations, and possible functional roles. The SPDI collection should facilitate efforts to better understand intercellular communication, may lead to new understandings of human diseases, and provides potential opportunities for the development of therapeutics.