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.

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.

A proliferation-inducing ligand (APRIL) is a member of the tumor necrosis factor (TNF) ligand superfamily and has a proliferative effect on both normal and tumor cells. The TNF family receptors (B-cell maturation antigen (BCMA), transmembrane activator and CAML-interactor (TACI), and BAFF receptor-3 (BR3)) for APRIL and the closely related ligand, B-cell activating factor of the TNF family (BAFF), bind these ligands through a highly conserved six residue DXL motif ((F/Y/W)-D-X-L-(V/T)-(R/G)). Panning peptide phage display libraries led to the identification of several novel classes of APRIL-binding peptides, which could be grouped by their common sequence motifs. Interestingly, only one of these ten classes consisted of peptides containing the DXL motif. Nevertheless, all classes of peptides prevented APRIL, but not BAFF, from binding BCMA, their shared receptor. Synthetic peptides based on selected sequences inhibited APRIL binding to BCMA with IC(50) values of 0.49-27 microM. An X-ray crystallographic structure of APRIL bound to one of the phage-derived peptides showed that the peptide, lacking the DXL motif, was nevertheless bound in the DXL pocket on APRIL. Our results demonstrate that even though a focused, highly conserved motif is required for APRIL-receptor interaction, remarkably, many novel and distinct classes of peptides are also capable of binding APRIL at the ligand receptor interface.

Multicellular organisms rely on complex, fine-tuned protein networks to respond to environmental changes. We used in vitro evolution to explore the role of domain mutation and expansion in the evolution of network complexity. Using random mutagenesis to facilitate family expansion, we asked how versatile and robust the binding site must be to produce the rich functional diversity of the natural PDZ domain family. From a combinatorial protein library, we analyzed several hundred structured domain variants and found that one-quarter were functional for carboxyl-terminal ligand recognition and that our variant repertoire was as specific and diverse as the natural family. Our results show that ligand binding is hardwired in the PDZ fold and suggest that this flexibility may facilitate the rapid evolution of complex protein interaction networks.

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.

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.

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.