Src homology 2 (SH2) domains are the largest family of interaction modules encoded by the human genome to recognize tyrosine-phosphorylated sequences and thereby play pivotal roles in transducing and controlling cellular signals emanating from protein-tyrosine kinases. Different SH2 domains select for distinct phosphopeptides, and the function of a given SH2 domain is often dictated by the specific motifs that it recognizes. Therefore, deciphering the phosphotyrosyl peptide motif recognized by an SH2 domain is the key to understanding its cellular function. Here we cloned all 120 SH2 domains identified in the human genome and determined the phosphotyrosyl peptide binding properties of 76 SH2 domains by screening an oriented peptide array library. Of these 76, we defined the selectivity for 43 SH2 domains and refined the binding motifs for another 33 SH2 domains. We identified a number of novel binding motifs, which are exemplified by the BRDG1 SH2 domain that selects specifically for a bulky, hydrophobic residue at P ؉ 4 relative to the Tyr(P) residue. Based on the oriented peptide array library data, we developed scoring matrix-assisted ligand identification (or SMALI), a Web-based program for predicting binding partners for SH2-containing proteins. When applied to SH2D1A/SAP (SLAM-associated protein), a protein whose mutation or deletion underlies the Xlinked lymphoproliferative syndrome, SMALI not only recapitulated known interactions but also identified a number of novel interacting proteins for this diseaseassociated protein. SMALI also identified a number of potential interactors for BRDG1, a protein whose function is largely unknown. Peptide in-solution binding analysis demonstrated that a SMALI score correlates well with the binding energy of a peptide to a given SH2 domain. The definition of the specificity space of the human SH2 domain provides both the necessary molecular basis and a platform for future exploration of the functions for SH2-containing proteins in cells.

Ubiquitin ligases (E3s) confer specificity to ubiquitination by recognizing target substrates. However, the substrates of most E3s have not been extensively discovered, and new methods are needed to efficiently and comprehensively identify these substrates. Mostly, E3s specifically recognize substrates via their protein interaction domains. We developed a novel integrated strategy to identify substrates of E3s containing protein interaction domains on a proteomic scale. The binding properties of the protein interaction domains were characterized by screening a random peptide library using a yeast two-hybrid system. Artificial degrons, consisting of a preferential ubiquitination sequence and particular interaction domain-binding motifs, were tested as potential substrates by in vitro ubiquitination assays. Using this strategy, not only substrates but also nonsubstrate regulators can be discovered. The detailed substrate recognition mechanisms, which are useful for drug discovery, can also be characterized. We used the Ligand of Numb protein X (LNX) family of E3s, a group of PDZ domain-containing RING-type E3 ubiquitin ligases, to demonstrate the feasibility of this strategy. Many potential substrates of LNX E3s were identified. Eight of the nine selected candidates were ubiquitinated in vitro, and two novel endogenous substrates, PDZ-binding kinase (PBK) and breakpoint cluster region protein (BCR), were confirmed in vivo. We further revealed that the LNX1-mediated ubiquitination and degradation of PBK inhibited cell proliferation and enhanced sensitivity to doxorubicin-induced apoptosis. The substrate recognition mechanism of LNX E3s was also characterized; this process involves the recognition of substrates via their specific PDZ domains by binding to the C-termini of the target proteins. This strategy can potentially be extended to a variety of E3s that contain protein interaction domain(s), thereby serving as a powerful tool for the comprehensive identification of their substrates on a proteomic scale.

A large proportion of protein-protein interactions is mediated by families of peptide-binding domains. Comprehensive characterization of each of these domains is critical for understanding the mechanisms and networks of protein interaction at the domain level. However, existing methods are all based on large scale screenings for each domain that are inefficient to deal with hundreds of members in major domain families. We developed a systematic strategy for efficient binding property characterization of peptide-binding domains based on high throughput validation screening of a specialized candidate ligand library using yeast two-hybrid mating array. Its outstanding feature is that the overall efficiency is dramatically improved compared with that of traditional screening, and it will be higher as the system cycles. PDZ domain family was first used to test the strategy. Five PDZ domains were rapidly characterized. Broader binding properties were identified compared with other methods, including novel recognition specificities that provided the basis for major revision of conventional PDZ classification. Several novel interactions were discovered, serving as significant clues for further functional investigation. This strategy can be easily extended to a variety of peptide-binding domains as a powerful tool for comprehensive analysis of domain binding property in proteomic scale. Molecular & Cellular Proteomics 5:1368 -1381, 2006.

Protein-protein interactions (PPIs) are essential events to play important roles in a series of biological processes. There are probably more ways of PPIs than we currently realized. Structural and functional investigations of weak PPIs have lagged behind those of strong PPIs due to technical difficulties. Weak PPIs are often short-lived, which may result in more dynamic signals with important biological roles within and/or between cells. For example, the characteristics of PSD-95/Dlg/ZO-1 (PDZ) domain binding to internal sequences, which are primarily weak interactions, have not yet been systematically explored. In the present study, we constructed a nearly random octapeptide yeast two-hybrid library. A total of 24 PDZ domains were used as baits for screening the library. Fourteen of these domains were able to bind internal PDZ-domain binding motifs (PBMs), and PBMs screened for nine PDZ domains exhibited strong preferences. Among 11 PDZ domains that have not been reported their internal PBM binding ability, six were confirmed to bind internal PBMs. The first PDZ domain of LNX2, which has not been reported to bind C-terminal PBMs, was found to bind internal PBMs. These results suggest that the internal PBMs binding ability of PDZ domains may have been underestimated. The data provided diverse internal binding properties for several PDZ domains that may help identify their novel binding partners.

PDZK1 is a simple adaptor protein with four protein interaction PDZ domains, but without any other known functional domains. Here, we used yeast two-hybrid screening of a random peptide library and high-throughput validation screening of a specialized PDZ ligand candidate library to systematically and comprehensively identify PDZK1 ligands. The potential functional associations of the ligands were predicted by functional annotations from a MILANO literature search and subcellular localizations. The ligands were considered more likely to be functionally associated if they had similar patterns of functions or closely related functions. For some functionally associated ligand pairs, interaction with one ligand was found to be influenced by another ligand in a yeast three-hybrid system. Many G-protein signaling pathway-related proteins were found to interact with PDZK1, and they were likely to be functionally associated with transporters based on their closely related functions. This strategy can be extended to the study of other adaptor proteins that contain peptide-binding domains.

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Analysis of secretory proteins is an important area in proteomic research. We propose that a good secretory protein sample should be enriched with known secretory proteins, and a secretory protein should be enriched in the secretory protein sample compared with its corresponding soluble cell lysate. Positive identifications of proteins were subjected to quantitation of spectral counts, which reflect relative protein abundance. Enrichment index of the sample (EIS) and the enrichment index for protein (EIP) were obtained by comparing proteins identified in the secretory protein sample and those in the soluble cell lysate sample. The quality of the secretory protein sample can be represented by EIS. EIP was used to identify the secretory proteins.The secretory proteins from mouse dendritic cell sarcoma (DCS) were analyzed by MS. The EISs of two samples were 75.4 and 84.65, respectively. 72 proteins were significantly enriched in secretory protein samples, of which 42 proteins were either annotated in Swiss-Prot and/or predicted by signal peptides to be secretory. In the remaining 30 proteins, 12 and 15 proteins were positively predicted by SecretomeP and ProP, respectively, and 5 proteins were positive by both methods. Furthermore, 11 proteins were found to be present in exosome in other studies that involved mice dendritic cell lines. We suggest that this assessment method is helpful for systemic research of secretory proteins and biomarker discovery for diseases such as cancer.

Secretome study presents new possibilities for understanding liver secretory function in a comprehensive and exploratory way. Perfusates from isolated perfused rat liver are good targets for liver secretome study on the organ level. There are two major concerns in this type of study, cytosolic and blood contaminations in the perfusates. Therefore, the perfusion conditions were carefully controlled and alanine aminotransferase levels in the perfusates were monitored as indicators of liver integrity and cytosolic contamination. The protein pattern of perfusate was significantly different from cell lysate, which showed low cytosolic contamination. The amount of immunoglobulins in the perfusates identified by both Western blot and MS/MS indicated low serum contamination. In total, 357 secretory protein candidates were identified by the Enrichment Index method or N-terminal signal peptide prediction. Secretory proteins annotated by Swiss-Prot were 5-fold enriched in the perfusates and around 10-fold enriched in the portion identified by the Enrichment Index method. Some cytokines, secretory proteins from liver interstitial cells, and components of the liver microenvironment were found in the perfusates, highlighting the advantages of studying the liver secretome on the organ level. The strategy can be used in physiology research and biomarker discovery for diseases in the liver as well as other organs.