The multiple‐specificity landscape of modular peptide recognition domains

Modular protein interaction domains form the building blocks of eukaryotic signaling pathways. Many of them, known as peptide recognition domains, mediate protein interactions by recognizing short, linear amino acid stretches on the surface of their cognate partners with high specificity. Residues in these stretches are usually assumed to contribute independently to binding, which has led to a simplified understanding of protein interactions. Conversely, we observe in large binding peptide data sets that different residue positions display highly significant correlations for many domains in three distinct families (PDZ, SH3 and WW). These correlation patterns reveal a widespread occurrence of multiple binding specificities and give novel structural insights into protein interactions. For example, we predict a new binding mode of PDZ domains and structurally rationalize it for DLG1 PDZ1. We show that multiple specificity more accurately predicts protein interactions and experimentally validate some of the predictions for the human proteins DLG1 and SCRIB. Overall, our results reveal a rich specificity landscape in peptide recognition domains, suggesting new ways of encoding specificity in protein interaction networks.     

Plasticity of PDZ domains in ligand recognition and signaling

The PDZ domain is a protein-protein interacting module that plays an important role in the organization of signaling complexes. The recognition of short intrinsically disordered C-terminal peptide motifs is the archetypical PDZ function, but the functional repertoire of this versatile module also includes recognition of internal peptide sequences, dimerization and phospholipid binding. The PDZ function can be tuned by various means such as allosteric effects, changes of physiological buffer conditions and phosphorylation of PDZ domains and/or ligands, which poses PDZ domains as dynamic regulators of cell signaling. This review is focused on the plasticity of the PDZ interactions.     

Dynamic regulation of the INAD signaling scaffold becomes crystal clear

PDZ domains are common building blocks of scaffold proteins that enhance specificity and speed in signal transduction cascades. Although PDZ modules are often viewed as passive participants, Mishra et al. (2007) now show that a PDZ domain in INAD, a scaffold protein in photoreceptor cells of the fruit fly, undergoes a light-dependent conformational change, which has important consequences for signaling and animal behavior.     

Solution structure of the RIM1alpha PDZ domain in complex with an ELKS1b C-terminal peptide

PDZ domains are widespread protein modules that commonly recognize C-terminal sequences of target proteins and help to organize macromolecular signaling complexes. These sequences usually bind in an extended conformation to relatively shallow grooves formed between a beta-strand and an alpha-helix in the corresponding PDZ domains. Because of this binding mode, many PDZ domains recognize primarily the C-terminal and the antepenultimate side-chains of the target protein, which commonly conform to motifs that have been categorized into different classes. However, an increasing number of PDZ domains have been found to exhibit unusual specificities. These include the PDZ domain of RIMs, which are large multidomain proteins that regulate neurotransmitter release and help to organize presynaptic active zones. The RIM PDZ domain binds to the C-terminal sequence of ELKS with a unique specificity that involves each of the four ELKS C-terminal residues. To elucidate the structural basis for this specificity, we have determined the 3D structure in solution of an RIM/ELKS C-terminal peptide complex using NMR spectroscopy. The structure shows that the RIM PDZ domain contains an unusually deep and narrow peptide-binding groove with an exquisite shape complementarity to the four ELKS C-terminal residues in their bound conformation. This groove is formed, in part, by a set of side-chains that is conserved selectively in RIM PDZ domains and that hence determines, at least in part, their unique specificity.     

Role of the PDZ domains in Escherichia coli DegP protein

PDZ domains are modular protein interaction domains that are present in metazoans and bacteria. These domains possess unique structural features that allow them to interact with the C-terminal residues of their ligands. The Escherichia coli essential periplasmic protein DegP contains two PDZ domains attached to the C-terminal end of the protease domain. In this study we examined the role of each PDZ domain in the protease and chaperone activities of this protein. Specifically, DegP mutants with either one or both PDZ domains deleted were generated and tested to determine their protease and chaperone activities, as well as their abilities to sequester unfolded substrates. We found that the PDZ domains in DegP have different roles; the PDZ1 domain is essential for protease activity and is responsible for recognizing and sequestering unfolded substrates through C-terminal tags, whereas the PDZ2 domain is mostly involved in maintaining the hexameric cage of DegP. Interestingly, neither of the PDZ domains was required for the chaperone activity of DegP. In addition, we found that the loops connecting the protease domain to PDZ1 and connecting PDZ1 to PDZ2 are also essential for the protease activity of the hexameric DegP protein. New insights into the roles of the PDZ domains in the structure and function of DegP are provided. These results imply that DegP recognizes substrate molecules targeted for degradation and substrate molecules targeted for refolding in different manners and suggest that the substrate recognition mechanisms may play a role in the protease-chaperone switch, dictating whether the substrate is degraded or refolded.     

Characterization of PDZ domain‐peptide interaction interface based on energetic patterns

PDZ domain is one of the abundant modular domains that recognize short peptide sequences to mediate protein–protein interactions. To decipher the binding specificity of PDZ domain, we analyzed the interactions between 11 mouse PDZ domains and 217 peptides using a method called MIECSVM, which energetically characterizes the domain‐peptide interaction using molecular interaction energy components (MIECs) and predicts binding specificity using support vector machine (SVM). Cross‐validation and leave‐one‐domain‐out test showed that the MIEC‐SVM using all 44 PDZ‐peptide residue pairs at the interaction interface outperformed the sequence‐based methods in the literature. A further feature (residue pair) selection procedure illustrated that 16 residue pairs were uninformative to the binding specificity, even though they contributed significantly (～50%) to the binding energy. If only using the 28 informative residue pairs, the performance of the MIEC‐SVM on predicting the PDZ binding specificity was significantly improved. This analysis suggests that the informative and uninformative residue interactions between the PDZ domain and the peptide may represent those contributing to binding specificity and affinity, respectively. We performed additional structural and energetic analyses to shed light on understanding how the PDZ‐peptide recognition is established. The success of the MIEC‐SVM method on PDZ domains in this study and SH3 domains in our previous studies illustrates its generality on characterizing protein‐ peptide interactions and understanding protein recognition from a structural and energetic viewpoint.     

Uncovering new aspects of protein interactions through analysis of specificity landscapes in peptide recognition domains

Protein interactions underlie all biological processes. An important class of protein interactions, often observed in signaling pathways, consists of peptide recognition domains binding short protein segments on the surface of their target proteins. Recent developments in experimental techniques have uncovered many such interactions and shed new lights on their specificity. To analyze these data, novel computational methods have been introduced that can accurately describe the specificity landscape of peptide recognition domains and predict new interactions. Combining large-scale analysis of binding specificity data with structure-based modeling can further reveal new biological insights into the molecular recognition events underlying signaling pathways.     

Inferring PDZ domain multi-mutant binding preferences from single-mutant data

Many important cellular protein interactions are mediated by peptide recognition domains. The ability to predict a domain's binding specificity directly from its primary sequence is essential to understanding the complexity of protein-protein interaction networks. One such recognition domain is the PDZ domain, functioning in scaffold proteins that facilitate formation of signaling networks. Predicting the PDZ domain's binding specificity was a part of the DREAM4 Peptide Recognition Domain challenge, the goal of which was to describe, as position weight matrices, the specificity profiles of five multi-mutant ERBB2IP-1 domains. We developed a method that derives multi-mutant binding preferences by generalizing the effects of single point mutations on the wild type domain's binding specificities. Our approach, trained on publicly available ERBB2IP-1 single-mutant phage display data, combined linear regression-based prediction for ligand positions whose specificity is determined by few PDZ positions, and single-mutant position weight matrix averaging for all other ligand columns. The success of our method as the winning entry of the DREAM4 competition, as well as its superior performance over a general PDZ-ligand binding model, demonstrates the advantages of training a model on a well-selected domain-specific data set.     

Degenerate specificity of PDZ domains from RhoA-specific nucleotide exchange factors PDZRhoGEF and LARG

PDZ domains are ubiquitous protein-protein interaction modules which bind short, usually carboxyterminal fragments of receptors, other integral or membrane-associated proteins, and occasionally cytosolic proteins. Their role in organizing multiprotein complexes at the cellular membrane is crucial for many signaling pathways, but the rules defining their binding specificity are still poorly understood and do not readily explain the observed diversity of their known binding partners. Two homologous RhoA-specific, multidomain nucleotide exchange factors PDZRhoGEF and LARG contain PDZ domains which show a particularly broad recognition profile, as suggested by the identification of five diverse biological targets. To investigate the molecular roots of this phenomenon, we constructed a phage display library of random carboxyterminal hexapeptides. Peptide variants corresponding to the sequences identified in library selection were synthesized and their affinities for both PDZ domains were measured and compared with those of peptides derived from sequences of natural partners. Based on the analysis of the binding sequences identified for PDZRhoGEF, we propose a sequence for an 'optimal' binding partner. Our results support the hypothesis that PDZ-peptide interactions may be best understood when one considers the sum of entropic and dynamic effects for each peptide as a whole entity, rather than preferences for specific residues at a given position.     

Characterization of PDZ domain-peptide interaction interface based on energetic patterns

PDZ domain is one of the abundant modular domains that recognize short peptide sequences to mediate protein-protein interactions. To decipher the binding specificity of PDZ domain, we analyzed the interactions between 11 mouse PDZ domains and 2387 peptides using a method called MIEC-SVM, which energetically characterizes the domain-peptide interaction using molecular interaction energy components (MIECs) and predicts binding specificity using support vector machine (SVM). Cross-validation and leave-one-domain-out test showed that the MIEC-SVM using all 44 PDZ-peptide residue pairs at the interaction interface outperformed the sequence-based methods in the literature. A further feature (residue pair) selection procedure illustrated that 16 residue pairs were uninformative to the binding specificity, even though they contributed significantly (~50%) to the binding energy. If only using the 28 informative residue pairs, the performance of the MIEC-SVM on predicting the PDZ binding specificity was significantly improved. This analysis suggests that the informative and uninformative residue interactions between the PDZ domain and the peptide may represent those contributing to binding specificity and affinity, respectively. We performed additional structural and energetic analyses to shed light on understanding how the PDZ-peptide recognition is established. The success of the MIEC-SVM method on PDZ domains in this study and SH3 domains in our previous studies illustrates its generality on characterizing protein-peptide interactions and understanding protein recognition from a structural and energetic viewpoint.     

Specificity and promiscuity in human glutaminase interacting protein recognition: insight from the binding of the internal and C-terminal motif

A large number of cellular processes are mediated by protein-protein interactions, often specified by particular protein binding modules. PDZ domains make up an important class of protein-protein interaction modules that typically bind to the C-terminus of target proteins. These domains act as a scaffold where signaling molecules are linked to a multiprotein complex. Human glutaminase interacting protein (GIP), also known as tax interacting protein 1, is unique among PDZ domain-containing proteins because it is composed almost exclusively of a single PDZ domain rather than one of many domains as part of a larger protein. GIP plays pivotal roles in cellular signaling, protein scaffolding, and cancer pathways via its interaction with the C-terminus of a growing list of partner proteins. We have identified novel internal motifs that are recognized by GIP through combinatorial phage library screening. Leu and Asp residues in the consensus sequence were identified to be critical for binding to GIP through site-directed mutagenesis studies. Structure-based models of GIP bound to two different surrogate peptides determined from nuclear magnetic resonance constraints revealed that the binding pocket is flexible enough to accommodate either the smaller carboxylate (COO(-)) group of a C-terminal recognition motif or the bulkier aspartate side chain (CH(2)COO(-)) of an internal motif. The noncanonical ILGF loop in GIP moves in for the C-terminal motif but moves out for the internal recognition motifs, allowing binding to different partner proteins. One of the peptides colocalizes with GIP within human glioma cells, indicating that GIP might be a potential target for anticancer therapeutics.     

An allosteric intramolecular PDZ-PDZ interaction modulates PTP-BL PDZ2 binding specificity

PDZ (acronym of the synapse-associated protein PSD-95/SAP90, the septate junction protein Discs-large, and the tight junction protein ZO-1) domains are abundant small globular protein interaction domains that mainly recognize the carboxyl termini of their target proteins. Detailed knowledge on PDZ domain binding specificity is a prerequisite for understanding the interaction networks they establish. We determined the binding preference of the five PDZ domains in the protein tyrosine phosphatase PTP-BL by screening a random C-terminal peptide lambda phage display library. Interestingly, the potential of PDZ2 to interact with class III-type ligands was found to be modulated by the presence of PDZ1. Structural studies revealed a direct and specific interaction of PDZ1 with a surface on PDZ2 that is opposite the peptide binding groove. Long-range allosteric effects that cause structural changes in the PDZ2 peptide binding groove thus explain the altered PDZ2 binding preference. Our results experimentally corroborate that the molecular embedding of PDZ domains is an important determinant of their ligand binding specificity.     

Application of Wavelet Transform for PDZ Domain Classification

PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III), that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain''s primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT) and Shannon entropy denoted by wavelet entropy (WE) feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%), which outperformed our occurrence rearrangements based method. The recognition rate was (81.41%) with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification.     

Functional diversity of protein C-termini: more than zipcoding?

The carboxylated (C)-terminus of proteins, which includes the single terminal alpha-carboxyl group and preceding residues, is uniquely positioned to serve as a recognition signature for a variety of cell-biological processes, including protein targeting, subcellular anchoring and the static and dynamic formation of macromolecular complexes. The terminal sequence motifs can be processed by posttranslational modifications, thereby providing a means to increase sequence diversity and to regulate interactions. Several classes of protein domains have been identified that are either designed for or are capable of interacting with protein C-termini - these include PDZ and TPR domains. The interactions between these protein domains and various terminal epitopes play an important role in specifying cell-biological functions. The combination of diversity and the plasticity of the chemistry of C-termini provides mechanisms for spatial and temporal specificity that are exploited by a variety of biological processes, ranging from specifying prokaryotic protein degradation to nucleating mammalian neuronal signaling complexes. Understanding the diverse functions of protein C-termini might also provide an important indexing criterion for functional proteomics.     

PDZ domains and their binding partners: structure, specificity, and modification

PDZ domains are abundant protein interaction modules that often recognize short amino acid motifs at the C-termini of target proteins. They regulate multiple biological processes such as transport, ion channel signaling, and other signal transduction systems. This review discusses the structural characterization of PDZ domains and the use of recently emerging technologies such as proteomic arrays and peptide libraries to study the binding properties of PDZ-mediated interactions. Regulatory mechanisms responsible for PDZ-mediated interactions, such as phosphorylation in the PDZ ligands or PDZ domains, are also discussed. A better understanding of PDZ protein-protein interaction networks and regulatory mechanisms will improve our knowledge of many cellular and biological processes.     

Sequence-specific long range networks in PSD-95/discs large/ZO-1 (PDZ) domains tune their binding selectivity

Protein-protein interactions mediated by modular protein domains are critical for cell scaffolding, differentiation, signaling, and ultimately, evolution. Given the vast number of ligands competing for binding to a limited number of domain families, it is often puzzling how specificity can be achieved. Selectivity may be modulated by intradomain allostery, whereby a remote residue is energetically connected to the functional binding site via side chain or backbone interactions. Whereas several energetic pathways, which could mediate intradomain allostery, have been predicted in modular protein domains, there is a paucity of experimental data to validate their existence and roles. Here, we have identified such functional energetic networks in one of the most common protein-protein interaction modules, the PDZ domain. We used double mutant cycles involving site-directed mutagenesis of both the PDZ domain and the peptide ligand, in conjunction with kinetics to capture the fine energetic details of the networks involved in peptide recognition. We performed the analysis on two homologous PDZ-ligand complexes and found that the energetically coupled residues differ for these two complexes. This result demonstrates that amino acid sequence rather than topology dictates the allosteric pathways. Furthermore, our data support a mechanism whereby the whole domain and not only the binding pocket is optimized for a specific ligand. Such cross-talk between binding sites and remote residues may be used to fine tune target selectivity.     

Putting into practice domain-linear motif interaction predictions for exploration of protein networks

PDZ domains recognise short sequence motifs at the extreme C-termini of proteins. A model based on microarray data has been recently published for predicting the binding preferences of PDZ domains to five residue long C-terminal sequences. Here we investigated the potential of this predictor for discovering novel protein interactions that involve PDZ domains. When tested on real negative data assembled from published literature, the predictor displayed a high false positive rate (FPR). We predicted and experimentally validated interactions between four PDZ domains derived from the human proteins MAGI1 and SCRIB and 19 peptides derived from human and viral C-termini of proteins. Measured binding intensities did not correlate with prediction scores, and the high FPR of the predictor was confirmed. Results indicate that limitations of the predictor may arise from an incomplete model definition and improper training of the model. Taking into account these limitations, we identified several novel putative interactions between PDZ domains of MAGI1 and SCRIB and the C-termini of the proteins FZD4, ARHGAP6, NET1, TANC1, GLUT7, MARCH3, MAS, ABC1, DLL1, TMEM215 and CYSLTR2. These proteins are localised to the membrane or suggested to act close to it and are often involved in G protein signalling. Furthermore, we showed that, while extension of minimal interacting domains or peptides toward tandem constructs or longer peptides never suppressed their ability to interact, the measured affinities and inferred specificity patterns often changed significantly. This suggests that if protein fragments interact, the full length proteins are also likely to interact, albeit possibly with altered affinities and specificities. Therefore, predictors dealing with protein fragments are promising tools for discovering protein interaction networks but their application to predict binding preferences within networks may be limited.     

Role of electrostatic interactions in PDZ domain ligand recognition

PDZ domains are protein-protein interaction modules that normally recognize short C-terminal peptides. The apparent requirement for a ligand with a free terminal carboxylate group has led to the proposal that electrostatic interactions with the terminus play a significant role in recognition. However, this model has been called into question by the more recent finding that PDZ domains can recognize some internal peptide motifs that occur within a specific secondary structure context. Although these motifs bind at the same interface, they lack a terminal charge. Here we have investigated the role of electrostatics in PDZ-mediated recognition in the mouse alpha1-syntrophin PDZ domain by examining the salt dependence of binding to both terminal and internal ligands and the effects of mutating a conserved basic residue previously proposed to play a role in electrostatic recognition. These studies indicate that direct electrostatic interactions with the peptide terminus do not play a significant energetic role in binding. Additional chemical modification studies of the peptide terminus support a model in which steric and hydrogen bonding complementarity play a primary role in recognition specificity. Peptides with a free carboxy terminus, or presented within a specific structural context, can satisfy these requirements.     

Distinct binding specificity of the multiple PDZ domains of INADL, a human protein with homology to INAD from Drosophila melanogaster

PDZ domains are protein-protein interaction modules that typically bind to short peptide sequences at the carboxyl terminus of target proteins. Proteins containing multiple PDZ domains often bind to different trans-membrane and intracellular proteins, playing a central role as organizers of multimeric complexes. To characterize the rules underlying the binding specificity of different PDZ domains, we have assembled a novel repertoire of random peptides that are displayed at high density at the carboxyl terminus of the capsid D protein of bacteriophage lambda. We have exploited this combinatorial library to determine the peptide binding preference of the seven PDZ domains of human INADL, a multi-PDZ protein that is homologous to the INAD protein of Drosophila melanogaster. This approach has permitted the determination of the consensus ligand for each PDZ domain and the assignment to class I, class II, and to a new specificity class, class IV, characterized by the presence of an acidic residue at the carboxyl-terminal position. Homology modeling and site-directed mutagenesis experiments confirmed the involvement of specific residues at contact positions in determining the domain binding preference. However, these experiments failed to reveal simple rules that would permit the association of the chemical characteristics of any given residue in the peptide binding pocket to the preference for specific amino acid sequences in the ligand peptide. Rather, they suggested that to infer the binding preference of any PDZ domain, it is necessary to simultaneously take into account all contact positions by using computational procedures. For this purpose we extended the SPOT algorithm, originally developed for SH3 domains, to evaluate the probability that any peptide would bind to any given PDZ domain.