An oriented peptide array library (OPAL) strategy to study protein-protein interactions

Activation loop phosphorylation and cGMP saturation of PKG regulate egress of malaria parasites

The cGMP-dependent protein kinase (PKG) is the sole cGMP sensor in malaria parasites, acting as an essential signalling hub to govern key developmental processes throughout the parasite life cycle. Despite the importance of PKG in the clinically relevant asexual blood stages, many aspects of malarial PKG regulation, including the importance of phosphorylation, remain poorly understood. Here we use genetic and biochemical approaches to show that reduced cGMP binding to cyclic nucleotide binding domain B does not affect in vitro kinase activity but prevents parasite egress. Similarly, we show that phosphorylation of a key threonine residue (T695) in the activation loop is dispensable for kinase activity in vitro but is essential for in vivo PKG function, with loss of T695 phosphorylation leading to aberrant phosphorylation events across the parasite proteome and changes to the substrate specificity of PKG. Our findings indicate that Plasmodium PKG is uniquely regulated to transduce signals crucial for malaria parasite development.

Engineered FHA domains can bind to a variety of Phosphothreonine-containing peptides

Antibodies play a crucial role in monitoring post-translational modifications, like phosphorylation, which regulates protein activity and location; however, commercial polyclonal and monoclonal antibodies have limitations in renewability and engineering compared to recombinant affinity reagents. A scaffold based on the Forkhead-associated domain (FHA) has potential as a selective affinity reagent for this post-translational modification. Engineered FHA domains, termed phosphothreonine-binding domains (pTBDs), with limited cross-reactivity were isolated from an M13 bacteriophage display library by affinity selection with phosphopeptides corresponding to human mTOR, Chk2, 53BP1, and Akt1 proteins. To determine the specificity of the representative pTBDs, we focused on binders to the pT543 phosphopeptide (536-IDEDGENpTQIEDTEP-551) of the DNA repair protein 53BP1. ELISA and western blot experiments have demonstrated the pTBDs are specific to phosphothreonine, demonstrating the potential utility of pTBDs for monitoring the phosphorylation of specific threonine residues in clinically relevant human proteins.

Differential Binding and Conformational Dynamics of Tau Microtubule-Binding Repeats with a Preformed Amyloid-β Fibril Seed

Both senile plaques formed by amyloid-β (Aβ) and neurofibrillary tangles (NFTs) comprised of tau are pathological hallmarks of Alzheimer's disease (AD). The accumulation of NFTs better correlates with the loss of cognitive function than senile plaques, but NFTs are rarely observed without the presence of senile plaques. Hence, cross-seeding of tau by preformed Aβ amyloid fibril seeds has been proposed to drive the aggregation of tau and exacerbate AD progression, but the molecular mechanism remains unknown. Here, we first identified cross-interaction hotspots between Aβ and tau using atomistic discrete molecular dynamics simulations (DMD) and confirmed the critical role of the four microtubule-binding repeats of tau (R1-R4) in the cross-interaction with Aβ. We further investigated the binding structure and dynamics of each tau repeat with a preformed Aβ fibril seed. Specifically, R1 and R3 preferred to bind the Aβ fibril lateral surface instead of the elongation end. In contrast, R2 and R4 had higher binding propensities to the fibril elongation end than the lateral surface, enhancing β-sheet content by forming hydrogen bonds with the exposed hydrogen bond donors and acceptors. Together, our results suggest that the four repeats play distinct roles in driving the binding of tau to different surfaces of an Aβ fibril seed. Binding of tau to the lateral surface of Aβ fibril can increase the local concentration, while the binding to the elongation surface promotes β-sheet formation, both of which reduce the free energy barrier for tau aggregation nucleation and subsequent fibrillization.

SH2 Domains: Folding, Binding and Therapeutical Approaches

SH2 (Src Homology 2) domains are among the best characterized and most studied protein-protein interaction (PPIs) modules able to bind and recognize sequences presenting a phosphorylated tyrosine. This post-translational modification is a key regulator of a plethora of physiological and molecular pathways in the eukaryotic cell, so SH2 domains possess a fundamental role in cell signaling. Consequently, several pathologies arise from the dysregulation of such SH2-domains mediated PPIs. In this review, we recapitulate the current knowledge about the structural, folding stability, and binding properties of SH2 domains and their roles in molecular pathways and pathogenesis. Moreover, we focus attention on the different strategies employed to modulate/inhibit SH2 domains binding. Altogether, the information gathered points to evidence that pharmacological interest in SH2 domains is highly strategic to developing new therapeutics. Moreover, a deeper understanding of the molecular determinants of the thermodynamic stability as well as of the binding properties of SH2 domains appears to be fundamental in order to improve the possibility of preventing their dysregulated interactions.

Deconvoluting complex protein interaction networks through reductionist strategies in peptide biochemistry: Modern approaches and research questions

Following the decoding of the first human genome, researchers have vastly improved their understanding of cell biology and its regulation. As a result, it has become clear that it is not merely genetic information, but the aberrant changes in the functionality and connectivity of its encoded proteins that drive cell response to periods of stress and external cues. Therefore, proper utilization of refined methods that help to describe protein signalling or regulatory networks (i.e., functional connectivity), can help us understand how change in the signalling landscape effects the cell. However, given the vast complexity in 'how and when' proteins communicate or interact with each other, it is extremely difficult to define, characterize, and understand these interaction networks in a tangible manner. Herein lies the challenge of tackling the functional proteome; its regulation is encoded in multiple layers of interaction, chemical modification and cell compartmentalization. To address and refine simple research questions, modern reductionist strategies in protein biochemistry have successfully used peptide-based experiments; their summation helping to simplify the overall complexity of these protein interaction networks. In this way, peptides are powerful tools used in fundamental research that can be readily applied to comparative biochemical research. Understanding and defining how proteins interact is one of the key aspects towards understanding how the proteome functions. To date, reductionist peptide-based research has helped to address a wide range of proteome-related research questions, including the prediction of enzymes substrates, identification of posttranslational modifications, and the annotation of protein interaction partners. Peptide arrays have been used to identify the binding specificity of reader domains, which are able to recognise the posttranslational modifications; forming dynamic protein interactions that are dependent on modification state. Finally, representing one of the fastest growing classes of inhibitor molecules, peptides are now begin explored as "disruptors" of protein-protein interactions or enzyme activity. Collectively, this review will discuss the use of peptides, peptide arrays, peptide-oriented computational biochemistry as modern reductionist strategies in deconvoluting the functional proteome.

Phospho-Form Specific Substrates of Protein Kinase B (AKT1)

Protein kinase B (AKT1) is hyper-activated in diverse human tumors. AKT1 is activated by phosphorylation at two key regulatory sites, Thr308 and Ser473. Active AKT1 phosphorylates many, perhaps hundreds, of downstream cellular targets in the cytosol and nucleus. AKT1 is well-known for phosphorylating proteins that regulate cell survival and apoptosis, however, the full catalog of AKT1 substrates remains unknown. Using peptide arrays, we recently discovered that each phosphorylated form of AKT1 (pAKT1^S473, pAKT1^T308, and ppAKT1^S473,T308) has a distinct substrate specificity, and these data were used to predict potential new AKT1 substrates. To test the high-confidence predictions, we synthesized target peptides representing putative AKT1 substrates. Peptides substrates were synthesized by solid phase synthesis and their purity was confirmed by mass spectrometry. Most of the predicted peptides showed phosphate accepting activity similar to or greater than that observed with a peptide derived from a well-established AKT1 substrate, glycogen synthase kinase 3β (GSK-3β). Among the novel substrates, AKT1 was most active with peptides representing PIP3-binding protein Rab11 family-interacting protein 2 and cysteinyl leukotriene receptor 1, indicating their potential role in AKT1-dependent cellular signaling. The ppAKT1^S473,T308 enzyme was highly selective for peptides containing a patch of basic residues at −5, −4, −3 and aromatic residues (Phe/Tyr) at +1 positions from the phosphorylation site. The pAKT1^S473 variant preferred more acidic peptides, Ser or Pro at +4, and was agnostic to the residue at −5. The data further support our hypothesis that Ser473 phosphorylation plays a key role in modulating AKT1 substrate selectivity.

Methods for Membranes and Other Absorbent Surfaces

Membrane arrays are a unique array platform option for the detection of multiple analytes or materials simultaneously. Their naturally absorptive properties and near universal use in various laboratory methods make it an excellent source with which to probe multiple factors simultaneously. Any liquid sample type can be probed, from bacterial strains, tissue lysates, secreted proteins, to DNA aptamers. Below, we will describe some considerations in how to print a membrane array and then a specific usage of the membrane arrays as it relates to a sandwich-based antibody array technique for simultaneously detection of secreted proteins in a liquid sample.

Phosphorylation-dependent substrate selectivity of protein kinase B (AKT1)

Protein kinase B (AKT1) is a central node in a signaling pathway that regulates cell survival. The diverse pathways regulated by AKT1 are communicated in the cell via the phosphorylation of perhaps more than 100 cellular substrates. AKT1 is itself activated by phosphorylation at Thr-308 and Ser-473. Despite the fact that these phosphorylation sites are biomarkers for cancers and tumor biology, their individual roles in shaping AKT1 substrate selectivity are unknown. We recently developed a method to produce AKT1 with programmed phosphorylation at either or both of its key regulatory sites. Here, we used both defined and randomized peptide libraries to map the substrate selectivity of site-specific, singly and doubly phosphorylated AKT1 variants. To globally quantitate AKT1 substrate preferences, we synthesized three AKT1 substrate peptide libraries: one based on 84 "known" substrates and two independent and larger oriented peptide array libraries (OPALs) of ∼10¹¹ peptides each. We found that each phospho-form of AKT1 has common and distinct substrate requirements. Compared with pAKT1^T308, the addition of Ser-473 phosphorylation increased AKT1 activities on some, but not all of its substrates. This is the first report that Ser-473 phosphorylation can positively or negatively regulate kinase activity in a substrate-dependent fashion. Bioinformatics analysis indicated that the OPAL-activity data effectively discriminate known AKT1 substrates from closely related kinase substrates. Our results also enabled predictions of novel AKT1 substrates that suggest new and expanded roles for AKT1 signaling in regulating cellular processes.

Surface Loops in a Single SH2 Domain Are Capable of Encoding the Spectrum of Specificity of the SH2 Family

Src homology 2 (SH2) domains play an essential role in cellular signal transduction by binding to proteins phosphorylated on Tyr residue. Although Tyr phosphorylation (pY) is a prerequisite for binding for essentially all SH2 domains characterized to date, different SH2 domains prefer specific sequence motifs C-terminal to the pY residue. Because all SH2 domains adopt the same structural fold, it is not well understood how different SH2 domains have acquired the ability to recognize distinct sequence motifs. We have shown previously that the EF and BG loops that connect the secondary structure elements on an SH2 domain dictate its specificity. In this study, we investigated if these surface loops could be engineered to encode diverse specificities. By characterizing a group of SH2 variants selected by different pY peptides from phage-displayed libraries, we show that the EF and BG loops of the Fyn SH2 domain can encode a wide spectrum of specificities, including all three major specificity classes (p + 2, p + 3 and p + 4) of the SH2 domain family. Furthermore, we found that the specificity of a given variant correlates with the sequence feature of the bait peptide used for its isolation, suggesting that an SH2 domain may acquire specificity by co-evolving with its ligand. Intriguingly, we found that the SH2 variants can employ a variety of different mechanisms to confer the same specificity, suggesting the EF and BG loops are highly flexible and adaptable. Our work provides a plausible mechanism for the SH2 domain to acquire the wide spectrum of specificity observed in nature through loop variation with minimal disturbance to the SH2 fold. It is likely that similar mechanisms may have been employed by other modular interaction domains to generate diversity in specificity.

Engineered SH2 domains with tailored specificities and enhanced affinities for phosphoproteome analysis

Protein phosphorylation is the most abundant post-translational modification in cells. Src homology 2 (SH2) domains specifically recognize phosphorylated tyrosine (pTyr) residues to mediate signaling cascades. A conserved pocket in the SH2 domain binds the pTyr side chain and the EF and BG loops determine binding specificity. By using large phage-displayed libraries, we engineered the EF and BG loops of the Fyn SH2 domain to alter specificity. Engineered SH2 variants exhibited distinct specificity profiles and were able to bind pTyr sites on the epidermal growth factor receptor, which were not recognized by the wild-type Fyn SH2 domain. Furthermore, mass spectrometry showed that SH2 variants with additional mutations in the pTyr-binding pocket that enhanced affinity were highly effective for enrichment of diverse pTyr peptides within the human proteome. These results showed that engineering of the EF and BG loops could be used to tailor SH2 domain specificity, and SH2 variants with diverse specificities and high affinities for pTyr residues enabled more comprehensive analysis of the human phosphoproteome. STATEMENT: Src Homology 2 (SH2) domains are modular domains that recognize phosphorylated tyrosine embedded in proteins, transducing these post-translational modifications into cellular responses. Here we used phage display to engineer hundreds of SH2 domain variants with altered binding specificities and enhanced affinities, which enabled efficient and differential enrichment of the human phosphoproteome for analysis by mass spectrometry. These engineered SH2 domain variants will be useful tools for elucidating the molecular determinants governing SH2 domains binding specificity and for enhancing analysis and understanding of the human phosphoproteome.

Global substrate specificity profiling of post-translational modifying enzymes

Enzymes that modify the proteome, referred to as post-translational modifying (PTM) enzymes, are central regulators of cellular signaling. Determining the substrate specificity of PTM enzymes is a critical step in unraveling their biological functions both in normal physiological processes and in disease states. Advances in peptide chemistry over the last century have enabled the rapid generation of peptide libraries for querying substrate recognition by PTM enzymes. In this article, we highlight various peptide-based approaches for analysis of PTM enzyme substrate specificity. We focus on the application of these technologies to proteases and also discuss specific examples in which they have been used to uncover the substrate specificity of other types of PTM enzymes, such as kinases. In particular, we highlight our multiplex substrate profiling by mass spectrometry (MSP-MS) assay, which uses a rationally designed, physicochemically diverse library of tetradecapeptides. We show how this method has been applied to PTM enzymes to uncover biological function, and guide substrate and inhibitor design. We also briefly discuss how this technique can be combined with other methods to gain a systems-level understanding of PTM enzyme regulation and function.

Characterizing SH2 Domain Specificity and Network Interactions Using SPOT Peptide Arrays

Src Homology 2 (SH2) domains are protein interaction modules that recognize and bind tyrosine phosphorylated ligands. Their ability to distinguish binding to over thousands of potential phosphotyrosine (pTyr) ligands within the cell is critical for the fidelity of receptor tyrosine kinase (RTK) signaling. Within humans there are over a hundred SH2 domains with more than several thousand potential ligands across many cell types and cell states. Therefore, defining the specificity of individual SH2 domains is critical for predicting and identifying their physiological ligands. Here, in this chapter, I describe the broad use of SPOT peptide arrays for examining SH2 domain specificity. An orientated peptide array library (OPAL) approach can uncover both favorable and non-favorable residues, thus providing an in-depth analysis to SH2 specificity. Moreover, I discuss the application of SPOT arrays for paneling SH2 ligand binding with physiological peptides.

Multiplex Substrate Profiling by Mass Spectrometry for Kinases as a Method for Revealing Quantitative Substrate Motifs

The more than 500 protein kinases comprising the human kinome catalyze hundreds of thousands of phosphorylation events to regulate a diversity of cellular functions; however, the extended substrate specificity is still unknown for many of these kinases. We report here a method for quantitatively describing kinase substrate specificity using an unbiased peptide library-based approach with direct measurement of phosphorylation by tandem liquid chromatography-tandem mass spectrometry (LC-MS/MS) peptide sequencing (multiplex substrate profiling by mass spectrometry, MSP-MS). This method can be deployed with as low as 10 nM enzyme to determine activity against S/T/Y-containing peptides; additionally, label-free quantitation is used to ascertain catalytic efficiency values for individual peptide substrates in the multiplex assay. Using this approach we developed quantitative motifs for a selection of kinases from each branch of the kinome, with and without known substrates, highlighting the applicability of the method. The sensitivity of this approach is evidenced by its ability to detect phosphorylation events from nanogram quantities of immunoprecipitated material, which allows for wider applicability of this method. To increase the information content of the quantitative kinase motifs, a sublibrary approach was used to expand the testable sequence space within a peptide library of approximately 100 members for CDK1, CDK7, and CDK9. Kinetic analysis of the HIV-1 Tat (transactivator of transcription)-positive transcription elongation factor b (P-TEFb) interaction allowed for localization of the P-TEFb phosphorylation site as well as characterization of the stimulatory effect of Tat on P-TEFb catalytic efficiency.

Introduction: History of SH2 Domains and Their Applications

The Src Homology 2 (SH2) domain is the prototypical protein interaction module that lies at the heart of phosphotyrosine signaling. Since its serendipitous discovery, there has been a tremendous advancement in technologies and an array of techniques available for studying SH2 domains and phosphotyrosine signaling. In this chapter, we provide a glimpse of the history of SH2 domains and describe many of the tools and techniques that have been developed along the way and discuss future directions for SH2 domain studies. We highlight the gist of each chapter in this volume in the context of: the structural biology and phosphotyrosine binding; characterizing SH2 specificity and generating prediction models; systems biology and proteomics; SH2 domains in signal transduction; and SH2 domains in disease, diagnostics, and therapeutics. Many of the individual chapters provide an in-depth approach that will allow scientists to interrogate the function and role of SH2 domains.

Using oriented peptide array libraries to evaluate methylarginine-specific antibodies and arginine methyltransferase substrate motifs

Signal transduction in response to stimuli relies on the generation of cascades of posttranslational modifications that promote protein-protein interactions and facilitate the assembly of distinct signaling complexes. Arginine methylation is one such modification, which is catalyzed by a family of nine protein arginine methyltransferases, or PRMTs. Elucidating the substrate specificity of each PRMT will promote a better understanding of which signaling networks these enzymes contribute to. Although many PRMT substrates have been identified, and their methylation sites mapped, the optimal target motif for each of the nine PRMTs has not been systematically addressed. Here we describe the use of Oriented Peptide Array Libraries (OPALs) to methodically dissect the preferred methylation motifs for three of these enzymes - PRMT1, CARM1 and PRMT9. In parallel, we show that an OPAL platform with a fixed methylarginine residue can be used to validate the methyl-specific and sequence-specific properties of antibodies that have been generated against different PRMT substrates, and can also be used to confirm the pan nature of some methylarginine-specific antibodies.

Pin1: Intimate involvement with the regulatory protein kinase networks in the global phosphorylation landscape

BACKGROUND

Protein phosphorylation is a universal regulatory mechanism that involves an extensive network of protein kinases. The discovery of the phosphorylation-dependent peptidyl-prolyl isomerase Pin1 added an additional layer of complexity to these regulatory networks.

SCOPE OF REVIEW

We have evaluated interactions between Pin1 and the regulatory kinome and proline-dependent phosphoproteome taking into consideration findings from targeted studies as well as data that has emerged from systematic phosphoproteomic workflows and from curated protein interaction databases.

MAJOR CONCLUSIONS

The relationship between Pin1 and the regulatory protein kinase networks is not restricted simply to the recognition of proteins that are substrates for proline-directed kinases. In this respect, Pin1 itself is phosphorylated in cells by protein kinases that modulate its functional properties. Furthermore, the phosphorylation-dependent targets of Pin1 include a number of protein kinases as well as other enzymes such as phosphatases and regulatory subunits of kinases that modulate the actions of protein kinases.

GENERAL SIGNIFICANCE

As a result of its interactions with numerous protein kinases and their substrates, as well as itself being a target for phosphorylation, Pin1 has an intricate relationship with the regulatory protein kinase and phosphoproteomic networks that orchestrate complex cellular processes and respond to environmental cues. This article is part of a Special Issue entitled Proline-directed Foldases: Cell Signaling Catalysts and Drug Targets.

Global analysis of human nonreceptor tyrosine kinase specificity using high-density peptide microarrays

Protein kinases phosphorylate substrates in the context of specific phosphorylation site sequence motifs. The knowledge of the specific sequences that are recognized by kinases is useful for mapping sites of phosphorylation in protein substrates and facilitates the generation of model substrates to monitor kinase activity. Here, we have adapted a positional scanning peptide library method to a microarray format that is suitable for the rapid determination of phosphorylation site motifs for tyrosine kinases. Peptide mixtures were immobilized on glass slides through a layer of a tyrosine-free Y33F mutant avidin to facilitate the analysis of phosphorylation by radiolabel assay. A microarray analysis provided qualitatively similar results in comparison with the solution phase peptide library “macroarray” method. However, much smaller quantities of kinases were required to phosphorylate peptides on the microarrays, which thus enabled a proteome scale analysis of kinase specificity. We illustrated this capability by microarray profiling more than 80% of the human nonreceptor tyrosine kinases (NRTKs). Microarray results were used to generate a universal NRTK substrate set of 11 consensus peptides for in vitro kinase assays. Several substrates were highly specific for their cognate kinases, which should facilitate their incorporation into kinase-selective biosensors.

The development and application of a quantitative peptide microarray based approach to protein interaction domain specificity space

Protein interaction domain (PID) linear peptide motif interactions direct diverse cellular processes in a specific and coordinated fashion. PID specificity, or the interaction selectivity derived from affinity preferences between possible PID-peptide pairs is the basis of this ability. Here, we develop an integrated experimental and computational cellulose peptide conjugate microarray (CPCMA) based approach for the high throughput analysis of PID specificity that provides unprecedented quantitative resolution and reproducibility. As a test system, we quantify the specificity preferences of four Src Homology 2 domains and 124 physiological phosphopeptides to produce a novel quantitative interactome. The quantitative data set covers a broad affinity range, is highly precise, and agrees well with orthogonal biophysical validation, in vivo interactions, and peptide library trained algorithm predictions. In contrast to preceding approaches, the CPCMAs proved capable of confidently assigning interactions into affinity categories, resolving the subtle affinity contributions of residue correlations, and yielded predictive peptide motif affinity matrices. Unique CPCMA enabled modes of systems level analysis reveal a physiological interactome with expected node degree value decreasing as a function of affinity, resulting in minimal high affinity binding overlap between domains; uncover that Src Homology 2 domains bind ligands with a similar average affinity yet strikingly different levels of promiscuity and binding dynamic range; and parse with unprecedented quantitative resolution contextual factors directing specificity. The CPCMA platform promises broad application within the fields of PID specificity, synthetic biology, specificity focused drug design, and network biology.

Enhanced prediction of Src homology 2 (SH2) domain binding potentials using a fluorescence polarization-derived c-Met, c-Kit, ErbB, and androgen receptor interactome

Many human diseases are associated with aberrant regulation of phosphoprotein signaling networks. Src homology 2 (SH2) domains represent the major class of protein domains in metazoans that interact with proteins phosphorylated on the amino acid residue tyrosine. Although current SH2 domain prediction algorithms perform well at predicting the sequences of phosphorylated peptides that are likely to result in the highest possible interaction affinity in the context of random peptide library screens, these algorithms do poorly at predicting the interaction potential of SH2 domains with physiologically derived protein sequences. We employed a high throughput interaction assay system to empirically determine the affinity between 93 human SH2 domains and phosphopeptides abstracted from several receptor tyrosine kinases and signaling proteins. The resulting interaction experiments revealed over 1000 novel peptide-protein interactions and provided a glimpse into the common and specific interaction potentials of c-Met, c-Kit, GAB1, and the human androgen receptor. We used these data to build a permutation-based logistic regression classifier that performed considerably better than existing algorithms for predicting the interaction potential of several SH2 domains.

Semi-supervised prediction of SH2-peptide interactions from imbalanced high-throughput data

Src homology 2 (SH2) domains are the largest family of the peptide-recognition modules (PRMs) that bind to phosphotyrosine containing peptides. Knowledge about binding partners of SH2-domains is key for a deeper understanding of different cellular processes. Given the high binding specificity of SH2, in-silico ligand peptide prediction is of great interest. Currently however, only a few approaches have been published for the prediction of SH2-peptide interactions. Their main shortcomings range from limited coverage, to restrictive modeling assumptions (they are mainly based on position specific scoring matrices and do not take into consideration complex amino acids inter-dependencies) and high computational complexity. We propose a simple yet effective machine learning approach for a large set of known human SH2 domains. We used comprehensive data from micro-array and peptide-array experiments on 51 human SH2 domains. In order to deal with the high data imbalance problem and the high signal-to-noise ration, we casted the problem in a semi-supervised setting. We report competitive predictive performance w.r.t. state-of-the-art. Specifically we obtain 0.83 AUC ROC and 0.93 AUC PR in comparison to 0.71 AUC ROC and 0.87 AUC PR previously achieved by the position specific scoring matrices (PSSMs) based SMALI approach. Our work provides three main contributions. First, we showed that better models can be obtained when the information on the non-interacting peptides (negative examples) is also used. Second, we improve performance when considering high order correlations between the ligand positions employing regularization techniques to effectively avoid overfitting issues. Third, we developed an approach to tackle the data imbalance problem using a semi-supervised strategy. Finally, we performed a genome-wide prediction of human SH2-peptide binding, uncovering several findings of biological relevance. We make our models and genome-wide predictions, for all the 51 SH2-domains, freely available to the scientific community under the following URLs: http://www.bioinf.uni-freiburg.de/Software/SH2PepInt/SH2PepInt.tar.gz and http://www.bioinf.uni-freiburg.de/Software/SH2PepInt/Genome-wide-predictions.tar.gz, respectively.

Protein tyrosine phosphatase SHP2/PTPN11 mistargeting as a consequence of SH2-domain point mutations associated with Noonan Syndrome and leukemia

SHP2/PTPN11 is a key regulator of cytokine, growth factor and integrin signaling. SHP2 influences cell survival, proliferation and differentiation by regulating major signaling pathways. Mutations in PTPN11 cause severe diseases like Noonan, LEOPARD syndrome or leukemia. Whereas several of these mutations result in altered enzymatic activity due to impaired auto-inhibition, not all disease patterns can be explained by this mechanism. In this study we analyzed altered binding properties of disease-related SHP2-mutants bearing point mutations within the SH2-domain (T42A, E139D, and R138Q). Mutants were chosen according to SPR assays, which revealed different binding properties of mutated SH2 towards phosphorylated receptor peptides. To analyze global changes in mutant binding properties we applied quantitative mass spectrometry (SILAC). Using an in vitro approach we identified overall more than 1000 protein candidates, which specifically bind to the SH2-domain of SHP2. We discovered that mutations in the SH2-domain selectively affected protein enrichment by altering the binding capacity of the SH2-domain. Mutation-dependent, enhanced or reduced exposure of SHP2 to its binding partners could have an impact on the dynamics of signaling networks. Thus, disease-associated mutants of SHP2 should not only be discussed in the context of deregulated auto-inhibition but also with respect to deregulated protein targeting of the SHP2 mutants.

BIOLOGICAL SIGNIFICANCE

Using quantitative mass spectrometry based proteomics we provided evidence that disease related mutations in SHP2 domains of SHP2 are able to influence SHP2 recruitment to its targets in mutation dependent manner. We discovered that mutations in the SH2-domain selectively affected protein enrichment ratios suggesting altered binding properties of the SH2-domain. We demonstrated that mutations within SHP2, which had been attributed to affect the enzymatic activity (i.e. affect the open/close status of SHP2), also differ in respect to binding properties. Our study indicates that SHP2 mutations need to be discussed not only in terms of deregulated auto-inhibition but also with respect to deregulated protein targeting properties of the SHP2 mutants. Discovery of the new binding partners for disease-related SHP2 mutants might provide a fruitful foundation for developing strategies targeting Noonan-associated leukemia.

Universal quantitative kinase assay based on diagonal SCX chromatography and stable isotope dimethyl labeling provides high-definition kinase consensus motifs for PKA and human Mps1

In order to understand cellular signaling, a clear understanding of kinase-substrate relationships is essential. Some of these relationships are defined by consensus recognition motifs present in substrates making them amendable for phosphorylation by designated kinases. Here, we explore a method that is based on two sequential steps of strong cation exchange chromatography combined with differential stable isotope labeling, to define kinase consensus motifs with high accuracy. We demonstrate the value of our method by evaluating the motifs of two very distinct kinases: cAMP regulated protein kinase A (PKA) and human monopolar spindle 1 (Mps1) kinase, also known as TTK. PKA is a well-studied basophilic kinase with a relatively well-defined motif and numerous known substrates in vitro and in vivo. Mps1, a kinase involved in chromosome segregation, has been less well characterized. Its substrate specificity is unclear and here we show that Mps1 is an acidophilic kinase with a striking tendency for phosphorylation of threonines. The final outcomes of our work are high-definition kinase consensus motifs for PKA and Mps1. Our generic method, which makes use of proteolytic cell lysates as a source for peptide-substrate libraries, can be implemented for any kinase present in the kinome.

The Lipid Transfer Protein StarD7: Structure, Function, and Regulation

The steroidogenic acute regulatory (StAR) protein-related lipid transfer (START) domain proteins constitute a family of evolutionarily conserved and widely expressed proteins that have been implicated in lipid transport, metabolism, and signaling. The 15 well-characterized mammalian START domain-containing proteins are grouped into six subfamilies. The START domain containing 7 mRNA encodes StarD7, a member of the StarD2/phosphatidylcholine transfer protein (PCTP) subfamily, which was first identified as a gene overexpressed in a choriocarcinoma cell line. Recent studies show that the StarD7 protein facilitates the delivery of phosphatidylcholine to the mitochondria. This review summarizes the latest advances in StarD7 research, focusing on the structural and biochemical features, protein-lipid interactions, and mechanisms that regulate StarD7 expression. The implications of the role of StarD7 in cell proliferation, migration, and differentiation are also discussed.

Phosphotyrosine signaling proteins that drive oncogenesis tend to be highly interconnected

Mutation and overexpression of receptor tyrosine kinases or the proteins they regulate serve as oncogenic drivers in diverse cancers. To better understand receptor tyrosine kinase signaling and its link to oncogenesis, we used protein microarrays to systematically and quantitatively measure interactions between virtually every SH2 or PTB domain encoded in the human genome and all known sites of tyrosine phosphorylation on 40 receptor tyrosine kinases and on most of the SH2 and PTB domain-containing adaptor proteins. We found that adaptor proteins, like RTKs, have many high affinity bindings sites for other adaptor proteins. In addition, proteins that drive cancer, including both receptors and adaptor proteins, tend to be much more highly interconnected via networks of SH2 and PTB domain-mediated interactions than nononcogenic proteins. Our results suggest that network topological properties such as connectivity can be used to prioritize new drug targets in this well-studied family of signaling proteins.

Specificity profiling of protein-binding domains using one-bead-one-compound Peptide libraries

One-bead-one-compound (OBOC) libraries consist of structurally related compounds (e.g., peptides) covalently attached to a solid support, with each resin bead carrying a unique compound. OBOC libraries of high structural diversity can be rapidly synthesized and screened without the need for any special equipment, and therefore can be employed in any chemical or biochemical laboratory. OBOC peptide libraries have been widely used to map the ligand specificity of proteins, to determine the substrate specificity of enzymes, and to develop inhibitors against macromolecular targets. They have proven particularly useful in profiling the binding specificity of protein modular domains (e.g., SH2 domains, BIR domains, and PDZ domains); subsequently, the specificity information can be used to predict the protein targets of these domains. The protocols outlined in this article describe the methodologies for synthesizing and screening OBOC peptide libraries against SH2 and PDZ domains, and the related data analysis. Curr. Protoc. Chem. Biol. 4:331-355 © 2012 by John Wiley & Sons, Inc.

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases.

High-throughput analysis of peptide-binding modules

Modular protein interaction domains (PIDs) that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some PIDs such as SH2, 14-3-3, Chromo, and Bromo domains serve to recognize posttranslational modification (PTM) of amino acids (such as phosphorylation, acetylation, methylation, etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PSD-95/Discs-large/ZO-1 (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 (HTP) 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 associated with HTP analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of PIDs 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.

Probing subunit-subunit interactions in the yeast vacuolar ATPase by peptide arrays

BACKGROUND

Vacuolar (H(+))-ATPase (V-ATPase; V(1)V(o)-ATPase) is a large multisubunit enzyme complex found in the endomembrane system of all eukaryotic cells where its proton pumping action serves to acidify subcellular organelles. In the plasma membrane of certain specialized tissues, V-ATPase functions to pump protons from the cytoplasm into the extracellular space. The activity of the V-ATPase is regulated by a reversible dissociation mechanism that involves breaking and re-forming of protein-protein interactions in the V(1)-ATPase - V(o)-proton channel interface. The mechanism responsible for regulated V-ATPase dissociation is poorly understood, largely due to a lack of detailed knowledge of the molecular interactions that are responsible for the structural and functional link between the soluble ATPase and membrane bound proton channel domains.

METHODOLOGY/PRINCIPAL FINDINGS

To gain insight into where some of the stator subunits of the V-ATPase associate with each other, we have developed peptide arrays from the primary sequences of V-ATPase subunits. By probing the peptide arrays with individually expressed V-ATPase subunits, we have identified several key interactions involving stator subunits E, G, C, H and the N-terminal domain of the membrane bound a subunit.

CONCLUSIONS

The subunit-peptide interactions identified from the peptide arrays complement low resolution structural models of the eukaryotic vacuolar ATPase obtained from transmission electron microscopy. The subunit-subunit interaction data are discussed in context of our current model of reversible enzyme dissociation.

SRC Homology 2 Domain Binding Sites in Insulin, IGF-1 and FGF receptor mediated signaling networks reveal an extensive potential interactome

Specific peptide ligand recognition by modular interaction domains is essential for the fidelity of information flow through the signal transduction networks that control cell behavior in response to extrinsic and intrinsic stimuli. Src homology 2 (SH2) domains recognize distinct phosphotyrosine peptide motifs, but the specific sites that are phosphorylated and the complement of available SH2 domains varies considerably in individual cell types. Such differences are the basis for a wide range of available protein interaction microstates from which signaling can evolve in highly divergent ways. This underlying complexity suggests the need to broadly map the signaling potential of systems as a prerequisite for understanding signaling in specific cell types as well as various pathologies that involve signal transduction such as cancer, developmental defects and metabolic disorders. This report describes interactions between SH2 domains and potential binding partners that comprise initial signaling downstream of activated fibroblast growth factor (FGF), insulin (Ins), and insulin-like growth factor-1 (IGF-1) receptors. A panel of 50 SH2 domains screened against a set of 192 phosphotyrosine peptides defines an extensive potential interactome while demonstrating the selectivity of individual SH2 domains. The interactions described confirm virtually all previously reported associations while describing a large set of potential novel interactions that imply additional complexity in the signaling networks initiated from activated receptors. This study of pTyr ligand binding by SH2 domains provides valuable insight into the selectivity that underpins complex signaling networks that are assembled using modular protein interaction domains.

Proteomics strategy to identify substrates of LNX, a PDZ domain-containing E3 ubiquitin ligase

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.

Computational analysis of interactomes: current and future perspectives for bioinformatics approaches to model the host-pathogen interaction space

Bacterial and viral pathogens affect their eukaryotic host partly by interacting with proteins of the host cell. Hence, to investigate infection from a systems' perspective we need to construct complete and accurate host-pathogen protein-protein interaction networks. Because of the paucity of available data and the cost associated with experimental approaches, any construction and analysis of such a network in the near future has to rely on computational predictions. Specifically, this challenge consists of a number of sub-problems: First, prediction of possible pathogen interactors (e.g. effector proteins) is necessary for bacteria and protozoa. Second, the prospective host binding partners have to be determined and finally, the impact on the host cell analyzed. This review gives an overview of current bioinformatics approaches to obtain and understand host-pathogen interactions. As an application example of the methods covered, we predict host-pathogen interactions of Salmonella and discuss the value of these predictions as a prospective for further research.

Deciphering enzyme function using peptide arrays

Enzymes are key molecules in signal-transduction pathways. However, only a small fraction of more than 500 human kinases, 300 human proteases and 200 human phosphatases is characterised so far. Peptide microarray based technologies for extremely efficient profiling of enzyme substrate specificity emerged in the last years. This technology reduces set-up time for HTS assays and allows the identification of downstream targets. Moreover, peptide microarrays enable optimisation of enzyme substrates. Focus of this review is on assay principles for measuring activities of kinases, phosphatases or proteases and on substrate identification/optimisation for kinases. Additionally, several examples for reliable identification of substrates for lysine methyl-transferases, histone deacetylases and SUMO-transferases are given. Finally, use of high-density peptide microarrays for the simultaneous profiling of kinase activities in complex biological samples like cell lysates or lysates of complete organisms is described. All published examples of peptide arrays used for enzyme profiling are summarised comprehensively.

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.

Dissecting phosphorylation networks: lessons learned from yeast

Protein phosphorylation continues to be regarded as one of the most important post-translational modifications found in eukaryotes and has been implicated in key roles in the development of a number of human diseases. In order to elucidate roles for the 518 human kinases, phosphorylation has routinely been studied using the budding yeast Saccharomyces cerevisiae as a model system. In recent years, a number of technologies have emerged to globally map phosphorylation in yeast. In this article, we review these technologies and discuss how these phosphorylation mapping efforts have shed light on our understanding of kinase signaling pathways and eukaryotic proteomic networks in general.

Network evolution: rewiring and signatures of conservation in signaling

The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.

Protein interaction networks control virtually all cellular processes. The rules governing their evolution have remained elusive, as comprehensive protein interaction data is available for only a small number of very distant species, making evolutionary network studies difficult. Here we attempt to overcome this limitation by computationally constructing protein interaction networks for 23 relatively tightly spaced yeast species. We focus on networks consisting of kinase and peptide binding domain interactions, which play central roles in signaling pathways. These networks enable us to investigate evolutionary network mechanisms. We are able, for the first time, to accurately quantify the contribution of different rewiring mechanisms. Interaction change appears to be mainly accomplished through binding site evolution rather than through gene gain or loss. This is in contrast to other evolutionary processes, where gene duplication or deletion is a major driving factor. Moreover, our analysis reveals that interaction changes are very fast – fast enough that the number of changes saturates, i.e., the actual rate of change has been strongly underestimated in previous studies. Our analysis also reveals different mechanisms by which certain interactions are conserved throughout evolution. Our results likely transfer to other species and networks, and will benefit future evolutionary studies of signaling pathways.

Analysis of Jak2 catalytic function by peptide microarrays: the role of the JH2 domain and V617F mutation

Janus kinase 2 (JAK2) initiates signaling from several cytokine receptors and is required for biological responses such as erythropoiesis. JAK2 activity is controlled by regulatory proteins such as Suppressor of Cytokine Signaling (SOCS) proteins and protein tyrosine phosphatases. JAK2 activity is also intrinsically controlled by regulatory domains, where the pseudokinase (JAK homology 2, JH2) domain has been shown to play an essential role. The physiological role of the JH2 domain in the regulation of JAK2 activity was highlighted by the discovery of the acquired missense point mutation V617F in myeloproliferative neoplasms (MPN). Hence, determining the precise role of this domain is critical for understanding disease pathogenesis and design of new treatment modalities. Here, we have evaluated the effect of inter-domain interactions in kinase activity and substrate specificity. By using for the first time purified recombinant JAK2 proteins and a novel peptide micro-array platform, we have determined initial phosphorylation rates and peptide substrate preference for the recombinant kinase domain (JH1) of JAK2, and two constructs comprising both the kinase and pseudokinase domains (JH1-JH2) of JAK2. The data demonstrate that (i) JH2 drastically decreases the activity of the JAK2 JH1 domain, (ii) JH2 increased the K_m for ATP (iii) JH2 modulates the peptide preference of JAK2 (iv) the V617F mutation partially releases this inhibitory mechanism but does not significantly affect substrate preference or K_m for ATP. These results provide the biochemical basis for understanding the interaction between the kinase and the pseudokinase domain of JAK2 and identify a novel regulatory role for the JAK2 pseudokinase domain. Additionally, this method can be used to identify new regulatory mechanisms for protein kinases that provide a better platform for designing specific strategies for therapeutic approaches.

Studying binding specificities of peptide recognition modules by high-throughput phage display selections

Peptide recognition modules (PRMs) play critical roles in cellular processes, including differentiation, proliferation and cytoskeleton organization. PRMs normally bind to short linear motifs in protein ligands, and by so doing recruit proteins into signaling complexes. Based on the binding specificity profile of a PRM, one can predict putative natural interaction partners by searching genome databases. Candidate interaction partners can in turn provide clues to assemble potential in vivo protein complexes that the PRM may be involved with. Combinatorial peptide libraries have proven to be effective tools for profiling the binding specificities of PRMs. Herein, we describe high-throughput methods for the expression and purification of PRM proteins and the use of peptide-phage libraries for PRM specificity profiling. These high-throughput methods greatly expedite the study of PRM families on a genome-wide scale.

Studying of telomeric protein-protein interactions by Bi-molecular fluorescence complementation (BiFC) and peptide array-based assays

Studying protein-protein interactions is critical to our understanding of the signaling pathways. The Telomere Interactome is assembled around the telomeres and consists of proteins and factors from diverse pathways. Dissecting how this protein network contributes to telomere protection and length regulation requires the elucidation of the complex and dynamic interactions between the proteins within the interactome. Here, we focus on the Bi-molecular fluorescence complementation (BiFC) and peptide array methods that have proven vital in our studies of telomere protein interaction networks.

Two serine residues control sequential steps during catalysis of the yeast copper ATPase through different mechanisms that involve kinase-mediated phosphorylations

Ccc2, the yeast copper-transporting ATPase, pumps copper from the cytosol to the Golgi lumen. During its catalytic cycle, Ccc2 undergoes auto-phosphorylation on Asp(627) and uses the energy gained to transport copper across the cell membrane. We previously demonstrated that cAMP-dependent protein kinase (PKA) controls the energy interconversion (Cu)E∼P → E-P + Cu when Ser(258) is phosphorylated. We now demonstrate that Ser(258) is essential in vivo for copper homeostasis in extremely low copper and iron concentrations. The S258A mutation abrogates all PKA-mediated phosphorylations of Ccc2, whereas the S971A mutation leads to a 100% increase in its global regulatory phosphorylation. With S258A, the first-order rate constant of catalytic phosphorylation by ATP decreases from 0.057 to 0.030 s(-1), with an 8-fold decrease in the burst of initial phosphorylation. With the S971A mutant, the rate constant decreases to 0.007 s(-1). PKAi(5-24) decreases the amount of the aspartylphosphate intermediate (EP) in Ccc2 wt by 50% within 1 min, but not in S258A, S971A, or S258A/S971A. The increase of the initial burst and the extremely slow phosphorylation when the "phosphomimetic" mutant S258D was assayed (k = 0.0036 s(-1)), indicate that electrostatic and conformational (non-electrostatic) mechanisms are involved in the regulatory role of Ser(258). Accumulation of an ADP-insensitive form in S971A demonstrates that Ser(971) is required to accelerate the hydrolysis of the E-P form during turnover. We propose that Ser(258) and Ser(971) are under long-range intramolecular, reciprocal and concerted control, in a sequential process that is crucial for catalysis and copper transport in the yeast copper ATPase.

SH2 domains recognize contextual peptide sequence information to determine selectivity

Selective ligand recognition by modular protein interaction domains is a primary determinant of specificity in signaling pathways. Src homology 2 (SH2) domains fulfill this capacity immediately downstream of tyrosine kinases, acting to recruit their host polypeptides to ligand proteins harboring phosphorylated tyrosine residues. The degree to which SH2 domains are selective and the mechanisms underlying selectivity are fundamental to understanding phosphotyrosine signaling networks. An examination of interactions between 50 SH2 domains and a set of 192 phosphotyrosine peptides corresponding to physiological motifs within FGF, insulin, and IGF-1 receptor pathways indicates that individual SH2 domains have distinct recognition properties and exhibit a remarkable degree of selectivity beyond that predicted by previously described binding motifs. The underlying basis for such selectivity is the ability of SH2 domains to recognize both permissive amino acid residues that enhance binding and non-permissive amino acid residues that oppose binding in the vicinity of the essential phosphotyrosine. Neighboring positions affect one another so local sequence context matters to SH2 domains. This complex linguistics allows SH2 domains to distinguish subtle differences in peptide ligands. This newly appreciated contextual dependence substantially increases the accessible information content embedded in the peptide ligands that can be effectively integrated to determine binding. This concept may serve more broadly as a paradigm for subtle recognition of physiological ligands by protein interaction domains.

Loops govern SH2 domain specificity by controlling access to binding pockets

Cellular functions require specific protein-protein interactions that are often mediated by modular domains that use binding pockets to engage particular sequence motifs in their partners. Yet, how different members of a domain family select for distinct sequence motifs is not fully understood. The human genome encodes 120 Src homology 2 (SH2) domains (in 110 proteins), which mediate protein-protein interactions by binding to proteins with diverse phosphotyrosine (pTyr)-containing sequences. The structure of the SH2 domain of BRDG1 bound to a peptide revealed a binding pocket that was blocked by a loop residue in most other SH2 domains. Analysis of 63 SH2 domain structures suggested that the SH2 domains contain three binding pockets, which exhibit selectivity for the three positions after the pTyr in a peptide, and that SH2 domain loops defined the accessibility and shape of these pockets. Despite sequence variability in the loops, we identified conserved structural features in the loops of SH2 domains responsible for controlling access to these surface pockets. We engineered new loops in an SH2 domain that altered specificity as predicted. Thus, selective blockage of binding subsites or pockets by surface loops provides a molecular basis by which the diverse modes of ligand recognition by the SH2 domain may have evolved and provides a framework for engineering SH2 domains and designing SH2-specific inhibitors.

Targeting a novel N-terminal epitope of death receptor 5 triggers tumor cell death

Tumor necrosis factor-related apoptosis-inducing ligand receptors death receptor (DR) 4 and DR5 are potential targets for antibody-based cancer therapy. Activation of the proapoptotic DR5 in various cancer cells triggers the extrinsic and/or intrinsic pathway of apoptosis. It has been shown that there are several functional domains in the DR5 extracellular domain. The cysteine-rich domains of DR5 have a conservative role in tumor necrosis factor-related apoptosis-inducing ligand-DR5-mediated apoptosis, and the pre-ligand assembly domain within the N1-cap contributes to the ligand-independent formation of receptor complexes. However, the role of the N-terminal region (NTR) preceding the N1-cap of DR5 remains unclear. In this study, we demonstrate that NTR could mediate DR5 activation that transmits an apoptotic signal when bound to a specific agonistic monoclonal antibody. A novel epitope in the NTR of DR5 was identified by peptide array. Antibodies against the antigenic determinant showed high affinities for DR5 and triggered caspase activation in a time-dependent manner, suggesting the NTR of DR5 might function as a potential death-inducing region. Moreover, permutation analysis showed that Leu(6) was pivotal for the interaction of DR5 and the agonistic antibody. Synthetic wild-type epitopes eliminated the cytotoxicity of all three agonistic monoclonal antibodies, AD5-10, Adie-1, and Adie-2. These results indicate that the NTR of DR5 could be a potential target site for the development of new strategies for cancer immunotherapy. Also, our findings expand the current knowledge about DR5 extracellular functional domains and provide insights into the mechanism of DR5-mediated cell death.

Robust production of a peptide library using methodological synchronization

Peptide libraries have proven to be useful in applications such as substrate profiling, drug candidate screening and identifying protein-protein interaction partners. However, issues of fidelity, peptide length, and purity have been encountered when peptide libraries are chemically synthesized. Biochemically produced libraries, on the other hand, circumvent many of these issues due to the fidelity of the protein synthesis machinery. Using thioredoxin as an expression partner, a stably folded peptide scaffold (avian pancreatic polypeptide) and a compatible cleavage site for human rhinovirus 3C protease, we report a method that allows robust expression of a genetically encoded peptide library, which yields peptides of high purity. In addition, we report the use of methodological synchronization, an experimental design created for the production of a library, from initial cloning to peptide characterization, within a 5-week period of time. Total peptide yields ranged from 0.8% to 16%, which corresponds to 2-70 mg of pure peptide. Additionally, no correlation was observed between the ability to be expressed or overall yield of peptide-fusions and the intrinsic chemical characteristics of the peptides, indicating that this system can be used for a wide variety of peptide sequences with a range of chemical characteristics.

Binding specificity of SH2 domains: insight from free energy simulations

Cellular signal transduction pathways are controlled by specific protein-protein interactions mediated by the binding of short peptides to small modular interaction domains. To gain insights into the specificity of these interactions, the association of phosphotyrosine-containing peptides to Src Homology 2 (SH2) domains is characterized using computations. Molecular dynamics simulations based on high-resolution crystal structures complemented by homology models are used to calculate the absolute binding free energies for 25 SH2-peptides pairs. The calculations are carried out using a potential of mean force free energy simulations method with restraining potentials that was developed previously (Woo and Roux, Proc Natl Acad Sci USA 2005;102:6825-6830). The method is utilized in conjunction with an implicit solvent representation to reduce the computational cost to characterize the association of five SH2 domains and five peptides. Specificity is ascertained by directly comparing the affinities of a given SH2 domain binding for any of the different peptides. For three of the five SH2 domains, the computational results rank the native peptides, as the most preferred binding motif. For the remaining two SH2 domains, high affinity binding motifs other than the native peptides are identified. This study illustrates how free energy computations can complement experiments in trying to elucidate complex protein-protein interactions networks.

Peptide arrays for enzyme profiling

Enzymes are key molecules in signal transduction pathways. However, only a small fraction of more than 500 predicted human kinases, 250 proteases and 250 phosphatases is characterized so far. Peptide microarray-based technologies for extremely efficient profiling of enzyme substrate specificity emerged in the last years. Additionally, patterns of enzymatic activities could be used to fingerprint the status of cells or organisms. This technology reduces set-up time for HTS assays and allows the identification of downstream targets. Moreover, peptide microarrays enable optimization of enzyme substrates. A comprehensive overview regarding enzyme profiling using peptide microarrays is presented with special focus on assay principles.

Using peptide array to identify binding motifs and interaction networks for modular domains

Specific protein-protein interactions underlie all essential biological processes and form the basis of cellular signal transduction. The recognition of a short, linear peptide sequence in one protein by a modular domain in another represents a common theme of macromolecular recognition in cells, and the importance of this mode of protein-protein interaction is highlighted by the large number of peptide-binding domains encoded by the human genome. This phenomenon also provides a unique opportunity to identify protein-protein binding events using peptide arrays and complementary biochemical assays. Accordingly, high-density peptide array has emerged as a useful tool by which to map domain-mediated protein-protein interaction networks at the proteome level. Using the Src-homology 2 (SH2) and 3 (SH3) domains as examples, we describe the application of oriented peptide array libraries in uncovering specific motifs recognized by an SH2 domain and the use of high-density peptide arrays in identifying interaction networks mediated by the SH3 domain. Methods reviewed here could also be applied to other modular domains, including catalytic domains, that recognize linear peptide sequences.

Antimicrobial peptide arrays for detection of inactivated biothreat agents

Arrays of immobilized antimicrobial peptides are used to detect bacterial, viral, and rickettsial pathogens, including inactivated biothreat agents. These arrays differ from the many combinatorial peptide arrays described in the literature in that the peptides used here have naturally evolved to interact with and disrupt microbial membranes with high affinity but broad specificity. The interaction of these naturally occurring peptides with membranes of pathogens has been harnessed for the purpose of detection, with immobilized antimicrobial peptides acting as "capture" molecules in detection assays. Methods are presented for immobilizing the antimicrobial peptides in planar arrays, performing direct and sandwich assays, and detecting bound targets.

An integrated comparative phosphoproteomic and bioinformatic approach reveals a novel class of MPM-2 motifs upregulated in EGFRvIII-expressing glioblastoma cells

Glioblastoma (GBM, WHO grade IV) is an aggressively proliferative and invasive brain tumor that carries a poor clinical prognosis with a median survival of 9 to 12 months. In a prior phosphoproteomic study performed in the U87MG glioblastoma cell line, we identified tyrosine phosphorylation events that are regulated as a result of titrating EGFRvIII, a constitutively active mutant of the epidermal growth factor receptor (EGFR) associated with poor prognosis in GBM patients. In the present study, we have used the phosphoserine/phosphothreonine-specific antibody MPM-2 (mitotic protein monoclonal #2) to quantify serine/threonine phosphorylation events in the same cell lines. By employing a bioinformatic tool to identify amino acid sequence motifs regulated in response to increasing oncogene levels, a set of previously undescribed MPM-2 epitope sequence motifs orthogonal to the canonical "pS/pT-P" motif was identified. These motifs contain acidic amino acids in combinations of the -5, -2, +1, +3, and +5 positions relative to the phosphorylated amino acid. Phosphopeptides containing these motifs are upregulated in cells expressing EGFRvIII, raising the possibility of a general role for a previously unrecognized acidophilic kinase (e.g. casein kinase II (CK2)) in cell proliferation downstream of EGFR signaling.

Studying Cellular Processes and Detecting Disease with Protein Microarrays

Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications, and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.