The protein interaction network mediated by human SH3 domains

Revealing the role of the X25 domains through the characterization of truncated variants of amylopullulanase enzyme from Thermoanaerobacter brockii brockii

To understand the role of the X25 domains of the amylopullulanase enzyme from Thermoanaerobacter brockii brockii (T. brockii brockii), four truncated variants that are TbbApuΔX25-1-SH3 (S130-A1484), TbbApuΔX25-2-SH3 (T235-A1484), TbbApuΔX25-1-CBM20 (S130-P1254), and TbbApuΔX25-2-CBM20 (T235-P1254) were constructed, expressed and characterized together with the SH3 and CBM20 domain truncated variants (TbbApuΔSH3 (V1-A1484) and TbbApuΔCBM20 (V1-P1254). TbbApuΔSH3 showed improved affinity and specificity for both pullulan and soluble starch than full-length TbbApu with lower Km and higher kcat/Km values. It indicates that SH3 is a disposable domain without any effect on the activity and stability of the enzyme. However, TbbApuΔX25-1-SH3, TbbApuΔX25-2-SH3, TbbApuΔX25-1-CBM20, TbbApuΔX25-2-CBM20 (T235-P1254) and TbbApuΔCBM20 showed higher Km and lower kcat/Km values than TbbApuΔSH3 to both soluble starch and pullulan. It specifies that the X25 domains and CBM20 play an important role in both α-amylase and pullulanase activity. Also, it is revealed that while truncation of the CBM20 domain as starch binding domain (SBD) did not affect on raw starch binding ability of the enzyme, truncation of both X25 domains caused almost complete loss of the raw starch binding ability of the enzyme. All these results enlightened the function of the X25 domains that play a more crucial role than CBM20 in the enzyme's binding to raw starch and also play a crucial role in its activity.

Functional Classification and Interaction Selectivity Landscape of the Human SH3 Domain Superfamily

SRC homology 3 (SH3) domains are critical interaction modules that orchestrate the assembly of protein complexes involved in diverse biological processes. They facilitate transient protein-protein interactions by selectively interacting with proline-rich motifs (PRMs). A database search revealed 298 SH3 domains in 221 human proteins. Multiple sequence alignment of human SH3 domains is useful for phylogenetic analysis and determination of their selectivity towards PRM-containing peptides (PRPs). However, a more precise functional classification of SH3 domains is achieved by constructing a phylogenetic tree only from PRM-binding residues and using existing SH3 domain-PRP structures and biochemical data to determine the specificity within each of the 10 families for particular PRPs. In addition, the C-terminal proline-rich domain of the RAS activator SOS1 covers 13 of the 14 recognized proline-rich consensus sequence motifs, encompassing differential PRP pattern selectivity among all SH3 families. To evaluate the binding capabilities and affinities, we conducted fluorescence dot blot and polarization experiments using 25 representative SH3 domains and various PRPs derived from SOS1. Our analysis has identified 45 interacting pairs, with binding affinities ranging from 0.2 to 125 micromolar, out of 300 tested and potential new SH3 domain-SOS1 interactions. Furthermore, it establishes a framework to bridge the gap between SH3 and PRP interactions and provides predictive insights into the potential interactions of SH3 domains with PRMs based on sequence specifications. This novel framework has the potential to enhance the understanding of protein networks mediated by SH3 domain-PRM interactions and be utilized as a general approach for other domain-peptide interactions.

A Systematic Compilation of Human SH3 Domains: A Versatile Superfamily in Cellular Signaling

SRC homology 3 (SH3) domains are fundamental modules that enable the assembly of protein complexes through physical interactions with a pool of proline-rich/noncanonical motifs from partner proteins. They are widely studied modular building blocks across all five kingdoms of life and viruses, mediating various biological processes. The SH3 domains are also implicated in the development of human diseases, such as cancer, leukemia, osteoporosis, Alzheimer's disease, and various infections. A database search of the human proteome reveals the existence of 298 SH3 domains in 221 SH3 domain-containing proteins (SH3DCPs), ranging from 13 to 720 kilodaltons. A phylogenetic analysis of human SH3DCPs based on their multi-domain architecture seems to be the most practical way to classify them functionally, with regard to various physiological pathways. This review further summarizes the achievements made in the classification of SH3 domain functions, their binding specificity, and their significance for various diseases when exploiting SH3 protein modular interactions as drug targets.

Cloning and characterization of thermostable amylopullulanase TbbApu and its C-terminal truncated variants with enhanced activity in organic solvents

Bifunctional debranching-enzyme amylopullulanases belong to the glycoside hydrolases (GHs) family and catalyze both the hydrolysis of α-1,4 and α-1,6 glycosidic bonds in starch, pullulan, amylopectin and glycogen polysaccharides. Among these, especially thermostable ones are essential in starch processing applications. In this study, we focused to elucidate the complete sequence of the apu gene and the role of C-term domains on biochemical properties and enzyme activity of Thermoanaerobacter brockii brockii amylopullulanase (TbbApu). After the gene sequence was defined, C- term truncated variants were constructed. The most suitable host organism and expression vector were determined as E. coli BL21(DE3) and pET-28a(+) depending on the highest yield/biomass ratio for recombinant production of all constructs. It was seen that the expression yield increased approximately threefold in the case of the SH3 region truncation. In the biochemical characterization, TbbApu and its truncated variants exhibited maximum activity at 70 °C and 75 °C for pullulan and starch hydrolysis respectively, and the optimum pH of TbbApu were 6.5 and 6 for truncated variants. Moreover, hydrolysis activities of all recombinant enzymes were enhanced by Mn²⁺, Co²⁺ and Cu²⁺, detergents, and almost all organic solvents; except butanol, DMF and DMSO. All recombinant amylopullulanases remained 80% stable up to 80 °C in the wide range of pH and also retained > 85% stability in the presence of defined volatile organic solvents. No significant difference was observed between the raw starch adsorption capacity and the specific activity of the three variants. These results indicated that the C-terminal regions of TbbApu are non-essential for the enzyme activity, stability and substrate binding capacity; furthermore, hexane and acetone organic solvents enhanced both pullulanase and α-amylase activity of these enzymes, interestingly. With these features, TbbApu and its truncated variants are distinguished from other thermophilic amylopullulanases and also make them promising candidates for industrial use.

The decrease of selenoprotein K induced by selenium deficiency in diet improves apoptosis and cell progression block in chicken liver via the PTEN/PI3K/AKT pathway

Selenoprotein K (SELK) is imperative for normal development of chicken. It does regulate to chicken's physiological function. However, the injury of SELK-deficiency done on chicken liver and its underlying mechanism involved has not yet been covered. Therefore, we built SELK- deficiency model by feeding diet which contained low concentration of selenium (Se) to discuss SELK's regulation mechanism. Through using TUNEL, TEM, western blot and qRT-PCR we found apoptosis occurred in chicken liver in the SELK-deficiency groups. In the meanwhile, our study showed there were differentially expressed of the PTEN/PI3K/AKT pathway, calcium homeostasis, endoplasmic reticulum healthy and cell cycle progression in SELK-deficiency chicken liver tissues. In order to claim the regulation mechanism of SELK, we set SELK-knock down model in the LMH. The results in vitro were coincided with those in vivo. In the SELK-deficiency groups, the PTEN/PI3K/AKT pathway was activated and then induced ERS which eventually resulted in apoptosis in chicken liver. As the same time, the PTEN/PI3K/AKT pathway also regulated the combined effective of MDM2-p53, which leaned liver cells to G1/S blocking. Our findings support the potential of SELK in maintain the health of chicken liver, and indicate that adding proper amount of Se on the daily dietary may alleviate the deficiency of selenium.

Structure, Activity and Function of the PRMT2 Protein Arginine Methyltransferase

PRMT2 belongs to the protein arginine methyltransferase (PRMT) family, which catalyzes the arginine methylation of target proteins. As a type I enzyme, PRMT2 produces asymmetric dimethyl arginine and has been shown to have weak methyltransferase activity on histone substrates in vitro, suggesting that its authentic substrates have not yet been found. PRMT2 contains the canonical PRMT methylation core and a unique Src homology 3 domain. Studies have demonstrated its clear implication in many different cellular processes. PRMT2 acts as a coactivator of several nuclear hormone receptors and is known to interact with a multitude of splicing-related proteins. Furthermore, PRMT2 is aberrantly expressed in several cancer types, including breast cancer and glioblastoma. These reports highlight the crucial role played by PRMT2 and the need for a better characterization of its activity and cellular functions.

Nck adaptors at a glance

The non-catalytic region of tyrosine kinase (Nck) family of adaptors, consisting of Nck1 and Nck2, contributes to selectivity and specificity in the flow of cellular information by recruiting components of signaling networks. Known to play key roles in cytoskeletal remodeling, Nck adaptors modulate host cell-pathogen interactions, immune cell receptor activation, cell adhesion and motility, and intercellular junctions in kidney podocytes. Genetic inactivation of both members of the Nck family results in embryonic lethality; however, viability of mice lacking either one of these adaptors suggests partial functional redundancy. In this Cell Science at a Glance and the accompanying poster, we highlight the molecular organization and functions of the Nck family, focusing on key interactions and pathways, regulation of cellular processes, development, homeostasis and pathogenesis, as well as emerging and non-redundant functions of Nck1 compared to those of Nck2. This article thus aims to provide a timely perspective on the biology of Nck adaptors and their potential as therapeutic targets.

Protein Interaction Domains: Structural Features and Drug Discovery Applications (Part 2)

BACKGROUND

Proteins present a modular organization made up of several domains. Apart from the domains playing catalytic functions, many others are crucial to recruit interactors. The latter domains can be defined as "PIDs" (Protein Interaction Domains) and are responsible for pivotal outcomes in signal transduction and a certain array of normal physiological and disease-related pathways. Targeting such PIDs with small molecules and peptides able to modulate their interaction networks, may represent a valuable route to discover novel therapeutics.

OBJECTIVE

This work represents a continuation of a very recent review describing PIDs able to recognize post-translationally modified peptide segments. On the contrary, the second part concerns with PIDs that interact with simple peptide sequences provided with standard amino acids.

METHODS

Crucial structural information on different domain subfamilies and their interactomes was gained by a wide search in different online available databases (including the PDB (Protein Data Bank), the Pfam (Protein family), and the SMART (Simple Modular Architecture Research Tool)). Pubmed was also searched to explore the most recent literature related to the topic.

RESULTS AND CONCLUSION

PIDs are multifaceted: they have all diverse structural features and can recognize several consensus sequences. PIDs can be linked to different diseases onset and progression, like cancer or viral infections and find applications in the personalized medicine field. Many efforts have been centered on peptide/peptidomimetic inhibitors of PIDs mediated interactions but much more work needs to be conducted to improve drug-likeness and interaction affinities of identified compounds.

Large-scale survey and database of high affinity ligands for peptide recognition modules

Many proteins involved in signal transduction contain peptide recognition modules (PRMs) that recognize short linear motifs (SLiMs) within their interaction partners. Here, we used large-scale peptide-phage display methods to derive optimal ligands for 163 unique PRMs representing 79 distinct structural families. We combined the new data with previous data that we collected for the large SH3, PDZ, and WW domain families to assemble a database containing 7,984 unique peptide ligands for 500 PRMs representing 82 structural families. For 74 PRMs, we acquired enough new data to map the specificity profiles in detail and derived position weight matrices and binding specificity logos based on multiple peptide ligands. These analyses showed that optimal peptide ligands resembled peptides observed in existing structures of PRM-ligand complexes, indicating that a large majority of the phage-derived peptides are likely to target natural peptide-binding sites and could thus act as inhibitors of natural protein-protein interactions. The complete dataset has been assembled in an online database (http://www.prm-db.org) that will enable many structural, functional, and biological studies of PRMs and SLiMs.

New analysis pipeline for high-throughput domain-peptide affinity experiments improves SH2 interaction data

Protein domain interactions with short linear peptides, such as those of the Src homology 2 (SH2) domain with phosphotyrosine-containing peptide motifs (pTyr), are ubiquitous and important to many biochemical processes of the cell. The desire to map and quantify these interactions has resulted in the development of high-throughput (HTP) quantitative measurement techniques, such as microarray or fluorescence polarization assays. For example, in the last 15 years, experiments have progressed from measuring single interactions to covering 500,000 of the 5.5 million possible SH2-pTyr interactions in the human proteome. However, high variability in affinity measurements and disagreements about positive interactions between published data sets led us here to reevaluate the analysis methods and raw data of published SH2-pTyr HTP experiments. We identified several opportunities for improving the identification of positive and negative interactions and the accuracy of affinity measurements. We implemented model-fitting techniques that are more statistically appropriate for the nonlinear SH2-pTyr interaction data. We also developed a method to account for protein concentration errors due to impurities and degradation or protein inactivity and aggregation. Our revised analysis increases the reported affinity accuracy, reduces the false-negative rate, and increases the amount of useful data by adding reliable true-negative results. We demonstrate improvement in classification of binding versus nonbinding when using machine-learning techniques, suggesting improved coherence in the reanalyzed data sets. We present revised SH2-pTyr affinity results and propose a new analysis pipeline for future HTP measurements of domain-peptide interactions.

Splicing-accessible coding 3'UTRs control protein stability and interaction networks

BACKGROUND

3'-Untranslated regions (3'UTRs) play crucial roles in mRNA metabolism, such as by controlling mRNA stability, translation efficiency, and localization. Intriguingly, in some genes the 3'UTR is longer than their coding regions, pointing to additional, unknown functions. Here, we describe a protein-coding function of 3'UTRs upon frameshift-inducing alternative splicing in more than 10% of human and mouse protein-coding genes.

RESULTS

3'UTR-encoded amino acid sequences show an enrichment of PxxP motifs and lead to interactome rewiring. Furthermore, an elevated proline content increases protein disorder and reduces protein stability, thus allowing splicing-controlled regulation of protein half-life. This could also act as a surveillance mechanism for erroneous skipping of penultimate exons resulting in transcripts that escape nonsense mediated decay. The impact of frameshift-inducing alternative splicing on disease development is emphasized by a retinitis pigmentosa-causing mutation leading to translation of a 3'UTR-encoded, proline-rich, destabilized frameshift-protein with altered protein-protein interactions.

CONCLUSIONS

We describe a widespread, evolutionarily conserved mechanism that enriches the mammalian proteome, controls protein expression and protein-protein interactions, and has important implications for the discovery of novel, potentially disease-relevant protein variants.

Genome-wide identification of methylated CpG sites in nongenital cutaneous warts

BACKGROUND

Low-risk HPV infection has not been the subject of epigenetic investigation. The present study was carried out in order to investigate the methylation status of CpG sites in non-genital cutaneous warts.

METHODS

Genomic DNA was extracted from 24 paired epidermal samples of warts and normal skin. DNA samples were bisulfite converted and underwent genome-wide methylation profiling using the Infinium MethylationEPIC BeadChip Kit.

RESULTS

From a total of 844,234 CpG sites, 56,960 and 43,040 CpG sites were found to be hypo- and hypermethylated, respectively, in non-genital cutaneous warts. The most differentially methylated CpG sites in warts were located within the C10orf26, FAM83H-AS1, ZNF644, LINC00702, GSAP, STAT5A, HDAC4, NCALD, and EXOC4 genes.

CONCLUSION

Non-genital cutaneous warts exhibit a unique CpG methylation signature.

Molecular characterization, tissue distribution, and functional analysis of the STAC3 gene in chicken

The Src homology 3 and cysteine-rich domain 3 gene (STAC3) encodes a protein containing both a cysteine-rich domain and two Src (sarcoma) homology 3 domains (SH3). STAC3 is specifically expressed in skeletal muscle and plays an important role in skeletal muscle development, but the explicit sequence and function of chicken SATC3 remain unknown. In the current study, we found the full-length chicken STAC3 cDNA to be 1383 bp long, with a 1092 bp open reading frame that harbors one cysteine-rich C1 domain and two SH3 domains. Tissue distribution analysis reveals chicken STAC3 mRNA only in skeletal muscle among 12 chicken tissues examined by reverse transcription PCR. Both cholecystokinin octapeptide analysis and a 5-ethynyl-2'-deoxyuridine assay suggest that neither STAC3 overexpression nor knockdown has any effect on the proliferation of chicken skeletal muscle satellite cells. However, STAC3 knockdown significantly increases the mRNA expression of MyoG, MyoD, Mb, and MyHC, and the protein abundance of MyHC and MyoG, whereas the opposite result is found in STAC3 overexpressed cells. We conclude that the STAC3 gene is expressed specifically in skeletal muscle and is a negative regulator of skeletal muscle satellite cell differentiation in chicken.

A helical lock and key model of polyproline II conformation with SH3

Motivation

More than half of the human proteome contains the proline-rich motif, PxxP. This motif has a high propensity for adopting a left-handed polyproline II (PPII) helix and can potentially bind SH3 domains. SH3 domains are generally grouped into two classes, based on whether the PPII binds in a positive (N-to-C terminal) or negative (C-to-N terminal) orientation. Since the discovery of this structural motif, over six decades ago, a systematic understanding of its binding remains poor and the consensus amino acid sequence that binds SH3 domains is still ill defined.

Results

Here, we show that the PPII interaction with SH3 domains is governed by the helix backbone and its prolines, and their rotation angle around the PPII helical axis. Based on a geometric analysis of 131 experimentally solved SH3 domains in complex with PPIIs, we observed a rotary translation along the helical screw axis, and separated them by 120° into three categories we name α (0–120°), β (120–240°) and γ (240–360°). Furthermore, we found that PPII helices are distinguished by a shifting PxxP motif preceded by positively charged residues which act as a structural reading frame and dictates the organization of SH3 domains; however, there is no one single consensus motif for all classified PPIIs. Our results demonstrate a remarkable apparatus of a lock with a rotating and translating key with no known equivalent machinery in molecular biology. We anticipate our model to be a starting point for deciphering the PPII code, which can unlock an exponential growth in our understanding of the relationship between protein structure and function.

Availability and implementation

We have implemented the proposed methods in the R software environment and in an R package freely available at https://github.com/Grantlab/bio3d.

Supplementary information

Supplementary data are available at Bioinformatics online.

Identification of two distinct peptide-binding pockets in the SH3 domain of human mixed-lineage kinase 3

Mixed-lineage kinase 3 (MLK3; also known as MAP3K11) is a Ser/Thr protein kinase widely expressed in normal and cancerous tissues, including brain, lung, liver, heart, and skeletal muscle tissues. Its Src homology 3 (SH3) domain has been implicated in MLK3 autoinhibition and interactions with other proteins, including those from viruses. The MLK3 SH3 domain contains a six-amino-acid insert corresponding to the n-Src insert, suggesting that MLK3 may bind additional peptides. Here, affinity selection of a phage-displayed combinatorial peptide library for MLK3's SH3 domain yielded a 13-mer peptide, designated "MLK3 SH3-interacting peptide" (MIP). Unlike most SH3 domain peptide ligands, MIP contained a single proline. The 1.2-Å crystal structure of the MIP-bound SH3 domain revealed that the peptide adopts a β-hairpin shape, and comparison with a 1.5-Å apo SH3 domain structure disclosed that the n-Src loop in SH3 undergoes an MIP-induced conformational change. A 1.5-Å structure of the MLK3 SH3 domain bound to a canonical proline-rich peptide from hepatitis C virus nonstructural 5A (NS5A) protein revealed that it and MIP bind the SH3 domain at two distinct sites, but biophysical analyses suggested that the two peptides compete with each other for SH3 binding. Moreover, SH3 domains of MLK1 and MLK4, but not MLK2, also bound MIP, suggesting that the MLK1-4 family may be differentially regulated through their SH3 domains. In summary, we have identified two distinct peptide-binding sites in the SH3 domain of MLK3, providing critical insights into mechanisms of ligand binding by the MLK family of kinases.

Allosteric mechanisms underlie GPCR signaling to SH3-domain proteins through arrestin

Signals from 800 G-protein-coupled receptors (GPCRs) to many SH3 domain-containing proteins (SH3-CPs) regulate important physiological functions. These GPCRs may share a common pathway by signaling to SH3-CPs via agonist-dependent arrestin recruitment rather than through direct interactions. In the present study, ¹⁹F-NMR and cellular studies revealed that downstream of GPCR activation engagement of the receptor-phospho-tail with arrestin allosterically regulates the specific conformational states and functional outcomes of remote β-arrestin 1 proline regions (PRs). The observed NMR chemical shifts of arrestin PRs were consistent with the intrinsic efficacy and specificity of SH3 domain recruitment, which was controlled by defined propagation pathways. Moreover, in vitro reconstitution experiments and biophysical results showed that the receptor-arrestin complex promoted SRC kinase activity through an allosteric mechanism. Thus, allosteric regulation of the conformational states of β-arrestin 1 PRs by GPCRs and the allosteric activation of downstream effectors by arrestin are two important mechanisms underlying GPCR-to-SH3-CP signaling.

First-in-class inhibitor of the T cell receptor for the treatment of autoimmune diseases

Modulating T cell activation is critical for treating autoimmune diseases but requires avoiding concomitant opportunistic infections. Antigen binding to the T cell receptor (TCR) triggers the recruitment of the cytosolic adaptor protein Nck to a proline-rich sequence in the cytoplasmic tail of the TCR's CD3ε subunit. Through virtual screening and using combinatorial chemistry, we have generated an orally available, low-molecular weight inhibitor of the TCR-Nck interaction that selectively inhibits TCR-triggered T cell activation with an IC₅₀ (median inhibitory concentration) ~1 nM. By modulating TCR signaling, the inhibitor prevented the development of psoriasis and asthma and, furthermore, exerted a long-lasting therapeutic effect in a model of autoimmune encephalomyelitis. However, it did not prevent the generation of a protective memory response against a mouse pathogen, suggesting that the compound might not exert its effects through immunosuppression. These results suggest that inhibiting an immediate TCR signal has promise for treating a broad spectrum of human T cell-mediated autoimmune and inflammatory diseases.

The MIntAct Project and Molecular Interaction Databases

Molecular interaction databases collect, organize, and enable the analysis of the increasing amounts of molecular interaction data being produced and published as we move towards a more complete understanding of the interactomes of key model organisms. The organization of these data in a structured format supports analyses such as the modeling of pairwise relationships between interactors into interaction networks and is a powerful tool for understanding the complex molecular machinery of the cell. This chapter gives an overview of the principal molecular interaction databases, in particular the IMEx databases, and their curation policies, use of standardized data formats and quality control rules. Special attention is given to the MIntAct project, in which IntAct and MINT joined forces to create a single resource to improve curation and software development efforts. This is exemplified as a model for the future of molecular interaction data collation and dissemination.

Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases

Reversible tyrosine phosphorylation is a widespread post-translational modification mechanism underlying cell physiology. Thus, understanding the mechanisms responsible for substrate selection by kinases and phosphatases is central to our ability to model signal transduction at a system level. Classical protein-tyrosine phosphatases can exhibit substrate specificity in vivo by combining intrinsic enzymatic specificity with the network of protein-protein interactions, which positions the enzymes in close proximity to their substrates. Here we use a high throughput approach, based on high density phosphopeptide chips, to determine the in vitro substrate preference of 16 members of the protein-tyrosine phosphatase family. This approach helped identify one residue in the substrate binding pocket of the phosphatase domain that confers specificity for phosphopeptides in a specific sequence context. We also present a Bayesian model that combines intrinsic enzymatic specificity and interaction information in the context of the human protein interaction network to infer new phosphatase substrates at the proteome level.

Large-Scale Screening of Preferred Interactions of Human Src Homology-3 (SH3) Domains Using Native Target Proteins as Affinity Ligands

The Src Homology-3 (SH3) domains are ubiquitous protein modules that mediate important intracellular protein interactions via binding to short proline-rich consensus motifs in their target proteins. The affinity and specificity of such core SH3 - ligand contacts are typically modest, but additional binding interfaces can give rise to stronger and more specific SH3-mediated interactions. To understand how commonly such robust SH3 interactions occur in the human protein interactome, and to identify these in an unbiased manner we have expressed 324 predicted human SH3 ligands as full-length proteins in mammalian cells, and screened for their preferred SH3 partners using a phage display-based approach. This discovery platform contains an essentially complete repertoire of the ∼300 human SH3 domains, and involves an inherent binding threshold that ensures selective identification of only SH3 interactions with relatively high affinity. Such strong and selective SH3 partners could be identified for only 19 of these 324 predicted ligand proteins, suggesting that the majority of human SH3 interactions are relatively weak, and thereby have capacity for only modest inherent selectivity. The panel of exceptionally robust SH3 interactions identified here provides a rich source of leads and hypotheses for further studies. However, a truly comprehensive characterization of the human SH3 interactome will require novel high-throughput methods based on function instead of absolute binding affinity.

A single PXXP motif in the C-terminal region of srGAP3 mediates binding to multiple SH3 domains

The Slit-Robo GTPase-activating protein 3 (srGAP3) has been implicated in different critical aspects of neuronal development. These findings have mainly been based on the characterisation of the three conserved globular N-terminal domains, while the function of the C-terminal region (CTR) is still unknown. We show that this predicted unstructured region acts as an adaptor by binding to the endocytic proteins Amphiphysin, Endophilin-A2, Endophilin-A1, as well as the Ras signalling protein Grb2. All these interactions depend on a single proline-rich motif in the CTR and the Src-homology 3 domains of the binding partners. Via these interactions srGAP3 could link receptor signalling events to the endocytic machinery.

The adapter protein CD2AP binds to p53 protein in the cytoplasm and can discriminate its polymorphic variants P72R

Proline-rich motifs are widely distributed in eukaryotic proteomes and are usually involved in the assembly of functional complexes through interaction with specific binding modules. The tumour-suppressor p53 protein presents a proline-rich region that is crucial for regulating apoptosis by connecting the p53 with a complex protein network. In humans, a common polymorphism determines the identity of residue 72, either proline or arginine, and affects the features of the motifs present in the polyproline domain. The two isoforms have different biochemical properties and markedly influence cancer onset and progression. In this article, we analyse the binding of the p53 proline-rich region with a pool of selected polyproline binding domains (i.e. SH3 and WW), and we present the first demonstration that the purified SH3 domains of the CD2AP/Cin85 protein family are able to directly bind the p53 protein, and to discriminate between the two polymorphic variants P72R.

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.

MoDPepInt: an interactive web server for prediction of modular domain-peptide interactions

Summary: MoDPepInt (Modular Domain Peptide Interaction) is a new easy-to-use web server for the prediction of binding partners for modular protein domains. Currently, we offer models for SH2, SH3 and PDZ domains via the tools SH2PepInt, SH3PepInt and PDZPepInt, respectively. More specifically, our server offers predictions for 51 SH2 human domains and 69 SH3 human domains via single domain models, and predictions for 226 PDZ domains across several species, via 43 multidomain models. All models are based on support vector machines with different kernel functions ranging from polynomial, to Gaussian, to advanced graph kernels. In this way, we model non-linear interactions between amino acid residues. Results were validated on manually curated datasets achieving competitive performance against various state-of-the-art approaches.

Availability and implementation: The MoDPepInt server is available under the URL http://modpepint.informatik.uni-freiburg.de/

Contact: backofen@informatik.uni-freiburg.de

Supplementary information: Supplementary data are available at Bioinformatics online.

Combining affinity proteomics and network context to identify new phosphatase substrates and adapters in growth pathways

Protein phosphorylation homoeostasis is tightly controlled and pathological conditions are caused by subtle alterations of the cell phosphorylation profile. Altered levels of kinase activities have already been associated to specific diseases. Less is known about the impact of phosphatases, the enzymes that down-regulate phosphorylation by removing the phosphate groups. This is partly due to our poor understanding of the phosphatase-substrate network. Much of phosphatase substrate specificity is not based on intrinsic enzyme specificity with the catalytic pocket recognizing the sequence/structure context of the phosphorylated residue. In addition many phosphatase catalytic subunits do not form a stable complex with their substrates. This makes the inference and validation of phosphatase substrates a non-trivial task. Here, we present a novel approach that builds on the observation that much of phosphatase substrate selection is based on the network of physical interactions linking the phosphatase to the substrate. We first used affinity proteomics coupled to quantitative mass spectrometry to saturate the interactome of eight phosphatases whose down regulations was shown to affect the activation of the RAS-PI3K pathway. By integrating information from functional siRNA with protein interaction information, we develop a strategy that aims at inferring phosphatase physiological substrates. Graph analysis is used to identify protein scaffolds that may link the catalytic subunits to their substrates. By this approach we rediscover several previously described phosphatase substrate interactions and characterize two new protein scaffolds that promote the dephosphorylation of PTPN11 and ERK by DUSP18 and DUSP26, respectively.

Crk adaptors negatively regulate actin polymerization in pedestals formed by enteropathogenic Escherichia coli (EPEC) by binding to Tir effector

Infections by enteropathogenic Escherichia coli (EPEC) cause diarrhea linked to high infant mortality in developing countries. EPEC adheres to epithelial cells and induces the formation of actin pedestals. Actin polymerization is driven fundamentally through signaling mediated by Tir bacterial effector protein, which inserts in the plasma membrane of the infected cell. Tir binds Nck adaptor proteins, which in turn recruit and activate N-WASP, a ubiquitous member of the Wiskott-Aldrich syndrome family of proteins. N-WASP activates the Arp2/3 complex to promote actin polymerization. Other proteins aside from components of the Tir-Nck-N-WASP pathway are recruited to the pedestals but their functions are unknown. Here we investigate the function of two alternatively spliced isoforms of Crk adaptors (CrkI/II) and the paralog protein CrkL during pedestal formation by EPEC. We found that the Crk isoforms act as redundant inhibitors of pedestal formation. The SH2 domain of CrkII and CrkL binds to phosphorylated tyrosine 474 of Tir and competes with Nck to bind Tir, preventing its recruitment to pedestals and thereby inhibiting actin polymerization. EPEC infection induces phosphorylation of the major regulatory tyrosine in CrkII and CrkL, possibly preventing the SH2 domain of these proteins from interacting with Tir. Phosphorylated CrkII and CrkL proteins localize specifically to the plasma membrane in contact with EPEC. Our study uncovers a novel role for Crk adaptors at pedestals, opening a new perspective in how these oncoproteins regulate actin polymerization.

The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases

IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org).

A graph kernel approach for alignment-free domain-peptide interaction prediction with an application to human SH3 domains

MOTIVATION

State-of-the-art experimental data for determining binding specificities of peptide recognition modules (PRMs) is obtained by high-throughput approaches like peptide arrays. Most prediction tools applicable to this kind of data are based on an initial multiple alignment of the peptide ligands. Building an initial alignment can be error-prone, especially in the case of the proline-rich peptides bound by the SH3 domains.

RESULTS

Here, we present a machine-learning approach based on an efficient graph-kernel technique to predict the specificity of a large set of 70 human SH3 domains, which are an important class of PRMs. The graph-kernel strategy allows us to (i) integrate several types of physico-chemical information for each amino acid, (ii) consider high-order correlations between these features and (iii) eliminate the need for an initial peptide alignment. We build specialized models for each human SH3 domain and achieve competitive predictive performance of 0.73 area under precision-recall curve, compared with 0.27 area under precision-recall curve for state-of-the-art methods based on position weight matrices. We show that better models can be obtained when we use information on the noninteracting peptides (negative examples), which is currently not used by the state-of-the art approaches based on position weight matrices. To this end, we analyze two strategies to identify subsets of high confidence negative data. The techniques introduced here are more general and hence can also be used for any other protein domains, which interact with short peptides (i.e. other PRMs).

AVAILABILITY

The program with the predictive models can be found at http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/SH3PepInt.tar.gz. We also provide a genome-wide prediction for all 70 human SH3 domains, which can be found under http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/Genome-Wide-Predictions.tar.gz.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploring the diversity of SPRY/B30.2-mediated interactions

The SPla/Ryanodine receptor (SPRY)/B30.2 domain is one of the most common folds in higher eukaryotes. The human genome encodes 103 SPRY/B30.2 domains, several of which are involved in the immune response. Approximately 45% of human SPRY/B30.2-containing proteins are E3 ligases. The role and function of the majority of SPRY/B30.2 domains are still poorly understood, however, in several cases mutations in this domain have been linked to congenital disorders. The recent characterization of SPRY/B30.2-mediated protein interactions has provided evidence for a role of this domain as an adaptor module to assemble macromolecular complexes, analogous to Src homology (SH)2, SH3, and WW domains. However, functional and structural evidence suggests that SPRY/B30.2 is a more versatile fold, allowing a wide range of binding modes.

Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach

MOTIVATION

Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and/or the motifs are found at different locations within distinct peptides.

RESULTS

The algorithm presented in this article, based on Gibbs sampling, identifies multiple specificities in peptide data by performing two essential tasks simultaneously: alignment and clustering of peptide data. We apply the method to de-convolute binding motifs in a panel of peptide datasets with different degrees of complexity spanning from the simplest case of pre-aligned fixed-length peptides to cases of unaligned peptide datasets of variable length. Example applications described in this article include mixtures of binders to different MHC class I and class II alleles, distinct classes of ligands for SH3 domains and sub-specificities of the HLA-A*02:01 molecule.

AVAILABILITY

The Gibbs clustering method is available online as a web server at http://www.cbs.dtu.dk/services/GibbsCluster.

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.

Charting the landscape of tandem BRCT domain-mediated protein interactions

Eukaryotic cells have evolved an intricate system to resolve DNA damage to prevent its transmission to daughter cells. This system, collectively known as the DNA damage response (DDR) network, includes many proteins that detect DNA damage, promote repair, and coordinate progression through the cell cycle. Because defects in this network can lead to cancer, this network constitutes a barrier against tumorigenesis. The modular BRCA1 carboxyl-terminal (BRCT) domain is frequently present in proteins involved in the DDR, can exist either as an individual domain or as tandem domains (tBRCT), and can bind phosphorylated peptides. We performed a systematic analysis of protein-protein interactions involving tBRCT in the DDR by combining literature curation, yeast two-hybrid screens, and tandem affinity purification coupled to mass spectrometry. We identified 23 proteins containing conserved BRCT domains and generated a human protein-protein interaction network for seven proteins with tBRCT. This study also revealed previously unknown components in DNA damage signaling, such as COMMD1 and the target of rapamycin complex mTORC2. Additionally, integration of tBRCT domain interactions with DDR phosphoprotein studies and analysis of kinase-substrate interactions revealed signaling subnetworks that may aid in understanding the involvement of tBRCT in disease and DNA repair.

Expression and purification of the membrane enzyme selenoprotein K

Selenoprotein K (SelK) is a membrane protein residing in the endoplasmic reticulum. The function of SelK is mostly unknown; however, it has been shown to participate in anti-oxidant defense, calcium regulation and in the endoplasmic reticulum associated protein degradation (ERAD) pathway. In order to study the function of SelK and the role of selenocysteine in catalysis, we have tested heterologous expression of human SelK in E. coli. Consequently, we have developed an over-expression strategy that exploits the maltose binding protein as a fusion partner to stabilize and solubilize SelK. The fusion partner can be cleaved from SelK in the presence of a variety of detergents compatible with structural characterization and the protein purified to homogeneity. SelK acquires a helical secondary structure in detergent micelles, even though it was predicted to be an intrinsically disordered protein due to its high percentage of polar residues. The same strategy was successfully applied to preparation of SelK binding partner - selenoprotein S (SelS). Hence, this heterologous expression and purification strategy can be applied to other members of the membrane enzyme family to which SelK belongs.

Elucidation of the binding preferences of peptide recognition modules: SH3 and PDZ domains

Peptide-binding domains play a critical role in regulation of cellular processes by mediating protein interactions involved in signalling. In recent years, the development of large-scale technologies has enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. These efforts have provided significant insights into the binding specificities of these modular domains. Many research groups have taken advantage of this unprecedented volume of specificity data and have developed a variety of new algorithms for the prediction of binding specificities of peptide-binding domains and for the prediction of their natural binding targets. This knowledge has also been applied to the design of synthetic peptide-binding domains in order to rewire protein-protein interaction networks. Here, we describe how these experimental technologies have impacted on our understanding of peptide-binding domain specificities and on the elucidation of their natural ligands. We discuss SH3 and PDZ domains as well characterized examples, and we explore the feasibility of expanding high-throughput experiments to other peptide-binding domains.

Synthetic peptide arrays for investigating protein interaction domains

Synthetic peptide array technology was first developed in the early 1990s by Ronald Frank. Since then the technique has become a powerful tool for high throughput approaches in biology and biochemistry. Here, we focus on peptide arrays applied to investigate the binding specificity of protein interaction domains such as WW, SH3, and PDZ domains. We describe array-based methods used to reveal domain networks in yeast, and briefly review rules as well as ideas about the synthesis and application of peptide arrays. We also provide initial results of a study designed to investigate the nature and evolution of SH3 domain interaction networks in eukaryotes.

The application of modular protein domains in proteomics

The ability of modular protein domains to independently fold and bind short peptide ligands both in vivo and in vitro has allowed a significant number of protein-protein interaction studies to take advantage of them as affinity and detection reagents. Here, we refer to modular domain based proteomics as "domainomics" to draw attention to the potential of using domains and their motifs as tools in proteomics. In this review we describe core concepts of domainomics, established and emerging technologies, and recent studies by functional category. Accumulation of domain-motif binding data should ultimately provide the foundation for domain-specific interactomes, which will likely reveal the underlying substructure of protein networks as well as the selectivity and plasticity of signal transduction.