Cluster based prediction of PDZ-peptide interactions

The cell polarity protein Scribble is downregulated by the water channel aquaporin-5 in breast cancer cells

Breast carcinomas originate from cells in the terminal duct-lobular unit. Carcinomas are associated with increased cell proliferation and migration, altered cellular adhesion, as well as loss of epithelial polarity. In breast cancer, aberrant and high levels of aquaporin-5 (AQP5) are associated with increased metastasis, poor prognosis, and cancer recurrence. AQP5 increases the proliferation and migration of cancer cells, and ectopic expression of AQP5 in normal epithelial cells reduces cell-cell adhesion and increases cell detachment and dissemination from migrating cell sheets, the latter via AQP5-mediated activation of the Ras pathway. Here, we investigated if AQP5 also affects cellular polarity by examining the relationship between the essential polarity protein Scribble and AQP5. In tissue samples from invasive lobular and ductal carcinomas, the majority of cells with high AQP5 expression displayed low Scribble levels, indicating an inverse relationship. Probing for interactions via a Glutathione S-transferase pull-down experiment revealed that AQP5 and Scribble interacted. Moreover, overexpression of AQP5 in the breast cancer cell line MCF7 reduced both size and circularity of three-dimensional (3-D) spheroids and induced cell detachment and dissemination from migrating cell sheets. In addition, Scribble levels were reduced. An AQP5 mutant cell line, which cannot activate Ras (AQP5^S156A) signaling, displayed unchanged spheroid size and circularity and an intermediate level of Scribble, indicating that the effect of AQP5 on Scribble is, at least in part, dependent on AQP5-mediated activation of Ras. Thus, our results suggest that high AQP5 expression negatively regulates the essential polarity protein Scribble and thus, can affect cellular polarity in breast cancer.

The order of PDZ3 and TrpCage in fusion chimeras determines their properties-a biophysical characterization

Most of the structural proteins known today are composed of domains that carry their own functions while keeping their structural properties. It is supposed that such domains, when taken out of the context of the whole protein, can retain their original structure and function to a certain extent. Information on the specific functional and structural characteristics of individual domains in a new context of artificial fusion proteins may help to reveal the rules of internal and external domain communication. Moreover, this could also help explain the mechanism of such communication and address how the mutual allosteric effect plays a role in a such multi-domain protein system. The simple model system of the two-domain fusion protein investigated in this work consisted of a well-folded PDZ3 domain and an artificially designed small protein domain called Tryptophan Cage (TrpCage). Two fusion proteins with swapped domain order were designed to study their structural and functional features as well as their biophysical properties. The proteins composed of PDZ3 and TrpCage, both identical in amino acid sequence but different in composition (PDZ3-TrpCage, TrpCage-PDZ3), were studied using circualr dichroism (CD) spectrometry, analytical ultracentrifugation, and molecular dynamic simulations. The biophysical analysis uncovered different structural and denaturation properties of both studied proteins, revealing their different unfolding pathways and dynamics.

Gpr63 is a modifier of microcephaly in Ttc21b mouse mutants

The primary cilium is a signaling center critical for proper embryonic development. Previous studies have demonstrated that mice lacking Ttc21b have impaired retrograde trafficking within the cilium and multiple organogenesis phenotypes, including microcephaly. Interestingly, the severity of the microcephaly in Ttc21b^aln/aln homozygous null mutants is considerably affected by the genetic background and mutants on an FVB/NJ (FVB) background develop a forebrain significantly smaller than mutants on a C57BL/6J (B6) background. We performed a Quantitative Trait Locus (QTL) analysis to identify potential genetic modifiers and identified two regions linked to differential forebrain size: modifier of alien QTL1 (Moaq1) on chromosome 4 at 27.8 Mb and Moaq2 on chromosome 6 at 93.6 Mb. These QTLs were validated by constructing congenic strains. Further analysis of Moaq1 identified an orphan G-protein coupled receptor (GPCR), Gpr63, as a candidate gene. We identified a SNP that is polymorphic between the FVB and B6 strains in Gpr63 and creates a missense mutation predicted to be deleterious in the FVB protein. We used CRISPR-Cas9 genome editing to create two lines of FVB congenic mice: one with the B6 sequence of Gpr63 and the other with a deletion allele leading to a truncation of the GPR63 C-terminal tail. We then demonstrated that Gpr63 can localize to the cilium in vitro. These alleles affect ciliary localization of GPR63 in vitro and genetically interact with Ttc21b^aln/aln as Gpr63;Ttc21b double mutants show unique phenotypes including spina bifida aperta and earlier embryonic lethality. This validated Gpr63 as a modifier of multiple Ttc21b neural phenotypes and strongly supports Gpr63 as a causal gene (i.e., a quantitative trait gene, QTG) within the Moaq1 QTL.

TTC21B in humans is a known ciliopathy gene and contributes to the pathophysiology of a number of ciliopathies. Mice homozygous for a null allele of Ttc21b also have a spectrum of ciliopathy phenotypes, including microcephaly (small brain). Further work has shown that the severity of the microcephaly significantly depends on the genetic background of the mouse model. The genetic mechanisms of the Ttc21b pathophysiology and the interacting gene network remain far from understood. As an initial attempt to understand the underlying mechanism(s) underlying the variable effects on brain size, we performed a quantitative trait locus (QTL) analysis and found two regions of genomic significance that correlated with smaller brain size. We confirmed both QTLs with congenic lines. One of the two regions was small enough that we considered candidate genes and hypothesized Gpr63 might be a contributing locus for a number of reasons. We evaluated this hypothesis directly with precise variant creation using genome editing and provide evidence that Ttc21b and Gpr63 do indeed genetically interact. Thus, we have been able to combine classical QTL analysis and genome editing to directly test the resulting hypothesis.

MotifAnalyzer-PDZ: A computational program to investigate the evolution of PDZ-binding target specificity

Recognition of short linear motifs (SLiMs) or peptides by proteins is an important component of many cellular processes. However, due to limited and degenerate binding motifs, prediction of cellular targets is challenging. In addition, many of these interactions are transient and of relatively low affinity. Here, we focus on one of the largest families of SLiM-binding domains in the human proteome, the PDZ domain. These domains bind the extreme C-terminus of target proteins, and are involved in many signaling and trafficking pathways. To predict endogenous targets of PDZ domains, we developed MotifAnalyzer-PDZ, a program that filters and compares all motif-satisfying sequences in any publicly available proteome. This approach enables us to determine possible PDZ binding targets in humans and other organisms. Using this program, we predicted and biochemically tested novel human PDZ targets by looking for strong sequence conservation in evolution. We also identified three C-terminal sequences in choanoflagellates that bind a choanoflagellate PDZ domain, the Monsiga brevicollis SHANK1 PDZ domain (mbSHANK1), with endogenously-relevant affinities, despite a lack of conservation with the targets of a homologous human PDZ domain, SHANK1. All three are predicted to be signaling proteins, with strong sequence homology to cytosolic and receptor tyrosine kinases. Finally, we analyzed and compared the positional amino acid enrichments in PDZ motif-satisfying sequences from over a dozen organisms. Overall, MotifAnalyzer-PDZ is a versatile program to investigate potential PDZ interactions. This proof-of-concept work is poised to enable similar types of analyses for other SLiM-binding domains (e.g., MotifAnalyzer-Kinase). MotifAnalyzer-PDZ is available at http://motifAnalyzerPDZ.cs.wwu.edu.

Functional and structural analysis of rare SLC2A2 variants associated with Fanconi-Bickel syndrome and metabolic traits

Deleterious variants in SLC2A2 cause Fanconi-Bickel Syndrome (FBS), a glycogen storage disorder, whereas less common variants in SLC2A2 associate with numerous metabolic diseases. Phenotypic heterogeneity in FBS has been observed, but its causes remain unknown. Our goal was to functionally characterize rare SLC2A2 variants found in FBS and metabolic disease-associated variants to understand the impact of these variants on GLUT2 activity and expression and establish genotype-phenotype correlations. Complementary RNA-injected Xenopus laevis oocytes were used to study mutant transporter activity and membrane expression. GLUT2 homology models were constructed for mutation analysis using GLUT1, GLUT3, and XylE as templates. Seventeen FBS variants were characterized. Only c.457_462delCTTATA (p.Leu153_Ile154del) exhibited residual glucose uptake. Functional characterization revealed that only half of the variants were expressed on the plasma membrane. Most less common variants (except c.593 C>A (p.Thr198Lys) and c.1087 G>T (p.Ala363Ser)) exhibited similar GLUT2 transport activity as the wild type. Structural analysis of GLUT2 revealed that variants affect substrate-binding, steric hindrance, or overall transporter structure. The mutant transporter that is associated with a milder FBS phenotype, p.Leu153_Ile154del, retained transport activity. These results improve our overall understanding of the underlying causes of FBS and impact of GLUT2 function on various clinical phenotypes ranging from rare to common disease.

Magi-1 scaffolds NaV1.8 and Slack KNa channels in dorsal root ganglion neurons regulating excitability and pain

Voltage-dependent sodium (Na_V) 1.8 channels regulate action potential generation in nociceptive neurons, identifying them as putative analgesic targets. Here, we show that Na_V1.8 channel plasma membrane localization, retention, and stability occur through a direct interaction with the postsynaptic density-95/discs large/zonula occludens-1-and WW domain-containing scaffold protein called membrane-associated guanylate kinase with inverted orientation (Magi)-1. The neurophysiological roles of Magi-1 are largely unknown, but we found that dorsal root ganglion (DRG)-specific knockdown of Magi-1 attenuated thermal nociception and acute inflammatory pain and produced deficits in Na_V1.8 protein expression. A competing cell-penetrating peptide mimetic derived from the Na_V1.8 WW binding motif decreased sodium currents, reduced Na_V1.8 protein expression, and produced hypoexcitability. Remarkably, a phosphorylated variant of the very same peptide caused an opposing increase in Na_V1.8 surface expression and repetitive firing. Likewise, in vivo, the peptides produced diverging effects on nocifensive behavior. Additionally, we found that Magi-1 bound to sequence like a calcium-activated potassium channel sodium-activated (Slack) potassium channels, demonstrating macrocomplexing with Na_V1.8 channels. Taken together, these findings emphasize Magi-1 as an essential scaffold for ion transport in DRG neurons and a central player in pain.-Pryce, K. D., Powell, R., Agwa, D., Evely, K. M., Sheehan, G. D., Nip, A., Tomasello, D. L., Gururaj, S., Bhattacharjee, A. Magi-1 scaffolds Na_V1.8 and Slack K_Na channels in dorsal root ganglion neurons regulating excitability and pain.

LMDIPred: A web-server for prediction of linear peptide sequences binding to SH3, WW and PDZ domains

Protein-peptide interactions form an important subset of the total protein interaction network in the cell and play key roles in signaling and regulatory networks, and in major biological processes like cellular localization, protein degradation, and immune response. In this work, we have described the LMDIPred web server, an online resource for generalized prediction of linear peptide sequences that may bind to three most prevalent and well-studied peptide recognition modules (PRMs)—SH3, WW and PDZ. We have developed support vector machine (SVM)-based prediction models that achieved maximum Matthews Correlation Coefficient (MCC) of 0.85 with an accuracy of 94.55% for SH3, MCC of 0.90 with an accuracy of 95.82% for WW, and MCC of 0.83 with an accuracy of 92.29% for PDZ binding peptides. LMDIPred output combines predictions from these SVM models with predictions using Position-Specific Scoring Matrices (PSSMs) and string-matching methods using known domain-binding motif instances and regular expressions. All of these methods were evaluated using a five-fold cross-validation technique on both balanced and unbalanced datasets, and also validated on independent datasets. LMDIPred aims to provide a preliminary bioinformatics platform for sequence-based prediction of probable binding sites for SH3, WW or PDZ domains.

Freiburg RNA tools: a central online resource for RNA-focused research and teaching

The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.

Molecular characterization and expression analysis of four fish-specific CC chemokine receptors CCR4La, CCR4Lc1, CCR4Lc2 and CCR11 in rainbow trout (Oncorhynchus mykiss)

The chemokine and chemokine receptor networks regulate leukocyte trafficking, inflammation, immune cell differentiation, cancer and other biological processes. Comparative immunological studies have revealed that both chemokines and their receptors have expanded greatly in a species/lineage specific way. Of the 10 human CC chemokine receptors (CCR1-10) that bind CC chemokines, orthologues only to CCR6, 7, 9 and 10 are present in teleost fish. In this study, four fish-specific CCRs, termed as CCR4La, CCR4Lc1, CCR4Lc2 and CCR11, with a close link to human CCR1-5 and 8, in terms of amino acid homology and syntenic conservation, have been identified and characterized in rainbow trout (Oncorhynchus mykiss). These CCRs were found to possess the conserved features of the G protein-linked receptor family, including an extracellular N-terminal, seven TM domains, three extracellular loops and three intracellular loops, and a cytoplasmic carboxyl tail with multiple potential serine/threonine phosphorylation sites. Four cysteine residues known to be involved in forming two disulfide bonds are present in the extracellular domains and a DRY motif is present in the second intracellular loop. Signaling mediated by these receptors might be regulated by N-glycosylation, tyrosine sulfation, S-palmitoylation, a PDZ ligand motif and di-leucine motifs. Studies of intron/exon structure revealed distinct fish-specific CCR gene organization in different fish species/lineages that might contribute to the diversification of the chemokine ligand-receptor networks in different fish lineages. Fish-specific trout CCRs are highly expressed in immune tissues/organs, such as thymus, spleen, head kidney and gills. Their expression can be induced by the pro-inflammatory cytokines, IL-1β, IL-6 and IFNγ, by the pathogen associated molecular patterns, PolyIC and peptidoglycan, and by bacterial infection. These data suggest that fish-specific CCRs are likely to have an important role in immune regulation in fish.

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

modPDZpep: a web resource for structure based analysis of human PDZ-mediated interaction networks

Background

PDZ domains recognize short sequence stretches usually present in C-terminal of their interaction partners. Because of the involvement of PDZ domains in many important biological processes, several attempts have been made for developing bioinformatics tools for genome-wide identification of PDZ interaction networks. Currently available tools for prediction of interaction partners of PDZ domains utilize machine learning approach. Since, they have been trained using experimental substrate specificity data for specific PDZ families, their applicability is limited to PDZ families closely related to the training set. These tools also do not allow analysis of PDZ-peptide interaction interfaces.

Results

We have used a structure based approach to develop modPDZpep, a program to predict the interaction partners of human PDZ domains and analyze structural details of PDZ interaction interfaces. modPDZpep predicts interaction partners by using structural models of PDZ-peptide complexes and evaluating binding energy scores using residue based statistical pair potentials. Since, it does not require training using experimental data on peptide binding affinity, it can predict substrates for diverse PDZ families. Because of the use of simple scoring function for binding energy, it is also fast enough for genome scale structure based analysis of PDZ interaction networks. Benchmarking using artificial as well as real negative datasets indicates good predictive power with ROC-AUC values in the range of 0.7 to 0.9 for a large number of human PDZ domains. Another novel feature of modPDZpep is its ability to map novel PDZ mediated interactions in human protein-protein interaction networks, either by utilizing available experimental phage display data or by structure based predictions.

Conclusions

In summary, we have developed modPDZpep, a web-server for structure based analysis of human PDZ domains. It is freely available at http://www.nii.ac.in/modPDZpep.html or http://202.54.226.235/modPDZpep.html.

Reviewers

This article was reviewed by Michael Gromiha and Zoltán Gáspári.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-016-0151-4) contains supplementary material, which is available to authorized users.

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.