Protein Interaction Sites Research Articles

Recognition of sites of functional specialisation in all known eukaryotic protein kinase families.

The conserved function of protein phosphorylation, catalysed by members of protein kinase superfamily, is regulated in different ways in different kinase families. Further, differences in activating triggers, cellular localisation, domain architecture and substrate specificity between kinase families are also well known. While the transfer of γ-phosphate from ATP to the hydroxyl group of Ser/Thr/Tyr is mediated by a conserved Asp, the characteristic functional and regulatory sites are specialized at the level of families or sub-families. Such family-specific sites of functional specialization are unknown for most families of kinases. In this work, we systematically identify the family-specific residue features by comparing the extent of conservation of physicochemical properties, Shannon entropy and statistical probability of residue distributions between families of kinases. An integrated discriminatory score, which combines these three features, is developed to demarcate the functionally specialized sites in a kinase family from other sites. We achieved an area under ROC curve of 0.992 for the discrimination of kinase families. Our approach was extensively tested on well-studied families CDK and MAPK, wherein specific protein interaction sites and substrate recognition sites were successfully detected (p-value < 0.05). We also find that the known family-specific oncogenic driver mutation sites were scored high by our method. The method was applied to all known kinases encompassing 107 families from diverse eukaryotic organisms leading to a comprehensive list of family-specific functional sites. Apart from other uses, our method facilitates identification of specific protein interaction sites and drug target sites in a kinase family.

Using NMR Chemical Shifts to Determine Residue-Specific Secondary Structure Populations for Intrinsically Disordered Proteins.

Protein disorder is a pervasive phenomenon in biology and a natural consequence of polymer evolution that facilitates cell signaling by organizing sites for posttranslational modifications and protein-protein interactions into arrays of short linear motifs that can be rearranged by RNA splicing. Disordered proteins are missing the long-range nonpolar interactions that form tertiary structures, but they often contain regions with residual secondary structure that are stabilized by protein binding. NMR spectroscopy is uniquely suited to detect residual secondary structure in a disordered protein and it can provide atomic resolution data on the structure and dynamics of disordered protein interaction sites. Here we describe how backbone chemical shifts are used for assigning residual secondary structure in disordered proteins and discuss some of the tools available for estimating secondary structure populations with a focus on disordered proteins containing different levels of alpha helical secondary structure which are stabilized by protein binding.

Angiotensin II-induced preeclampsia mouse model using osmotic infusion pump

Atypical Fat cadherins represent a small but versatile group of signaling molecules that influence proliferation and tissue polarity. With huge extracellular domains and intracellular domains harboring many independent protein interaction sites, Fat cadherins are poised to translate local cell adhesion events into a variety of cell behaviors. The need for such global coordination is particularly prominent in the nervous system, where millions of morphologically diverse neurons are organized into functional networks. As we learn more about their biological functions and molecular properties, increasing evidence suggests that Fat cadherins mediate contact-induced changes that ultimately impose a structure to developing neuronal circuits.

Structural plasticity of the N-terminal capping helix of the TPR domain of kinesin light chain.

Kinesin1 plays a major role in neuronal transport by recruiting many different cargos through its kinesin light chain (KLC). Various structurally unrelated cargos interact with the conserved tetratricopeptide repeat (TPR) domain of KLC. The N-terminal capping helix of the TPR domain exhibits an atypical sequence and structural features that may contribute to the versatility of the TPR domain to bind different cargos. We determined crystal structures of the TPR domain of both KLC1 and KLC2 encompassing the N-terminal capping helix and show that this helix exhibits two distinct and defined orientations relative to the rest of the TPR domain. Such a difference in orientation gives rise, at the N-terminal part of the groove, to the formation of one hydrophobic pocket, as well as to electrostatic variations at the groove surface. We present a comprehensive structural analysis of available KLC1/2-TPR domain structures that highlights that ligand binding into the groove can be specific of one or the other N-terminal capping helix orientations. Further, structural analysis reveals that the N-terminal capping helix is always involved in crystal packing contacts, especially in a TPR1:TPR1’ contact which highlights its propensity to be a protein–protein interaction site. Together, these results underline that the structural plasticity of the N-terminal capping helix might represent a structural determinant for TPR domain structural versatility in cargo binding.

IntPred: a structure-based predictor of protein-protein interaction sites.

MotivationProtein–protein interactions are vital for protein function with the average protein having between three and ten interacting partners. Knowledge of precise protein–protein interfaces comes from crystal structures deposited in the Protein Data Bank (PDB), but only 50% of structures in the PDB are complexes. There is therefore a need to predict protein–protein interfaces in silico and various methods for this purpose. Here we explore the use of a predictor based on structural features and which exploits random forest machine learning, comparing its performance with a number of popular established methods.ResultsOn an independent test set of obligate and transient complexes, our IntPred predictor performs well (MCC = 0.370, ACC = 0.811, SPEC = 0.916, SENS = 0.411) and compares favourably with other methods. Overall, IntPred ranks second of six methods tested with SPPIDER having slightly better overall performance (MCC = 0.410, ACC = 0.759, SPEC = 0.783, SENS = 0.676), but considerably worse specificity than IntPred. As with SPPIDER, using an independent test set of obligate complexes enhanced performance (MCC = 0.381) while performance is somewhat reduced on a dataset of transient complexes (MCC = 0.303). The trade-off between sensitivity and specificity compared with SPPIDER suggests that the choice of the appropriate tool is application-dependent.Availability and implementationIntPred is implemented in Perl and may be downloaded for local use or run via a web server at www.bioinf.org.uk/intpred/.Supplementary information Supplementary data are available at Bioinformatics online.

Protein–protein interaction site predictions with minimum covariance determinant and Mahalanobis distance

Protein–protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein–protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application.

An Autoinhibitory Role for the Pleckstrin Homology Domain of Interleukin-2-Inducible Tyrosine Kinase and Its Interplay with Canonical Phospholipid Recognition.

Pleckstrin homology (PH) domains are well-known as phospholipid binding modules, yet evidence that PH domain function extends beyond lipid recognition is mounting. In this work, we characterize a protein binding function for the PH domain of interleukin-2-inducible tyrosine kinase (ITK), an immune cell specific signaling protein that belongs to the TEC family of nonreceptor tyrosine kinases. Its N-terminal PH domain is a well-characterized lipid binding module that localizes ITK to the membrane via phosphatidylinositol 3,4,5-trisphosphate (PIP3) binding. Using a combination of nuclear magnetic resonance spectroscopy and mutagenesis, we have mapped an autoregulatory protein interaction site on the ITK PH domain that makes direct contact with the catalytic kinase domain of ITK, inhibiting the phospho-transfer reaction. Moreover, we have elucidated an important interplay between lipid binding by the ITK PH domain and the stability of the autoinhibitory complex formed by full length ITK. The ITK activation loop in the kinase domain becomes accessible to phosphorylation to the exogenous kinase LCK upon binding of the ITK PH domain to PIP3. By clarifying the allosteric role of the ITK PH domain in controlling ITK function, we have expanded the functional repertoire of the PH domain generally and opened the door to alternative strategies to target this specific kinase in the context of immune cell signaling.

One-Pot Synthesis of Multiple Protein-Encapsulated DNA Flowers and Their Application in Intracellular Protein Delivery.

Inspired by biological systems, many biomimetic methods suggest fabrication of functional materials with unique physicochemical properties. Such methods frequently generate organic-inorganic composites that feature highly ordered hierarchical structures with intriguing properties, distinct from their individual components. A striking example is that of DNA-inorganic hybrid micro/nanostructures, fabricated by the rolling circle technique. Here, a novel concept for the encapsulation of bioactive proteins in DNA flowers (DNF) while maintaining the activity of protein payloads is reported. A wide range of proteins, including enzymes, can be simultaneously associated with the growing DNA strands and Mg2 PPi crystals during the rolling circle process, ultimately leading to the direct immobilization of proteins into DNF. The unique porous structure of this construct, along with the abundance of Mg ions and DNA molecules present, provides many interaction sites for proteins, enabling high loading efficiency and enhanced stability. Further, as a proof of concept, it is demonstrated that the DNF can deliver payloads of cytotoxic protein (i.e., RNase A) to the cells without a loss in its biological function and structural integrity, resulting in highly increased cell death compared to the free protein.

NHS-Esters As Versatile Reactivity-Based Probes for Mapping Proteome-Wide Ligandable Hotspots.

Most of the proteome is considered undruggable, oftentimes hindering translational efforts for drug discovery. Identifying previously unknown druggable hotspots in proteins would enable strategies for pharmacologically interrogating these sites with small molecules. Activity-based protein profiling (ABPP) has arisen as a powerful chemoproteomic strategy that uses reactivity-based chemical probes to map reactive, functional, and ligandable hotspots in complex proteomes, which has enabled inhibitor discovery against various therapeutic protein targets. Here, we report an alkyne-functionalized N-hydroxysuccinimide-ester (NHS-ester) as a versatile reactivity-based probe for mapping the reactivity of a wide range of nucleophilic ligandable hotspots, including lysines, serines, threonines, and tyrosines, encompassing active sites, allosteric sites, post-translational modification sites, protein interaction sites, and previously uncharacterized potential binding sites. Surprisingly, we also show that fragment-based NHS-ester ligands can be made to confer selectivity for specific lysine hotspots on specific targets including Dpyd, Aldh2, and Gstt1. We thus put forth NHS-esters as promising reactivity-based probes and chemical scaffolds for covalent ligand discovery.

Identification of Sequence Variants within Experimentally Validated Protein Interaction Sites Provides New Insights into Molecular Mechanisms of Disease Development.

Protein interactions (PI) underlie complex biological processes. Protein interaction partners include DNA, RNA, ions, small chemical compounds, and proteins (protein-protein interactions; PPI). Analysis of sequence variants within regions corresponding to experimentally validated PI sites presents novel opportunities for understanding of complex diseases. Such information has not been systematically collected due to the fact that datasets are dispersed throughout databases and publications. Sequence variants and PI regions were obtained from the UniProt database. The location of the variants was compared to start and end positions of each PPI. Associations of sequence variants with phenotype were obtained from databases including COSMIC, GAD, PharmGKB, and dbSNP. We developed a catalogue of 603 sequence variants located within regions corresponding to experimentally validated PI sites, mostly PPI regions. These sequence variants were previously associated with risk for cancer, reproduction, ageing, renal, and immune system diseases. The developed catalogue connects information from different research papers and databases, represents a new layer of information and enables designing new hypotheses. It provides a baseline for prioritization of sequence variants, which may affect protein function and binding sites. The study contributes to the development of the proteogenomics field and provides new insights for understanding molecular mechanisms underlying disease development.

Dynamics of the E. coli beta clamp and its influence on DNA loading

Sliding clamps are found in all domains of life and are essential for efficient DNA replication, which is required every time a cell divides, as well as for coordinating traffic on DNA. The Escherichia coli (E. coli) beta‐clamp is a ring‐shaped protein consisting of two identical monomers encoded by the dnaN gene that associates with DNA polymerase III and facilitates the high degree of processivity required for DNA replication. Sliding clamp proteins open and are loaded onto specific DNA structures by clamp loaders in the presence of ATP. We aim to gain insights into the contributions of different domains to the function of beta using a linked‐beta‐clamp that constrains the homodimer at one of two interfaces. Usually the homo‐dimeric structure of the beta‐clamp allows it to act as a molecular tool belt, binding more than one protein simultaneously at specific protein interaction sites on the clamp. Thus, a better understanding of the sliding clamps' role in the process of DNA damage tolerance will be gathered by investigating whether one interface or binding site is adequate for DNA loading or for other protein interactions. To create this construct, the linker length and sequence, as well as expression conditions, were optimized. The linked‐beta proteins were characterized through a thermal denaturation assay, and showed comparable thermal stability to wild‐type beta. In an ATPase assay, similar amounts of inorganic phosphate were detected in reactions containing either linked‐beta or wild‐type beta, indicating that the clamp loader can interact with both versions of the beta clamp. Currently, we are investigating whether linked and wild‐type beta improve the processivity of a polymerase in a primer extension assay. We are now constructing and characterizing variants of wild‐type beta and linked‐beta to test the importance of residues at only one of the interfaces or partner protein binding sites.

ISPRED4: interaction sites PREDiction in protein structures with a refining grammar model.

The identification of protein-protein interaction (PPI) sites is an important step towards the characterization of protein functional integration in the cell complexity. Experimental methods are costly and time-consuming and computational tools for predicting PPI sites can fill the gaps of PPI present knowledge. We present ISPRED4, an improved structure-based predictor of PPI sites on unbound monomer surfaces. ISPRED4 relies on machine-learning methods and it incorporates features extracted from protein sequence and structure. Cross-validation experiments are carried out on a new dataset that includes 151 high-resolution protein complexes and indicate that ISPRED4 achieves a per-residue Matthew Correlation Coefficient of 0.48 and an overall accuracy of 0.85. Benchmarking results show that ISPRED4 is one of the top-performing PPI site predictors developed so far. gigi@biocomp.unibo.it. ISPRED4 and datasets used in this study are available at http://ispred4.biocomp.unibo.it .

JET2 Viewer: a database of predicted multiple, possibly overlapping, protein–protein interaction sites for PDB structures

The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET2 at large-scale on more than 20 000 chains. JET2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein–protein interactions modulation and interaction surface redesign.

A Highly Diverse and Functional Naïve Ubiquitin Variant Library for Generation of Intracellular Affinity Reagents

We report the design, construction, and validation of a highly diverse phage-displayed naïve ubiquitin variant (Ubv) library. We first conducted a mutation tolerance scan of 27 residues and confirmed that 24 of these could be substituted by chemically diverse amino acids without compromising the display of Ubvs on phage. Subsequently, we constructed a library containing 6.8×1010 unique members, in which these 24 positions were diversified with a degenerate codon that encodes for 6 aa that are prevalent in protein interaction sites. To ensure the optimal structural stability of the Ubvs, we constructed the library in a two-step process, whereby 12 positions were randomized first, and following the selection for displayed Ubvs, the resulting pool was further diversified at the other 12 positions. The resulting library was validated by conducting binding selections against a panel of 40 diverse protein antigens and was found to be as functional as a highly validated synthetic antibody library, yielding binders against 30 of the antigens. Detailed characterization of an Ubv that bound to the cell-surface receptor human epidermal growth factor receptor 3 revealed tight binding in the single-digit nanomolar range. Moreover, Ubvs that bound to two distinct sites on the intracellular adapter Grb2 could be combined to generate a potent inhibitor that functioned in cells. These results validate ubiquitin as a robust scaffold for the construction of naïve libraries that can be used to generate Ubvs that target signaling networks both outside and inside the cells.

Electrophilic Helical Peptides That Bond Covalently, Irreversibly, and Selectively in a Protein-Protein Interaction Site.

Protein-protein interactions mediate most physiological and disease processes. Helix-constrained peptides potently mimic or inhibit these interactions by making multiple contacts over large surface areas. However, despite high affinities, they typically have short lifetimes bound to the protein. Here we insert both a helix-inducing constraint and an adjacent electrophile into the native peptide ligand BIM to target the oncogenic protein Bcl2A1. The modified BIM peptide bonds covalently and irreversibly to one cysteine within the helix-binding groove of Bcl2A1, but not to two other exposed cysteines on its surface, and shows no covalent bonding to other Bcl2 proteins. It also penetrates cell membranes and bonds covalently to Bcl2A1 inside cells. This innovative approach to increasing receptor residence time of helical peptides demonstrates the potential to selectively silence a PPI inside cells, with selectivity over other nucleophilic sites on proteins.

Computational identification of non-synonymous polymorphisms within regions corresponding to protein interaction sites

BackgroundProtein-protein interactions (PPI) play an important role in function of all organisms and enable understanding of underlying metabolic processes. Computational predictions of PPIs are an important aspect in proteomics, as experimental methods may result in high degree of false positive results and are more expensive. Although there are many databases collecting predicted PPIs, exploration of genetics information underlying PPI interactions has not been investigated thoroughly. The aim of the present study was to identify genomic locations corresponding to regions involved in predicted PPIs and to collect non-synonymous polymorphisms (nsSNPs) located within those regions; which we termed PPI-SNPs. MethodsPredicted PPIs were obtained from PiSITE database (http://pisite.hgc.jp). Non-synonymous SNPs mapped on protein structural data (PDBs) were obtained from the UCSC server. Polymorphism locations on protein structures were mapped to predicted PPI regions. DAVID tool was used for pathway enrichment and gene cluster analysis (https://david.ncifcrf.gov/). ResultsWe collected 544 polymorphisms located within predicted PPI sites that map to 197 genes. We identified 9 SNPs, previously associated with diseases, but not yet associated with PPI sites. We also found examples in which polymorphisms located within predicted PPI regions are also occurring within previously experimentally validated PPIs and within experimentally determined functional domains. ConclusionsOur study provides the first catalog of nsSNPs located within predicted PPIs. These prioritized SNPs present the basis for planning experimental validation of SNPs that cause gain or loss of PPIs. Our implementation is expandable, as datasets used are constantly updated.

Protein Interaction Profile Sequencing (PIP-seq).

Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc.

Structure and target interaction of a G-quadruplex RNA-aptamer

ABSTRACTG-quadruplexes have recently moved into focus of research in nucleic acids, thereby evolving in scientific significance from exceptional secondary structure motifs to complex modulators of gene regulation. Aptamers (nucleic acid based ligands with recognition properties for a specific target) that form Gquadruplexes may have particular potential for therapeutic applications as they combine the characteristics of specific targeting and Gquadruplex mediated stability and regulation. We have investigated the structure and target interaction properties of one such aptamer: AIR-3 and its truncated form AIR-3A. These RNA aptamers are specific for human interleukin-6 receptor (hIL-6R), a key player in inflammatory diseases and cancer, and have recently been exploited for in vitro drug delivery studies. With the aim to resolve the RNA structure, global shape, RNA:protein interaction site and binding stoichiometry, we now investigated AIR-3 and AIR-3A by different methods including RNA structure probing, Small Angle X-ray scattering and microscale thermophoresis. Our findings suggest a broader spectrum of folding species than assumed so far and remarkable tolerance toward different modifications. Mass spectrometry based binding site analysis, supported by molecular modeling and docking studies propose a general Gquadruplex affinity for the target molecule hIL-6R.

RGS14 regulates the lifetime of Gα-GTP signaling but does not prolong Gβγ signaling following receptor activation in live cells.

RGS14 is a multifunctional scaffolding protein possessing two distinct G protein interaction sites including a regulator of G protein signaling (RGS) domain that acts as a GTPase activating protein (GAP) to deactivate Gαi/o‐GTP proteins, and a G protein regulatory (GPR) motif that binds inactive Gαi1/3‐GDP proteins independent of Gβγ. GPR interactions with Gαi recruit RGS14 to the plasma membrane to interact with Gαi‐linked GPCRs and regulate Gαi signaling. While RGS14 actions on Gα proteins are well characterized, consequent effects on Gβγ signaling remain unknown. Conventional RGS proteins act as dedicated GAPs to deactivate Gα and Gβγ signaling following receptor activation. RGS14 may do the same or, alternatively, may coordinate its actions to deactivate Gα‐GTP with the RGS domain and then capture the same Gα‐GDP via its GPR motif to prevent heterotrimer reassociation and prolong Gβγ signaling. To test this idea, we compared the regulation of G protein activation and deactivation kinetics by a conventional RGS protein, RGS4, and RGS14 in response to GPCR agonist/antagonist treatment utilizing bioluminescence resonance energy transfer (BRET). Co‐expression of either RGS4 or RGS14 inhibited the release of free Gβγ after agonist stimulation and increased the deactivation rate of Gα, consistent with their roles as GTPase activating proteins (GAPs). Overexpression of inactive Gαi1 to recruit RGS14 to the plasma membrane did not alter RGS14′s capacity to act as a GAP for a second Gαo protein. These results demonstrate the role of RGS14 as a dedicated GAP and suggest that the G protein regulatory (GPR) motif functions independently of the RGS domain and is silent in regulating GAP activity in a cellular context.

The alpha-fetoprotein (AFP) third domain: a search for AFP interaction sites of cell cycle proteins.

The carboxy-terminal third domain of alpha-fetoprotein (AFP-3D) is known to harbor binding and/or interaction sites for hydrophobic ligands, receptors, and binding proteins. Such reports have established that AFP-3D consists of amino acid (AA) sequence stretches on the AFP polypeptide that engages in protein-to-protein interactions with various ligands and receptors. Using a computer software program specifically designed for such interactions, the present report identified AA sequence fragments on AFP-3D that could potentially interact with a variety of cell cycle proteins. The cell cycle proteins identified were (1) cyclins, (2) cyclin-dependent kinases, (3) cell cycle-associated proteins (inhibitors, checkpoints, initiators), and (4) ubiquitin ligases. Following detection of the AFP-3D to cell cycle protein interaction sites, the computer-derived AFP localization AA sequences were compared and aligned with previously reported hydrophobic ligand and receptor interaction sites on AFP-3D. A literature survey of the association of cell cycle proteins with AFP showed both positive relationships and correlations. Previous reports of experimental AFP-derived peptides effects on various cell cycle proteins served to confirm and verify the present computer cell cycle protein identifications. Cell cycle protein interactions with AFP-CD peptides have been reported in cultured MCF-7 breast cancer cells subjected to mRNA microarray analysis. After 7days in culture with MCF-7 cells, the AFP-derived peptides were shown to downregulate cyclin E, SKP2, checkpoint suppressors, cyclin-dependent kinases, and ubiquitin ligases that modulate cyclin E/CdK2 transition from the G1 to the S-phase of the cell cycle. Thus, the experimental data on AFP-CD interaction with cell cycle proteins were consistent with the "in silico" findings.