Adhesion Protein Structure, Molecular Affinities, and Principles of Cell-Cell Recognition.

The ability of cells to organize into multicellular structures in precise patterns requires that they "recognize" one another with high specificity. We discuss recent progress in understanding the molecular basis of cell-cell recognition, including unique phenomena associated with neuronal interactions. We describe structures of select adhesion receptor complexes and their assembly into larger intercellular junction structures and discuss emerging principles that relate cell-cell organization to the binding specificities and energetics of adhesion receptors. Armed with these insights, advances in protein design and gene editing should pave the way for breakthroughs toward understanding the molecular basis of cell patterning in vivo.

A Structure-Informed Atlas of Human-Virus Interactions.

While knowledge of protein-protein interactions (PPIs) is critical for understanding virus-host relationships, limitations on the scalability of high-throughput methods have hampered their identification beyond a number of well-studied viruses. Here, we implement an in silico computational framework (pathogen host interactome prediction using structure similarity [P-HIPSTer]) that employs structural information to predict ∼282,000 pan viral-human PPIs with an experimental validation rate of ∼76%. In addition to rediscovering known biology, P-HIPSTer has yielded a series of new findings: the discovery of shared and unique machinery employed across human-infecting viruses, a likely role for ZIKV-ESR1 interactions in modulating viral replication, the identification of PPIs that discriminate between human papilloma viruses (HPVs) with high and low oncogenic potential, and a structure-enabled history of evolutionary selective pressure imposed on the human proteome. Further, P-HIPSTer enables discovery of previously unappreciated cellular circuits that act on human-infecting viruses and provides insight into experimentally intractable viruses.

Molecular logic of neuronal self-recognition through protocadherin domain interactions.

Self-avoidance, a process preventing interactions of axons and dendrites from the same neuron during development, is mediated in vertebrates through the stochastic single-neuron expression of clustered protocadherin protein isoforms. Extracellular cadherin (EC) domains mediate isoform-specific homophilic binding between cells, conferring cell recognition through a poorly understood mechanism. Here, we report crystal structures for the EC1-EC3 domain regions from four protocadherin isoforms representing the α, ß, and γ subfamilies. All are rod shaped and monomeric in solution. Biophysical measurements, cell aggregation assays, and computational docking reveal that trans binding between cells depends on the EC1-EC4 domains, which interact in an antiparallel orientation. We also show that the EC6 domains are required for the formation of cis-dimers. Overall, our results are consistent with a model in which protocadherin cis-dimers engage in a head-to-tail interaction between EC1-EC4 domains from apposed cell surfaces, possibly forming a zipper-like protein assembly, and thus providing a size-dependent self-recognition mechanism.

Single-cell identity generated by combinatorial homophilic interactions between α, ß, and γ protocadherins.

Individual mammalian neurons stochastically express distinct repertoires of α, ß, and γ protocadherin (Pcdh) proteins, which function in neural circuit assembly. We report that all three subfamilies of clustered Pcdhs can engage in specific homophilic interactions, that cell surface delivery of Pcdhα isoforms requires cis interactions with other Pcdhs, and that the extracellular cadherin domain EC6 plays a critical role in this process. Examination of homophilic interactions between specific combinations of multiple Pcdh isoforms revealed that Pcdh combinatorial recognition specificities depend on the identity of all of the expressed isoforms. A single mismatched Pcdh isoform can interfere with these combinatorial homophilic interactions. A theoretical analysis reveals that assembly of Pcdh isoforms into multimeric recognition units and the observed tolerance for mismatched isoforms can generate cell surface diversity sufficient for single-cell identity. However, the competing demands of nonself discrimination and self-recognition place limitations on the mechanisms by which homophilic recognition units can function.

ZEPPI: Proteome-scale sequence-based evaluation of protein-protein interaction models.

We introduce ZEPPI (Z-score Evaluation of Protein-Protein Interfaces), a framework to evaluate structural models of a complex based on sequence coevolution and conservation involving residues in protein-protein interfaces. The ZEPPI score is calculated by comparing metrics for an interface to those obtained from randomly chosen residues. Since contacting residues are defined by the structural model, this obviates the need to account for indirect interactions. Further, although ZEPPI relies on species-paired multiple sequence alignments, its focus on interfacial residues allows it to leverage quite shallow alignments. ZEPPI can be implemented on a proteome-wide scale and is applied here to millions of structural models of dimeric complexes in the Escherichia coli and human interactomes found in the PrePPI database. PrePPI's scoring function is based primarily on the evaluation of protein-protein interfaces, and ZEPPI adds a new feature to this analysis through the incorporation of evolutionary information. ZEPPI performance is evaluated through applications to experimentally determined complexes and to decoys from the CASP-CAPRI experiment. As we discuss, the standard CAPRI scores used to evaluate docking models are based on model quality and not on the ability to give yes/no answers as to whether two proteins interact. ZEPPI is able to detect weak signals from PPI models that the CAPRI scores define as incorrect and, similarly, to identify potential PPIs defined as low confidence by the current PrePPI scoring function. A number of examples that illustrate how the combination of PrePPI and ZEPPI can yield functional hypotheses are provided.

Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins.

Members of transcription factor families typically have similar DNA binding specificities yet execute unique functions in vivo. Transcription factors often bind DNA as multiprotein complexes, raising the possibility that complex formation might modify their DNA binding specificities. To test this hypothesis, we developed an experimental and computational platform, SELEX-seq, that can be used to determine the relative affinities to any DNA sequence for any transcription factor complex. Applying this method to all eight Drosophila Hox proteins, we show that they obtain novel recognition properties when they bind DNA with the dimeric cofactor Extradenticle-Homothorax (Exd). Exd-Hox specificities group into three main classes that obey Hox gene collinearity rules and DNA structure predictions suggest that anterior and posterior Hox proteins prefer DNA sequences with distinct minor groove topographies. Together, these data suggest that emergent DNA recognition properties revealed by interactions with cofactors contribute to transcription factor specificities in vivo.

Origins of specificity in protein-DNA recognition.

Specific interactions between proteins and DNA are fundamental to many biological processes. In this review, we provide a revised view of protein-DNA interactions that emphasizes the importance of the three-dimensional structures of both macromolecules. We divide protein-DNA interactions into two categories: those when the protein recognizes the unique chemical signatures of the DNA bases (base readout) and those when the protein recognizes a sequence-dependent DNA shape (shape readout). We further divide base readout into those interactions that occur in the major groove from those that occur in the minor groove. Analogously, the readout of the DNA shape is subdivided into global shape recognition (for example, when the DNA helix exhibits an overall bend) and local shape recognition (for example, when a base pair step is kinked or a region of the minor groove is narrow). Based on the >1500 structures of protein-DNA complexes now available in the Protein Data Bank, we argue that individual DNA-binding proteins combine multiple readout mechanisms to achieve DNA-binding specificity. Specificity that distinguishes between families frequently involves base readout in the major groove, whereas shape readout is often exploited for higher resolution specificity, to distinguish between members within the same DNA-binding protein family.

Visualization of clustered protocadherin neuronal self-recognition complexes.

Neurite self-recognition and avoidance are fundamental properties of all nervous systems1. These processes facilitate dendritic arborization2,3, prevent formation of autapses4 and allow free interaction among non-self neurons1,2,4,5. Avoidance among self neurites is mediated by stochastic cell-surface expression of combinations of about 60 isoforms of α-, ß- and γ-clustered protocadherin that provide mammalian neurons with single-cell identities1,2,4-13. Avoidance is observed between neurons that express identical protocadherin repertoires2,5, and single-isoform differences are sufficient to prevent self-recognition10. Protocadherins form isoform-promiscuous cis dimers and isoform-specific homophilic trans dimers10,14-20. Although these interactions have previously been characterized in isolation15,17-20, structures of full-length protocadherin ectodomains have not been determined, and how these two interfaces engage in self-recognition between neuronal surfaces remains unknown. Here we determine the molecular arrangement of full-length clustered protocadherin ectodomains in single-isoform self-recognition complexes, using X-ray crystallography and cryo-electron tomography. We determine the crystal structure of the clustered protocadherin γB4 ectodomain, which reveals a zipper-like lattice that is formed by alternating cis and trans interactions. Using cryo-electron tomography, we show that clustered protocadherin γB6 ectodomains tethered to liposomes spontaneously assemble into linear arrays at membrane contact sites, in a configuration that is consistent with the assembly observed in the crystal structure. These linear assemblies pack against each other as parallel arrays to form larger two-dimensional structures between membranes. Our results suggest that the formation of ordered linear assemblies by clustered protocadherins represents the initial self-recognition step in neuronal avoidance, and thus provide support for the isoform-mismatch chain-termination model of protocadherin-mediated self-recognition, which depends on these linear chains11.

On the formation of ordered protein assemblies in cell-cell interfaces.

Crystal structures of many cell-cell adhesion receptors reveal the formation of linear "molecular zippers" comprising an ordered one-dimensional array of proteins that form both intercellular (trans) and intracellular (cis) interactions. The clustered protocadherins (cPcdhs) provide an exemplar of this phenomenon and use it as a basis of barcoding of vertebrate neurons. Here, we report both Metropolis and kinetic Monte Carlo simulations of cPcdh zipper formation using simplified models of cPcdhs that nevertheless capture essential features of their three-dimensional structure. The simulations reveal that the formation of long zippers is an implicit feature of cPcdh structure and is driven by their cis and trans interactions that have been quantitatively characterized in previous work. Moreover, in agreement with cryo-electron tomography studies, the zippers are found to organize into two-dimensional arrays even in the absence of attractive interactions between individual zippers. Our results suggest that the formation of ordered two-dimensional arrays of linear zippers of adhesion proteins is a common feature of cell-cell interfaces. From the perspective of simulations, they demonstrate the importance of a realistic depiction of adhesion protein structure and interactions if important biological phenomena are to be properly captured.

SH2 Domains Serve as Lipid-Binding Modules for pTyr-Signaling Proteins.

The Src-homology 2 (SH2) domain is a protein interaction domain that directs myriad phosphotyrosine (pY)-signaling pathways. Genome-wide screening of human SH2 domains reveals that ∼90% of SH2 domains bind plasma membrane lipids and many have high phosphoinositide specificity. They bind lipids using surface cationic patches separate from pY-binding pockets, thus binding lipids and the pY motif independently. The patches form grooves for specific lipid headgroup recognition or flat surfaces for non-specific membrane binding and both types of interaction are important for cellular function and regulation of SH2 domain-containing proteins. Cellular studies with ZAP70 showed that multiple lipids bind its C-terminal SH2 domain in a spatiotemporally specific manner and thereby exert exquisite spatiotemporal control over its protein binding and signaling activities in T cells. Collectively, this study reveals how lipids control SH2 domain-mediated cellular protein-protein interaction networks and suggest a new strategy for therapeutic modulation of pY-signaling pathways.

Sorting of cadherin-catenin-associated proteins into individual clusters.

The cytoplasmic tails of classical cadherins form a multiprotein cadherin-catenin complex (CCC) that constitutes the major structural unit of adherens junctions (AJs). The CCC in AJs forms junctional clusters, "E clusters," driven by cis and trans interactions in the cadherin ectodomain and stabilized by α-catenin-actin interactions. Additional proteins are known to bind to the cytoplasmic region of the CCC. Here, we analyze how these CCC-associated proteins (CAPs) integrate into cadherin clusters and how they affect the clustering process. Using a cross-linking approach coupled with mass spectrometry, we found that the majority of CAPs, including the force-sensing protein vinculin, interact with CCCs outside of AJs. Accordingly, structural modeling shows that there is not enough space for CAPs the size of vinculin to integrate into E clusters. Using two CAPs, scribble and erbin, as examples, we provide evidence that these proteins form separate clusters, which we term "C clusters." As proof of principle, we show, by using cadherin ectodomain monoclonal antibodies (mAbs), that mAb-bound E-cadherin forms separate clusters that undergo trans interactions. Taken together, our data suggest that, in addition to its role in cell-cell adhesion, CAP-driven CCC clustering serves to organize cytoplasmic proteins into distinct domains that may synchronize signaling networks of neighboring cells within tissues.

Push-pull mechanics of E-cadherin ectodomains in biomimetic adhesions.

E-cadherin plays a central role in cell-cell adhesion. The ectodomains of wild-type cadherins form a crystalline-like two-dimensional lattice in cell-cell interfaces mediated by both trans (apposed cell) and cis (same cell) interactions. In addition to these extracellular forces, adhesive strength is further regulated by cytosolic phenomena involving α and ß catenin-mediated interactions between cadherin and the actin cytoskeleton. Cell-cell adhesion can be further strengthened under tension through mechanisms that have not been definitively characterized in molecular detail. Here we quantitatively determine the role of the cadherin ectodomain in mechanosensing. To this end, we devise an E-cadherin-coated emulsion system, in which droplet surface tension is balanced by protein binding strength to give rise to stable areas of adhesion. To reach the honeycomb/cohesive limit, an initial emulsion compression by centrifugation facilitates E-cadherin trans binding, whereas a high protein surface concentration enables the cis-enhanced stabilization of the interface. We observe an abrupt concentration dependence on recruitment into adhesions of constant crystalline density, reminiscent of a first-order phase transition. Removing the lateral cis interaction with a "cis mutant" shifts this transition to higher surface densities leading to denser, yet weaker adhesions. In both proteins, the stabilization of progressively larger areas of deformation is consistent with single-molecule experiments that show a force-dependent lifetime enhancement in the cadherin ectodomain, which may be attributed to the "X-dimer" bond.

Integrating 3D structural information into systems biology.

Systems biology is a data-heavy field that focuses on systems-wide depictions of biological phenomena necessarily sacrificing a detailed characterization of individual components. As an example, genome-wide protein interaction networks are widely used in systems biology and continuously extended and refined as new sources of evidence become available. Despite the vast amount of information about individual protein structures and protein complexes that has accumulated in the past 50 years in the Protein Data Bank, the data, computational tools, and language of structural biology are not an integral part of systems biology. However, increasing effort has been devoted to this integration, and the related literature is reviewed here. Relationships between proteins that are detected via structural similarity offer a rich source of information not available from sequence similarity, and homology modeling can be used to leverage Protein Data Bank structures to produce 3D models for a significant fraction of many proteomes. A number of structure-informed genomic and cross-species (i.e., virus-host) interactomes will be described, and the unique information they provide will be illustrated with a number of examples. Tissue- and tumor-specific interactomes have also been developed through computational strategies that exploit patient information and through genetic interactions available from increasingly sensitive screens. Strategies to integrate structural information with these alternate data sources will be described. Finally, efforts to link protein structure space with chemical compound space offer novel sources of information in drug design, off-target identification, and the identification of targets for compounds found to be effective in phenotypic screens.

Acetylation-regulated interaction between p53 and SET reveals a widespread regulatory mode.

Although lysine acetylation is now recognized as a general protein modification for both histones and non-histone proteins, the mechanisms of acetylation-mediated actions are not completely understood. Acetylation of the C-terminal domain (CTD) of p53 (also known as TP53) was an early example of non-histone protein acetylation and its precise role remains unclear. Lysine acetylation often creates binding sites for bromodomain-containing 'reader' proteins. Here we use a proteomic screen to identify the oncoprotein SET as a major cellular factor whose binding with p53 is dependent on CTD acetylation status. SET profoundly inhibits p53 transcriptional activity in unstressed cells, but SET-mediated repression is abolished by stress-induced acetylation of p53 CTD. Moreover, loss of the interaction with SET activates p53, resulting in tumour regression in mouse xenograft models. Notably, the acidic domain of SET acts as a 'reader' for the unacetylated CTD of p53 and this mechanism of acetylation-dependent regulation is widespread in nature. For example, acetylation of p53 also modulates its interactions with similar acidic domains found in other p53 regulators including VPRBP (also known as DCAF1), DAXX and PELP1 (refs. 7, 8, 9), and computational analysis of the proteome has identified numerous proteins with the potential to serve as acidic domain readers and lysine-rich ligands. Unlike bromodomain readers, which preferentially bind the acetylated forms of their cognate ligands, the acidic domain readers specifically recognize the unacetylated forms of their ligands. Finally, the acetylation-dependent regulation of p53 was further validated in vivo by using a knock-in mouse model expressing an acetylation-mimicking form of p53. These results reveal that acidic-domain-containing factors act as a class of acetylation-dependent regulators by targeting p53 and, potentially, other proteins.

Trans-endocytosis elicited by nectins transfers cytoplasmic cargo, including infectious material, between cells.

Here, we show that cells expressing the adherens junction protein nectin-1 capture nectin-4-containing membranes from the surface of adjacent cells in a trans-endocytosis process. We find that internalized nectin-1-nectin-4 complexes follow the endocytic pathway. The nectin-1 cytoplasmic tail controls transfer: its deletion prevents trans-endocytosis, while its exchange with the nectin-4 tail reverses transfer direction. Nectin-1-expressing cells acquire dye-labeled cytoplasmic proteins synchronously with nectin-4, a process most active during cell adhesion. Some cytoplasmic cargo remains functional after transfer, as demonstrated with encapsidated genomes of measles virus (MeV). This virus uses nectin-4, but not nectin-1, as a receptor. Epithelial cells expressing nectin-4, but not those expressing another MeV receptor in its place, can transfer infection to nectin-1-expressing primary neurons. Thus, this newly discovered process can move cytoplasmic cargo, including infectious material, from epithelial cells to neurons. We name the process nectin-elicited cytoplasm transfer (NECT). NECT-related trans-endocytosis processes may be exploited by pathogens to extend tropism. This article has an associated First Person interview with the first author of the paper.

Spatial and temporal organization of cadherin in punctate adherens junctions.

Adherens junctions (AJs) play a fundamental role in tissue integrity; however, the organization and dynamics of the key AJ transmembrane protein, E-cadherin, both inside and outside of AJs, remain controversial. Here we have studied the distribution and motility of E-cadherin in punctate AJs (pAJs) of A431 cells. Using single-molecule localization microscopy, we show that pAJs in these cells reach more than 1 µm in length and consist of several cadherin clusters with crystal-like density interspersed within sparser cadherin regions. Notably, extrajunctional cadherin appears to be monomeric, and its density is almost four orders of magnitude less than observed in the pAJ regions. Two alternative strategies of tracking cadherin motion within individual junctions show that pAJs undergo actin-dependent rapid-on the order of seconds-internal reorganizations, during which dense clusters disassemble and their cadherins are immediately reused for new clusters. Our results thus modify the classical view of AJs by depicting them as mosaics of cadherin clusters, the short lifetimes of which enable stable overall morphology combined with rapid internal rearrangements.

Bi-allelic missense disease-causing variants in RPL3L associate neonatal dilated cardiomyopathy with muscle-specific ribosome biogenesis.

Dilated cardiomyopathy (DCM) belongs to the most frequent forms of cardiomyopathy mainly characterized by cardiac dilatation and reduced systolic function. Although most cases of DCM are classified as sporadic, 20-30% of cases show a heritable pattern. Familial forms of DCM are genetically heterogeneous, and mutations in several genes have been identified that most commonly play a role in cytoskeleton and sarcomere-associated processes. Still, a large number of familial cases remain unsolved. Here, we report five individuals from three independent families who presented with severe dilated cardiomyopathy during the neonatal period. Using whole-exome sequencing (WES), we identified causative, compound heterozygous missense variants in RPL3L (ribosomal protein L3-like) in all the affected individuals. The identified variants co-segregated with the disease in each of the three families and were absent or very rare in the human population, in line with an autosomal recessive inheritance pattern. They are located within the conserved RPL3 domain of the protein and were classified as deleterious by several in silico prediction software applications. RPL3L is one of the four non-canonical riboprotein genes and it encodes the 60S ribosomal protein L3-like protein that is highly expressed only in cardiac and skeletal muscle. Three-dimensional homology modeling and in silico analysis of the affected residues in RPL3L indicate that the identified changes specifically alter the interaction of RPL3L with the RNA components of the 60S ribosomal subunit and thus destabilize its binding to the 60S subunit. In conclusion, we report that bi-allelic pathogenic variants in RPL3L are causative of an early-onset, severe neonatal form of dilated cardiomyopathy, and we show for the first time that cytoplasmic ribosomal proteins are involved in the pathogenesis of non-syndromic cardiomyopathies.

Genetic Drivers of Kidney Defects in the DiGeorge Syndrome.

BACKGROUND: The DiGeorge syndrome, the most common of the microdeletion syndromes, affects multiple organs, including the heart, the nervous system, and the kidney. It is caused by deletions on chromosome 22q11.2; the genetic driver of the kidney defects is unknown. METHODS: We conducted a genomewide search for structural variants in two cohorts: 2080 patients with congenital kidney and urinary tract anomalies and 22,094 controls. We performed exome and targeted resequencing in samples obtained from 586 additional patients with congenital kidney anomalies. We also carried out functional studies using zebrafish and mice. RESULTS: We identified heterozygous deletions of 22q11.2 in 1.1% of the patients with congenital kidney anomalies and in 0.01% of population controls (odds ratio, 81.5; P=4.5×10-14). We localized the main drivers of renal disease in the DiGeorge syndrome to a 370-kb region containing nine genes. In zebrafish embryos, an induced loss of function in snap29, aifm3, and crkl resulted in renal defects; the loss of crkl alone was sufficient to induce defects. Five of 586 patients with congenital urinary anomalies had newly identified, heterozygous protein-altering variants, including a premature termination codon, in CRKL. The inactivation of Crkl in the mouse model induced developmental defects similar to those observed in patients with congenital urinary anomalies. CONCLUSIONS: We identified a recurrent 370-kb deletion at the 22q11.2 locus as a driver of kidney defects in the DiGeorge syndrome and in sporadic congenital kidney and urinary tract anomalies. Of the nine genes at this locus, SNAP29, AIFM3, and CRKL appear to be critical to the phenotype, with haploinsufficiency of CRKL emerging as the main genetic driver. (Funded by the National Institutes of Health and others.).

Genome-wide functional annotation of dual-specificity protein- and lipid-binding modules that regulate protein interactions.

Emerging evidence indicates that membrane lipids regulate protein networking by directly interacting with protein-interaction domains (PIDs). As a pilot study to identify and functionally annodate lipid-binding PIDs on a genomic scale, we performed experimental and computational studies of PDZ domains. Characterization of 70 PDZ domains showed that ~40% had submicromolar membrane affinity. Using a computational model built from these data, we predicted the membrane-binding properties of 2,000 PDZ domains from 20 species. The accuracy of the prediction was experimentally validated for 26 PDZ domains. We also subdivided lipid-binding PDZ domains into three classes based on the interplay between membrane- and protein-binding sites. For different classes of PDZ domains, lipid binding regulates their protein interactions by different mechanisms. Functional studies of a PDZ domain protein, rhophilin 2, suggest that all classes of lipid-binding PDZ domains serve as genuine dual-specificity modules regulating protein interactions at the membrane under physiological conditions.

Structure-based prediction of ligand-protein interactions on a genome-wide scale.

We report a template-based method, LT-scanner, which scans the human proteome using protein structural alignment to identify proteins that are likely to bind ligands that are present in experimentally determined complexes. A scoring function that rapidly accounts for binding site similarities between the template and the proteins being scanned is a crucial feature of the method. The overall approach is first tested based on its ability to predict the residues on the surface of a protein that are likely to bind small-molecule ligands. The algorithm that we present, LBias, is shown to compare very favorably to existing algorithms for binding site residue prediction. LT-scanner's performance is evaluated based on its ability to identify known targets of Food and Drug Administration (FDA)-approved drugs and it too proves to be highly effective. The specificity of the scoring function that we use is demonstrated by the ability of LT-scanner to identify the known targets of FDA-approved kinase inhibitors based on templates involving other kinases. Combining sequence with structural information further improves LT-scanner performance. The approach we describe is extendable to the more general problem of identifying binding partners of known ligands even if they do not appear in a structurally determined complex, although this will require the integration of methods that combine protein structure and chemical compound databases.