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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.

The acidic domain of SET binds and represses unacetylated p53, but this interaction is prevented by cellular-stress-induced p53 CTD acetylation. Acetylation in the p53 tumour suppressor The tumour suppressor p53 is acetylated on lysines in the C-terminal domain (CTD) but the precise role of acetylation has been unclear. Here, Wei Gu and colleagues identify the transcriptional oncoprotein SET as a protein that binds unacetylated p53 and represses p53 transcriptional activity. When p53 becomes acetylated after cellular stress, SET can no longer bind and p53 is activated. The authors show that SET has an acidic domain that acts as a 'reader' for the unacetylated p53 C-terminal domain. This mechanism of acetylation-dependent regulation seems to be widespread — acetylation also modulates interactions of p53 with acidic domains found in some of its other regulators, and computational analysis reveals numerous proteins with the potential to act as readers containing acidic domains or lysine-rich targets for these acidic domains. Although lysine acetylation is now recognized as a general protein modification for both histones and non-histone proteins 1 , 2 , 3 , 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 4 and its precise role remains unclear. Lysine acetylation often creates binding sites for bromodomain-containing ‘reader’ proteins 5 , 6 . 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.

Desmosomes are intercellular adhesive junctions that impart strength to vertebrate tissues. Their dense, ordered intercellular attachments are formed by desmogleins (Dsgs) and desmocollins (Dscs), but the nature of trans-cellular interactions between these specialized cadherins is unclear. Here, using solution biophysics and coated-bead aggregation experiments, we demonstrate family-wise heterophilic specificity: All Dsgs form adhesive dimers with all Dscs, with affinities characteristic of each Dsg:Dsc pair. Crystal structures of ectodomains from Dsg2 and Dsg3 and from Dsc1 and Dsc2 show binding through a strand-swap mechanism similar to that of homophilic classical cadherins. However, conserved charged amino acids inhibit Dsg:Dsg and Dsc:Dsc interactions by same-charge repulsion and promote heterophilic Dsg:Dsc interactions through opposite-charge attraction. These findings show that Dsg:Dsc heterodimers represent the fundamental adhesive unit of desmosomes and provide a structural framework for understanding desmosome assembly.

Protein–protein interactions, essential for understanding how a cell functions, are predicted using a new method that combines protein structure with other computationally and experimentally derived clues. Protein interactions predicted The analysis of protein-interaction networks is essential to an understanding of the regulatory processes in a living cell. Many methods have been developed with a view to predicting protein–protein interactions (PPIs) at a genome-wide level, although the differences obtained using these approaches suggest that there are still factors unaccounted for. Barry Honig and colleagues have developed a new way of predicting PPIs that is based on the proteins' three-dimensional structures and functional data. Tests of several predictions of the new algorithm, known as PREPPI, confirm the accuracy of the results. The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms 1 , 2 . Much of our present knowledge derives from high-throughput techniques such as the yeast two-hybrid assay and affinity purification 3 , as well as from manual curation of experiments on individual systems 4 . A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein–protein interactions (PPIs) 5 , 6 . Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages 7 , 8 , 9 . Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence. Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human. Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins.

The recognition of specific DNA sequences by proteins is thought to depend on two types of mechanism: one that involves the formation of hydrogen bonds with specific bases, primarily in the major groove, and one involving sequence-dependent deformations of the DNA helix. By comprehensively analysing the three-dimensional structures of protein–DNA complexes, here we show that the binding of arginine residues to narrow minor grooves is a widely used mode for protein–DNA recognition. This readout mechanism exploits the phenomenon that narrow minor grooves strongly enhance the negative electrostatic potential of the DNA. The nucleosome core particle offers a prominent example of this effect. Minor-groove narrowing is often associated with the presence of A-tracts, AT-rich sequences that exclude the flexible TpA step. These findings indicate that the ability to detect local variations in DNA shape and electrostatic potential is a general mechanism that enables proteins to use information in the minor groove, which otherwise offers few opportunities for the formation of base-specific hydrogen bonds, to achieve DNA-binding specificity. Major to minor How sequence-specific DNA-binding proteins can find targets in the midst of vast amounts of non-specific DNA is a long-standing puzzle. A favoured model was that the sequence was read as hydrogen bonds formed between the protein and bases in the major groove of the DNA helix. A new analysis of the three-dimensional structures of protein–DNA complexes suggests that DNA shape is key to recognition. DNA sequence context alters the width of the minor groove of the helix by preferential binding of arginines to electronegative pockets. The positioning of DNA in the nucleosome core particle is an example of this effect. The question of how proteins recognize specific DNA sequences in the face of vastly higher concentrations of non-specific DNA remains unclear. One suggested mechanism involves the formation of hydrogen bonds with specific bases, primarily in the major groove. The comprehensive analysis of the three-dimensional structures of protein–DNA complexes now shows that the binding of arginine residues to narrow minor grooves is a widely used mode for protein–DNA recognition.

With the advent of Systems Biology, the prediction of whether two proteins form a complex has become a problem of increased importance. A variety of experimental techniques have been applied to the problem, but three-dimensional structural information has not been widely exploited. Here we explore the range of applicability of such information by analyzing the extent to which the location of binding sites on protein surfaces is conserved among structural neighbors. We find, as expected, that interface conservation is most significant among proteins that have a clear evolutionary relationship, but that there is a significant level of conservation even among remote structural neighbors. This finding is consistent with recent evidence that information available from structural neighbors, independent of classification, should be exploited in the search for functional insights. The value of such structural information is highlighted through the development of a new protein interface prediction method, PredUs, that identifies what residues on protein surfaces are likely to participate in complexes with other proteins. The performance of PredUs, as measured through comparisons with other methods, suggests that relationships across protein structure space can be successfully exploited in the prediction of protein-protein interactions.

Crystal structures of LeuT, a bacterial homologue of mammalian neurotransmitter transporters, show a molecule of bound substrate that is essentially exposed to the extracellular space but occluded from the cytoplasm. Thus, there must exist an alternate conformation for LeuT in which the substrate is accessible to the cytoplasm and a corresponding mechanism that switches accessibility from one side of the membrane to the other. Here, we identify the cytoplasmic accessibility pathway of the alternate conformation in a mammalian serotonin transporter (SERT) (a member of the same transporter family as LeuT). We also propose a model for the cytoplasmic-facing state that exploits the internal pseudosymmetry observed in the crystal structure. LeuT contains two structurally similar repeats (TMs1-5 and TMs 6-10) that are inverted with respect to the plane of the membrane. The conformational differences between them result in the formation of the extracellular pathway. Our model for the cytoplasm-facing state exchanges the conformations of the two repeats and thus exposes the substrate and ion-binding sites to the cytoplasm. The conformational change that connects the two states primarily involves the tilting of a 4-helix bundle composed of transmembrane helices 1, 2, 6, and 7. Switching the tilt angle of this bundle is essentially equivalent to switching the conformation of the two repeats. Extensive mutagenesis of SERT and accessibility measurements, using cysteine reagents, are accommodated by our model. These observations may be of relevance to other transporter families, many of which contain internal inverted repeats.

Neurite self-recognition and avoidance are fundamental properties of all nervous systems 1 . These processes facilitate dendritic arborization 2 , 3 , prevent formation of autapses 4 and allow free interaction among non-self neurons 1 , 2 , 4 , 5 . Avoidance among self neurites is mediated by stochastic cell-surface expression of combinations of about 60 isoforms of α-, β- and γ-clustered protocadherin that provide mammalian neurons with single-cell identities 1 , 2 , 4 – 13 . Avoidance is observed between neurons that express identical protocadherin repertoires 2 , 5 , and single-isoform differences are sufficient to prevent self-recognition 10 . Protocadherins form isoform-promiscuous cis dimers and isoform-specific homophilic trans dimers 10 , 14 – 20 . Although these interactions have previously been characterized in isolation 15 , 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 chains 11 . Clustered protocadherin ectodomains spontaneously assemble to form a zipper-like lattice of alternating cis and trans interactions at membrane contact sites, which probably represents their mode of function in neuronal self-recognition.

Intercellullar junctions formed by cadherins, including desmosomes and adherens junctions, comprise two dimensional arrays of \"trans\" dimers formed between monomers emanating from opposing cell surfaces. Lateral \"cis\" interfaces between cadherins from the same cell surface have been proposed to play a role in cadherin clustering. Although the molecular details of cis interactions remain uncertain, they must define an anisotropic arrangement where binding is favorable only in certain orientations. Here we report Monte Carlo simulations performed on a 2D lattice constructed to account for the anisotropy in cadherin cis interactions. A crucial finding is that the \"phase transition\" between freely diffusing cadherin monomers and dimers and a condensed ordered 2D junction formed by dimers alone is a cooperative process involving both trans and cis interactions. Moreover, cis interactions, despite being too weak to be measured in solution, are critical to the formation of an ordered junction structure. We discuss these results in light of available experimental information on cadherin binding free energies that are transformed from their bulk solution values to interaction energies on a 2D lattice.

The cadherin (cdh) superfamily of adhesion molecules carry O-linked mannose (O-Man) glycans at highly conserved sites localized to specific β-strands of their extracellular cdh (EC) domains. These O-Man glycans do not appear to be elongated like O-Man glycans found on α-dystroglycan (α-DG), and we recently demonstrated that initiation of cdh/protocadherin (pcdh) O-Man glycosylation is not dependent on the evolutionary conserved POMT1/POMT2 enzymes that initiate O-Man glycosylation on α-DG. Here, we used a CRISPR/Cas9 genetic dissection strategy combined with sensitive and quantitative O-Man glycoproteomics to identify a homologous family of four putative protein O-mannosyltransferases encoded by the TMTC1–4 genes, which were found to be imperative for cdh and pcdh O-Man glycosylation. KO of all four TMTC genes in HEK293 cells resulted in specific loss of cdh and pcdh O-Man glycosylation, whereas combined KO of TMTC1 and TMTC3 resulted in selective loss of O-Man glycans on specific β-strands of EC domains, suggesting that each isoenzyme serves a different function. In addition, O-Man glycosylation of IPT/TIG domains of plexins and hepatocyte growth factor receptor was not affected in TMTC KO cells, suggesting the existence of yet another O-Man glycosylation machinery. Our study demonstrates that regulation of O-mannosylation in higher eukaryotes is more complex than envisioned, and the discovery of the functions of TMTCs provide insight into cobblestone lissencephaly caused by deficiency in TMTC3.