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Crystallographic, biochemical, and genetic studies reveal the mechanism of Rap protein phosphatase activity within the phosphorelay pathway leading to sporulation in Bacillus species., Bacterial Rap family proteins have been most extensively studied in Bacillus subtilis, where they regulate activities including sporulation, genetic competence, antibiotic expression, and the movement of the ICEBs1 transposon. One subset of Rap proteins consists of phosphatases that control B. subtilis and B. anthracis sporulation by dephosphorylating the response regulator Spo0F. The mechanistic basis of Rap phosphatase activity was unknown. Here we present the RapH-Spo0F X-ray crystal structure, which shows that Rap proteins consist of a 3-helix bundle and a tetratricopeptide repeat domain. Extensive biochemical and genetic functional studies reveal the importance of the observed RapH-Spo0F interactions, including the catalytic role of a glutamine in the RapH 3-helix bundle that inserts into the Spo0F active site. We show that in addition to dephosphorylating Spo0F, RapH can antagonize sporulation by sterically blocking phosphoryl transfer to and from Spo0F. Our structure-function analysis of the RapH-Spo0F interaction identified Rap protein residues critical for Spo0F phosphatase activity. This information enabled us to assign Spo0F phosphatase activity to a Rap protein based on sequence alone, which was not previously possible. Finally, as the ultimate test of our newfound understanding of the structural requirements for Rap phosphatase function, a non-phosphatase Rap protein that inhibits the binding of the response regulator ComA to DNA was rationally engineered to dephosphorylate Spo0F. In addition to revealing the mechanistic basis of response regulator dephosphorylation by Rap proteins, our studies support the previously proposed T-loop-Y allostery model of receiver domain regulation that restricts the aromatic “switch” residue to an internal position when the β4-α4 loop adopts an active-site proximal conformation., Author Summary A phosphorelay signal transduction pathway regulates sporulation in numerous Bacillus species including the genetic model organism, B. subtilis, and the causative agent of anthrax, B. anthracis. Histidine kinases initiate the flow of phosphoryl groups along the phosphorelay pathway, which then shuttles them to a downstream response-regulator transcription factor called Spo0A. Ultimately, sporulation is governed by the cellular concentration of phosphorylated Spo0A. In numerous Bacillus species, Rap phosphatases function in opposition to the histidine kinases, inhibiting Spo0A activation by dephosphorylating an intermediate pathway protein called Spo0F. Here we present the structure of a Rap protein, RapH, in complex with Spo0F, as determined by X-ray crystallography. The RapH–Spo0F structure, along with biochemical and genetic studies, reveals the mechanism of Rap-protein-mediated Spo0F dephosphorylation. We used information gleaned from our structure–function analysis, first, to assign Spo0F phosphatase activity to an uncharacterized Rap protein, RapJ, on the basis of sequence alone, and, second, to engineer Spo0F phosphatase activity de novo into a non-phosphatase Rap protein, RapF. We found that in addition to dephosphorylating Spo0F, Rap proteins can inhibit the sporulation phosphorelay by sterically blocking the transfer of phosphoryl groups to and from Spo0F. Ultimately, new classes of drugs might be developed that disrupt the flow of phosphoryl groups along phosphotransfer signaling pathways by mimicking the antagonistic effects of Rap proteins on response regulators.

Here we investigate the correlations between coding sequence substitutions as a function of their separation along the protein sequence. We consider both substitutions between the reference genomes of several Drosophilids as well as polymorphisms in a population sample of Zimbabwean Drosophila melanogaster. We find that amino acid substitutions are “clustered” along the protein sequence, that is, the frequency of additional substitutions is strongly enhanced within ≈10 residues of a first such substitution. No such clustering is observed for synonymous substitutions, supporting a “correlation length” associated with selection on proteins as the causative mechanism. Clustering is stronger between substitutions that arose in the same lineage than it is between substitutions that arose in different lineages. We consider several possible origins of clustering, concluding that epistasis (interactions between amino acids within a protein that affect function) and positional heterogeneity in the strength of purifying selection are primarily responsible. The role of epistasis is directly supported by the tendency of nearby substitutions that arose on the same lineage to preserve the total charge of the residues within the correlation length and by the preferential cosegregation of neighboring derived alleles in our population sample. We interpret the observed length scale of clustering as a statistical reflection of the functional locality (or modularity) of proteins: amino acids that are near each other on the protein backbone are more likely to contribute to, and collaborate toward, a common subfunction., Author Summary Genes are templates for proteins, yet evolutionary studies of genes and proteins often bear little resemblance. Analyses of gene evolution typically treat each codon independently, quantifying gene evolution by summing over the constituent codons. In contrast, studies of protein evolution generally incorporate protein structure and interactions between amino acids explicitly. We investigate correlations in the evolution of codons as a function of their distance from each other along the protein coding sequence. This approach is motivated by the expectation that codons near each other in sequence often encode amino acids belonging to the same functional unit. Consequently, these amino acids are more likely to interact and/or experience similar selective regimes, introducing correlation between the evolution of the underlying codons. We find codon evolution in Drosophilids to be correlated over a characteristic length scale of ≈10 codons. Specifically, the presence of a non-synonymous substitution substantially increases the probability of further such substitutions nearby, particularly within that lineage. Further analysis suggests both functional interactions between amino acids and correlation in the strength of selection contribute to this effect. These findings are relevant for understanding the relative importance of different modes of selection, and particularly the role of epistasis, in gene and protein evolution.

International audience; Photoactivated localization microscopy (PALM) and related fluorescent biological imaging methods are capable of providing very high spatial resolutions (up to 20 nm). Two major demands limit its widespread use on biological samples: requirements for photoactivatable/photoconvertible fluorescent molecules, which are sometimes difficult to incorporate, and high background signals from autofluorescence or fluorophores in adjacent focal planes in three-dimensional imaging which reduces PALM resolution significantly. We present here a high-resolution PALM method utilizing conventional EGFP as the photoconvertible fluorophore, improved algorithms to deal with high levels of biological background noise, and apply this to imaging higher order chromatin structure. We found that the emission wavelength of EGFP is efficiently converted from green to red when exposed to blue light in the presence of reduced riboflavin. The photon yield of redconverted EGFP using riboflavin is comparable to other bright photoconvertible fluorescent proteins that allow < 20 nm resolution. We further found that image pre-processing using a combination of denoising and deconvolution of the raw PALM images substantially improved the spatial resolution of the reconstruction from noisy images. Performing PALM on Drosophila mitotic chromosomes labeled with H2AvD-EGFP, a histone H2A variant, revealed filamentous components of ~70 nm. This is the first observation of fine chromatin filaments specific for one histone variant at a resolution approximating that of conventional electron microscope images (10–30 nm). As demonstrated by modeling and experiments on a challenging specimen, the techniques described here facilitate super-resolution fluorescent imaging with common biological samples.

Soluble proteins must maintain backbone hydrogen bonds (BHBs) water-tight to ensure structural integrity. This protection is often achieved by burying the BHBs or wrapping them through intermolecular associations. On the other hand, water has low coordination resilience, with loss of hydrogen-bonding partnerships carrying significant thermodynamic cost. Thus, a core problem in structural biology is whether natural design actually exploits the water coordination stiffness to seal the backbone in regions that are exposed to the solvent. This work explores the molecular design features that make this type of seal operative, focusing on the side-chain arrangements that shield the protein backbone. We show that an efficient sealing is achieved by adapting the sub-nanoscale surface topography to the stringency of water coordination: an exposed BHB may be kept dry if the local concave curvature is small enough to impede formation of the coordination shell of a penetrating water molecule. Examination of an exhaustive database of uncomplexed proteins reveals that exposed BHBs invariably occur within such sub-nanoscale cavities in native folds, while this level of local ruggedness is absent in other regions. By contrast, BHB exposure in misfolded proteins occurs with larger local curvature promoting backbone hydration and consequently, structure disruption. These findings unravel physical constraints fitting a spatially dependent least-action for water coordination, introduce a molecular design concept, and herald the advent of water-tight peptide based materials with sufficient backbone exposure to remain flexible. © 2010 Schulz et al. Fil: Schulz, Erica Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina Fil: Frechero, Marisa Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina Fil: Appignanesi, Gustavo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina Fil: Fernández, Ariel. Rice University; Estados Unidos

Background Pathogenic bacteria adhere to the host cell surface using a family of outer membrane proteins called Trimeric Autotransporter Adhesins (TAAs). Although TAAs are highly divergent in sequence and domain structure, they are all conceptually comprised of a C-terminal membrane anchoring domain and an N-terminal passenger domain. Passenger domains consist of a secretion sequence, a head region that facilitates binding to the host cell surface, and a stalk region. Methodology/Principal Findings Pathogenic species of Burkholderia contain an overabundance of TAAs, some of which have been shown to elicit an immune response in the host. To understand the structural basis for host cell adhesion, we solved a 1.35 Å resolution crystal structure of a BpaA TAA head domain from Burkholderia pseudomallei, the pathogen that causes melioidosis. The structure reveals a novel fold of an intricately intertwined trimer. The BpaA head is composed of structural elements that have been observed in other TAA head structures as well as several elements of previously unknown structure predicted from low sequence homology between TAAs. These elements are typically up to 40 amino acids long and are not domains, but rather modular structural elements that may be duplicated or omitted through evolution, creating molecular diversity among TAAs. Conclusions/Significance The modular nature of BpaA, as demonstrated by its head domain crystal structure, and of TAAs in general provides insights into evolution of pathogen-host adhesion and may provide an avenue for diagnostics.

Genomic correlates of evolutionary adaptation to very low or very high optimal growth temperature (OGT) values have been the subject of many studies. Whereas these provided a protein-structural rationale of the activity and stability of globular proteins/enzymes, the point has been neglected that adaptation to extreme temperatures could also have resulted from an increased use of intrinsically disordered proteins (IDPs), which are resistant to these conditions in vitro. Contrary to these expectations, we found a conspicuously low level of structural disorder in bacteria of very high (and very low) OGT values. This paucity of disorder does not reflect phylogenetic relatedness, i.e. it is a result of genuine adaptation to extreme conditions. Because intrinsic disorder correlates with important regulatory functions, we asked how these bacteria could exist without IDPs by studying transcription factors, known to harbor a lot of function-related intrinsic disorder. Hyperthermophiles have much less transcription factors, which have reduced disorder compared to their mesophilic counterparts. On the other hand, we found by systematic categorization of proteins with long disordered regions that there are certain functions, such as translation and ribosome biogenesis that depend on structural disorder even in hyperthermophiles. In all, our observations suggest that adaptation to extreme conditions is achieved by a significant functional simplification, apparent at both the level of the genome and individual genes/proteins.

Peptidyl-prolyl isomerases catalyze the conversion between cis and trans isomers of proline. The cyclophilin family of peptidyl-prolyl isomerases is well known for being the target of the immunosuppressive drug cyclosporin, used to combat organ transplant rejection. There is great interest in both the substrate specificity of these enzymes and the design of isoform-selective ligands for them. However, the dearth of available data for individual family members inhibits attempts to design drug specificity; additionally, in order to define physiological functions for the cyclophilins, definitive isoform characterization is required. In the current study, enzymatic activity was assayed for 15 of the 17 human cyclophilin isomerase domains, and binding to the cyclosporin scaffold was tested. In order to rationalize the observed isoform diversity, the high-resolution crystallographic structures of seven cyclophilin domains were determined. These models, combined with seven previously solved cyclophilin isoforms, provide the basis for a family-wide structure∶function analysis. Detailed structural analysis of the human cyclophilin isomerase explains why cyclophilin activity against short peptides is correlated with an ability to ligate cyclosporin and why certain isoforms are not competent for either activity. In addition, we find that regions of the isomerase domain outside the proline-binding surface impart isoform specificity for both in vivo substrates and drug design. We hypothesize that there is a well-defined molecular surface corresponding to the substrate-binding S2 position that is a site of diversity in the cyclophilin family. Computational simulations of substrate binding in this region support our observations. Our data indicate that unique isoform determinants exist that may be exploited for development of selective ligands and suggest that the currently available small-molecule and peptide-based ligands for this class of enzyme are insufficient for isoform specificity. Enhanced version This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3-D representations and animated transitions. Please note that a Web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1., Author Summary Cyclophilins are proteins that catalyze the isomerization of prolines, interconverting this structurally important amino acid between cis and trans isomers. Although there are 17 cyclophilins in the human genome, the function of most cyclophilin isoforms is unknown. At least some members of this protein family are of interest for clinically relevant drug design, as they are targets of the drug cyclosporin, which is used as an immunosuppressant to treat patients following organ transplantation. The absence of a comprehensive picture of the similarities and differences between the different members of this protein family precludes effective and specific drug design, however. In the current study we undertake such a global structure∶function analysis. Using biochemical, structural, and computational methods we characterize the human cyclophilin family in detail and suggest that there is a previously overlooked region of these enzymes that contributes significantly to isoform diversity. We propose that this region may represent an important target for isoform-specific drug design.

International audience; BACKGROUND: Protein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. Designed sequences can be more diverse than natural sequences, possibly avoiding some limitations of experimental databases. METHODOLOGY/PRINCIPAL FINDINGS: WE EXPLORE THIS STRATEGY FOR FOUR SCOP FAMILIES: Small Kunitz-type inhibitors (SKIs), Interleukin-8 chemokines, PDZ domains, and large Caspase catalytic subunits, represented by 43 structures. An automated procedure is used to redesign the 43 proteins. We use the experimental backbones as fixed templates in the folded state and a molecular mechanics model to compute the interaction energies between sidechain and backbone groups. Calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is used to scan the sequence and conformational space, yielding 200,000-300,000 sequences per backbone template. The results confirm and generalize our earlier study of SH2 and SH3 domains. The designed sequences ressemble moderately-distant, natural homologues of the initial templates; e.g., the SUPERFAMILY, profile Hidden-Markov Model library recognizes 85% of the low-energy sequences as native-like. Conversely, Position Specific Scoring Matrices derived from the sequences can be used to detect natural homologues within the SwissProt database: 60% of known PDZ domains are detected and around 90% of known SKIs and chemokines. Energy components and inter-residue correlations are analyzed and ways to improve the method are discussed. CONCLUSIONS/SIGNIFICANCE: For some families, designed sequences can be a useful complement to experimental ones for homologue searching. However, improved tools are needed to extract more information from the designed profiles before the method can be of general use.

Background: Understanding the biogenesis pathways for the functional expression of recombinant proteins, in particular membrane proteins and complex multidomain assemblies, is a fundamental issue in cell biology and of high importance for future progress in structural genomics. In this study, we employed a proteomic approach to understand the difference in expression levels for various multidomain membrane proteins in L. lactis cells grown in complex and synthetic media.Methodology/Principal Findings: The proteomic profiles of cells growing in media in which the proteins were expressed to high or low levels suggested a limitation in the availability of branched-chain amino acids, more specifically a too limited capacity to accumulate these nutrients. By supplying the cells with an alternative path for accumulation of Ile, Leu and/or Val, i.e., a medium supplement of the appropriate dipeptides, or by engineering the transport capacity for branched-chain amino acids, the expression levels could be increased several fold.Conclusions: We show that the availability of branched chain amino acids is a critical factor for the (over) expression of proteins in L. lactis. The forward engineering of cells for functional protein production required fine-tuning of co-expression of the branched chain amino acid transporter.

The genome of Saccharomyces cerevisiae is arguably the best studied eukaryotic genome, and yet, it contains approximately 1000 genes that are still relatively uncharacterized. As the majority of these ORFs have no homologs with characterized sequence or protein structure, traditional sequence-based approaches cannot be applied to deduce their biological function. Here, we characterize YER067W, a conserved gene of unknown function that is strongly induced in response to many stress conditions and repressed in drug resistant yeast strains. Gene expression patterns of YER067W and its paralog YIL057C suggest an involvement in energy metabolism. We show that yeast lacking YER067W display altered levels of reserve carbohydrates and a growth deficiency in media that requires aerobic metabolism. Impaired mitochondrial function and overall reduction of ergosterol content in the YER067W deleted strain explained the observed 2- and 4-fold increase in resistance to the drugs fluconazole and amphotericin B, respectively. Cell fractionation and immunofluorescence microscopy revealed that Yer067w is associated with cellular membranes despite the absence of a transmembrane domain in the protein. Finally, the 1.7 A resolution crystal structure of Yer067w shows an alpha-beta fold with low similarity to known structures and a putative functional site. YER067W's involvement with aerobic energetic metabolism suggests the assignment of the gene name RGI1, standing for respiratory growth induced 1. Altogether, the results shed light on a previously uncharacterized protein family and provide basis for further studies of its apparent role in energy metabolism control and drug resistance.

Background: Functional similarity is challenging to identify when global sequence and structure similarity is low. Activesites or functionally relevant regions are evolutionarily more stable relative to the remainder of a protein structure and provide an alternative means to identify potential functional similarity between proteins. We recently developed the FASTNMR methodology to discover biochemical functions or functional hypotheses of proteins of unknown function by experimentally identifying ligand binding sites. FAST-NMR utilizes our CPASS software and database to assign a function based on a similarity in the structure and sequence of ligand binding sites between proteins of known and unknown function. Methodology/Principal Findings: The PrgI protein from Salmonella typhimurium forms the needle complex in the type III secretion system (T3SS). A FAST-NMR screen identified a similarity between the ligand binding sites of PrgI and the Bcl-2 apoptosis protein Bcl-xL. These ligand binding sites correlate with known protein-protein binding interfaces required for oligomerization. Both proteins form membrane pores through this oligomerization to release effector proteins to stimulate cell death. Structural analysis indicates an overlap between the PrgI structure and the pore forming motif of Bcl-xL. A sequence alignment indicates conservation between the PrgI and Bcl-xL ligand binding sites and pore formation regions. This active-site similarity was then used to verify that chelerythrine, a known Bcl-xL inhibitor, also binds PrgI. Conclusions/Significance: A structural and functional relationship between the bacterial T3SS and eukaryotic apoptosis was identified using our FAST-NMR ligand affinity screen in combination with a bioinformatic analysis based on our CPASS program. A similarity between PrgI and Bcl-xL is not readily apparent using traditional global sequence and structure analysis, but was only identified because of conservation in ligand binding sites. These results demonstrate the unique opportunity that ligand-binding sites provide for the identification of functional relationships when global sequence and structural information is limited.

Chromosomal translocations, which often generate chimeric proteins by fusing segments of two distinct genes, represent the single major genetic aberration leading to cancer. We suggest that the unifying theme of these events is a high level of intrinsic structural disorder, enabling fusion proteins to evade cellular surveillance mechanisms that eliminate misfolded proteins. Predictions in 406 translocation-related human proteins show that they are significantly enriched in disorder (43.3% vs. 20.7% in all human proteins), they have fewer Pfam domains, and their translocation breakpoints tend to avoid domain splitting. The vicinity of the breakpoint is significantly more disordered than the rest of these already highly disordered fusion proteins. In the unlikely event of domain splitting in fusion it usually spares much of the domain or splits at locations where the newly exposed hydrophobic surface area approximates that of an intact domain. The mechanisms of action of fusion proteins suggest that in most cases their structural disorder is also essential to the acquired oncogenic function, enabling the long-range structural communication of remote binding and/or catalytic elements. In this respect, there are three major mechanisms that contribute to generating an oncogenic signal: (i) a phosphorylation site and a tyrosine-kinase domain are fused, and structural disorder of the intervening region enables intramolecular phosphorylation (e.g., BCR-ABL); (ii) a dimerisation domain fuses with a tyrosine kinase domain and disorder enables the two subunits within the homodimer to engage in permanent intermolecular phosphorylations (e.g., TFG-ALK); (iii) the fusion of a DNA-binding element to a transactivator domain results in an aberrant transcription factor that causes severe misregulation of transcription (e.g. EWS-ATF). Our findings also suggest novel strategies of intervention against the ensuing neoplastic transformations., Author Summary Chromosomal translocations generate chimeric proteins by fusing segments of two distinct genes and are frequently associated with cancer. The proteins involved are large and fairly heterogeneous in sequence and typically have only a few dispersed structural domains connected by long uncharacterized regions. It has never been studied from a structural perspective how these chimeras survive losing significant portions of the original proteins and acquire new oncogenic functions. By analyzing a collection of 406 human translocation proteins we show here that the answer to both questions lies to a large extent in the high level of structural disorder in the fusion partner proteins (on average, they are twice as disordered as all human proteins). The translocation breakpoints usually avoid globular domains. In rare cases when a globular domain is truncated by the fusion, it happens at a location in the domain where the hydrophobicity exposed by the split is favorable (i.e., not too high). Disorder on average is significantly higher in the vicinity of the breakpoint than in the rest of the fusion proteins. Disorder also plays a pivotal role in the acquired oncogenic function by bringing distant/disparate fusion segments together that enables novel intra- and/or intermolecular interactions.

The study of functional RNAs of various sizes and structures requires efficient methods for their synthesis and purification. Here, 23 group I intron variants ranging in length from 246 to 341 nucleotides -- some containing exons -- were subjected to a native purification technique previously applied only to shorter RNAs (

Background Notch receptors are normally cleaved during maturation by a furin-like protease at an extracellular site termed S1, creating a heterodimer of non-covalently associated subunits. The S1 site lies within a key negative regulatory region (NRR) of the receptor, which contains three highly conserved Lin12/Notch repeats and a heterodimerization domain (HD) that interact to prevent premature signaling in the absence of ligands. Because the role of S1 cleavage in Notch signaling remains unresolved, we investigated the effect of S1 cleavage on the structure, surface trafficking and ligand-mediated activation of human Notch1 and Notch2, as well as on ligand-independent activation of Notch1 by mutations found in human leukemia. Principal Findings The X-ray structure of the Notch1 NRR after furin cleavage shows little change when compared with that of an engineered Notch1 NRR lacking the S1-cleavage loop. Likewise, NMR studies of the Notch2 HD domain show that the loop containing the S1 site can be removed or cleaved without causing a substantial change in its structure. However, Notch1 and Notch2 receptors engineered to resist S1 cleavage exhibit unexpected differences in surface delivery and signaling competence: S1-resistant Notch1 receptors exhibit decreased, but detectable, surface expression and ligand-mediated receptor activation, whereas S1-resistant Notch2 receptors are fully competent for cell surface delivery and for activation by ligands. Variable dependence on S1 cleavage also extends to T-ALL-associated NRR mutations, as common class 1 mutations display variable decrements in ligand-independent activation when introduced into furin-resistant receptors, whereas a class 2 mutation exhibits increased signaling activity. Conclusions/Significance S1 cleavage has distinct effects on the surface expression of Notch1 and Notch2, but is not generally required for physiologic or pathophysiologic activation of Notch proteins. These findings are consistent with models for receptor activation in which ligand-binding or T-ALL-associated mutations lead to conformational changes of the NRR that permit metalloprotease cleavage.

Since the outbreak of severe acute respiratory syndrome (SARS) in 2003, the three-dimensional structures of several of the replicase/transcriptase components of SARS coronavirus (SARS-CoV), the non-structural proteins (Nsps), have been determined. However, within the large Nsp3 (1922 amino-acid residues), the structure and function of the so-called SARS-unique domain (SUD) have remained elusive. SUD occurs only in SARS-CoV and the highly related viruses found in certain bats, but is absent from all other coronaviruses. Therefore, it has been speculated that it may be involved in the extreme pathogenicity of SARS-CoV, compared to other coronaviruses, most of which cause only mild infections in humans. In order to help elucidate the function of the SUD, we have determined crystal structures of fragment 389–652 (“SUDcore”) of Nsp3, which comprises 264 of the 338 residues of the domain. Both the monoclinic and triclinic crystal forms (2.2 and 2.8 Å resolution, respectively) revealed that SUDcore forms a homodimer. Each monomer consists of two subdomains, SUD-N and SUD-M, with a macrodomain fold similar to the SARS-CoV X-domain. However, in contrast to the latter, SUD fails to bind ADP-ribose, as determined by zone-interference gel electrophoresis. Instead, the entire SUDcore as well as its individual subdomains interact with oligonucleotides known to form G-quadruplexes. This includes oligodeoxy- as well as oligoribonucleotides. Mutations of selected lysine residues on the surface of the SUD-N subdomain lead to reduction of G-quadruplex binding, whereas mutations in the SUD-M subdomain abolish it. As there is no evidence for Nsp3 entering the nucleus of the host cell, the SARS-CoV genomic RNA or host-cell mRNA containing long G-stretches may be targets of SUD. The SARS-CoV genome is devoid of G-stretches longer than 5–6 nucleotides, but more extended G-stretches are found in the 3′-nontranslated regions of mRNAs coding for certain host-cell proteins involved in apoptosis or signal transduction, and have been shown to bind to SUD in vitro. Therefore, SUD may be involved in controlling the host cell's response to the viral infection. Possible interference with poly(ADP-ribose) polymerase-like domains is also discussed., Author Summary The genome of the SARS coronavirus codes for 16 non-structural proteins that are involved in replicating this huge RNA (approximately 29 kilobases). The roles of many of these in replication (and/or transcription) are unknown. We attempt to derive conclusions concerning the possible functions of these proteins from their three-dimensional structures, which we determine by X-ray crystallography. Non-structural protein 3 contains at least seven different functional modules within its 1922-amino-acid polypeptide chain. One of these is the so-called SARS-unique domain, a stretch of about 338 residues that is completely absent from any other coronavirus. It may thus be responsible for the extraordinarily high pathogenicity of the SARS coronavirus, compared to other viruses of this family. We describe here the three-dimensional structure of the SARS-unique domain and show that it consists of two modules with a known fold, the so-called macrodomain. Furthermore, we demonstrate that these domains bind unusual nucleic-acid structures formed by consecutive guanosine nucleotides, where four strands of nucleic acid are forming a superhelix (so-called G-quadruplexes). SUD may be involved in binding to viral or host-cell RNA bearing this peculiar structure and thereby regulate viral replication or fight the immune response of the infected host cell.

The envelope (E) protein from coronaviruses is a small polypeptide that contains at least one α-helical transmembrane domain. Absence, or inactivation, of E protein results in attenuated viruses, due to alterations in either virion morphology or tropism. Apart from its morphogenetic properties, protein E has been reported to have membrane permeabilizing activity. Further, the drug hexamethylene amiloride (HMA), but not amiloride, inhibited in vitro ion channel activity of some synthetic coronavirus E proteins, and also viral replication. We have previously shown for the coronavirus species responsible for severe acute respiratory syndrome (SARS-CoV) that the transmembrane domain of E protein (ETM) forms pentameric α-helical bundles that are likely responsible for the observed channel activity. Herein, using solution NMR in dodecylphosphatidylcholine micelles and energy minimization, we have obtained a model of this channel which features regular α-helices that form a pentameric left-handed parallel bundle. The drug HMA was found to bind inside the lumen of the channel, at both the C-terminal and the N-terminal openings, and, in contrast to amiloride, induced additional chemical shifts in ETM. Full length SARS-CoV E displayed channel activity when transiently expressed in human embryonic kidney 293 (HEK-293) cells in a whole-cell patch clamp set-up. This activity was significantly reduced by hexamethylene amiloride (HMA), but not by amiloride. The channel structure presented herein provides a possible rationale for inhibition, and a platform for future structure-based drug design of this potential pharmacological target., Author Summary Coronaviruses are viral pathogens that cause a variety of lethal diseases in birds and mammals, and common colds in humans. In 2003, however, an animal coronavirus was able to infect humans and produced severe acute respiratory syndrome (SARS), causing a near pandemic. Such events are likely to reoccur in the future, and new antiviral strategies are necessary. A small coronavirus protein called ‘envelope’ is important for pathogenesis, affecting the formation of the viral envelope and the distribution of the virus in the body. In vitro studies have shown that synthetic coronavirus envelope proteins have channel activity that in some cases has been inhibited by the drug hexamethylene amiloride, but not by amiloride. In the present paper, we have characterized the structure responsible for this channel activity. We have also determined the binding site of the drug hexamethylene amiloride in the channel, and shown that amiloride has only a mild effect on the NMR signals from the protein. The validity of these results is supported using mammalian cells expressing full length SARS-CoV E, where channel activity was inhibited by hexamethylene amiloride, but only mildly by amiloride. The structural model described for this channel provides a valuable insight into coronavirus envelope protein ion channel activity, and could serve as a platform for the development of novel anti-viral drugs.

We perform a large-scale study of intrinsically disordered regions in proteins and protein complexes using a non-redundant set of hundreds of different protein complexes. In accordance with the conventional view that folding and binding are coupled, in many of our cases the disorder-to-order transition occurs upon complex formation and can be localized to binding interfaces. Moreover, analysis of disorder in protein complexes depicts a significant fraction of intrinsically disordered regions, with up to one third of all residues being disordered. We find that the disorder in homodimers, especially in symmetrical homodimers, is significantly higher than in heterodimers and offer an explanation for this interesting phenomenon. We argue that the mechanisms of regulation of binding specificity through disordered regions in complexes can be as common as for unbound monomeric proteins. The fascinating diversity of roles of disordered regions in various biological processes and protein oligomeric forms shown in our study may be a subject of future endeavors in this area., Author Summary Traditionally, protein structure is believed to determine function. Recently, it was observed that many proteins contain regions without well-defined structure (intrinsically disordered regions), including a large fraction of eukaryotic proteins. Intrinsic disorder has been associated with particular functions including cell regulation; signaling; and protein, DNA, and ligand binding. Many proteins are intrinsically disordered in native form and fold upon binding, following the conventional paradigm. Accordingly, disorder in a protein may facilitate binding to multiple partners. However, in some cases disorder has also been found in the bound state. To gain clearer insight into the functional importance of disorder regions in protein complexes, we perform a large-scale analysis of disorder using protein structures in complex and in unbound forms. We show that disorder in protein complexes is rather common and pinpoint changes that occur upon protein binding at interaction interfaces. By illustrating a variety of functional roles for disorder in specific proteins, we emphasize the versatility and importance of this phenomenon.

We consider a recently suggested "equation of state" for natively folded proteins, and verify its validity for a set of about 5800 proteins. The equation is based on a fractal viewpoint of proteins, on a generalization of the Landau-Peierls instability, and on a marginal stability criterion. The latter allows for coexistence of stability and flexibility of proteins, which is required for their proper function. The equation of state relates the protein fractal dimension d(f), its spectral dimension d(s), and the number of amino acids N. Using structural data from the protein data bank (PDB) and the Gaussian network model (GNM), we compute d(f) and d(s) for the entire set and demonstrate that the equation of state is well obeyed. Addressing the fractal properties and making use of the equation of state may help to engineer biologically inspired catalysts.

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.php, This work was supported by the Ramon y Cajal program of the Spanish Science Ministry of Education and Science, Project ‘Centrosoma 3DBioinformatics’ of the program Consolider-Ingenio 2010 of the Spanish Ministry of Education and Science, Project BIO2005-0576 from the Spanish Ministry of Education and Science, Project 200520M157 from the Comunidad de Madrid, and Research Foundation ‘‘Ramon Areces’’.

Disordered proteins are highly abundant in regulatory processes such as transcription and cell-signaling. Different methods have been developed to predict protein disorder often focusing on different types of disordered regions. Here, we present MD, a novel META-Disorder prediction method that molds various sources of information predominantly obtained from orthogonal prediction methods, to significantly improve in performance over its constituents. In sustained cross-validation, MD not only outperforms its origins, but it also compares favorably to other state-of-the-art prediction methods in a variety of tests that we applied. Availability: http://www.rostlab.org/services/md/

Contains fulltext : 129351.pdf (Publisher’s version ) (Open Access) Background Chromosome structure, DNA metabolic processes and cell type identity can all be affected by changing the positions of nucleosomes along chromosomal DNA, a reaction that is catalysed by SNF2-type ATP-driven chromatin remodelers. Recently it was suggested that in vivo, more than 50% of the nucleosome positions can be predicted simply by DNA sequence, especially within promoter regions. This seemingly contrasts with remodeler induced nucleosome mobility. The ability of remodeling enzymes to mobilise nucleosomes over short DNA distances is well documented. However, the nucleosome translocation processivity along DNA remains elusive. Furthermore, it is unknown what determines the initial direction of movement and how new nucleosome positions are adopted. Methodology/Principal Findings We have used AFM imaging and high resolution PAGE of mononucleosomes on 600 and 2500 bp DNA molecules to analyze ATP-dependent nucleosome repositioning by native and recombinant SNF2-type enzymes. We report that the underlying DNA sequence can control the initial direction of translocation, translocation distance, as well as the new positions adopted by nucleosomes upon enzymatic mobilization. Within a strong nucleosomal positioning sequence both recombinant Drosophila Mi-2 (CHD-type) and native RSC from yeast (SWI/SNF-type) repositioned the nucleosome at 10 bp intervals, which are intrinsic to the positioning sequence. Furthermore, RSC-catalyzed nucleosome translocation was noticeably more efficient when beyond the influence of this sequence. Interestingly, under limiting ATP conditions RSC preferred to position the nucleosome with 20 bp intervals within the positioning sequence, suggesting that native RSC preferentially translocates nucleosomes with 15 to 25 bp DNA steps. Conclusions/Significance Nucleosome repositioning thus appears to be influenced by both remodeler intrinsic and DNA sequence specific properties that interplay to define ATPase-catalyzed repositioning. Here we propose a successive three-step framework consisting of initiation, translocation and release steps to describe SNF2-type enzyme mediated nucleosome translocation along DNA. This conceptual framework helps resolve the apparent paradox between the high abundance of ATP-dependent remodelers per nucleus and the relative success of sequence-based predictions of nucleosome positioning in vivo.

Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. While SDU effectively minimizes functions with funnel-shaped basins, its application to docking in the rotational and translational space SE(3) is not straightforward due to the geometry of that space. We introduce a strategy that uses separate independent variables for side-chain optimization, center-to-center distance of the two proteins, and five angular descriptors of the relative orientations of the molecules. The removal of the center-to-center distance turns out to vastly improve the efficiency of the search, because the five-dimensional space now exhibits a well-behaved energy surface suitable for underestimation. This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. Results for standard protein docking benchmarks establish that in this space the free energy landscape is a funnel in a reasonably broad neighborhood of the native state and that the SDU strategy can generate docking predictions with less than 5 Å ligand interface Cα root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods., Author Summary Protein–protein interactions play a central role in various aspects of the structural and functional organization of the cell, and their elucidation is crucial for a better understanding of processes such as metabolic control, signal transduction, and gene regulation. Genomewide proteomics studies, primarily yeast two-hybrid assays, will provide an increasing list of interacting proteins, but only a small fraction of the potential complexes will be amenable to direct experimental analysis. Thus, it is important to develop computational docking methods that can elucidate the details of specific interactions at the atomic level. Protein–protein docking generally starts with a rigid body search that generates a large number of docked conformations with good shape, electrostatic, and chemical complementarity. The conformations are clustered to obtain a manageable number of models, but the current methods are unable to select the most likely structure among these models. Here we describe a refinement algorithm that, applied to the individual clusters, improves the quality of the models. The better models are suitable for higher-accuracy energy calculation, thereby increasing the chances that near-native structures can be identified, and thus the refinement increases the reliability of the entire docking algorithm.

Positive selection for protein function can lead to multiple mutations within a small stretch of DNA, i.e., to a cluster of mutations. Recently, Wagner proposed a method to detect such mutation clusters. His method, however, did not take into account that residues with high solvent accessibility are inherently more variable than residues with low solvent accessibility. Here, we propose a new algorithm to detect clustered evolution. Our algorithm controls for different substitution probabilities at buried and exposed sites in the tertiary protein structure, and uses random permutations to calculate accurate P values for inferred clusters. We apply the algorithm to genomes of bacteria, fly, and mammals, and find several clusters of mutations in functionally important regions of proteins. Surprisingly, clustered evolution is a relatively rare phenomenon. Only between 2% and 10% of the genes we analyze contain a statistically significant mutation cluster. We also find that not controlling for solvent accessibility leads to an excess of clusters in terminal and solvent-exposed regions of proteins. Our algorithm provides a novel method to identify functionally relevant divergence between groups of species. Moreover, it could also be useful to detect artifacts in automatically assembled genomes.

Background: Eukaryotic cells seem unable to monitor replication completion during normal S phase, yet must ensure a reliable replication completion time. This is an acute problem in early Xenopus embryos since DNA replication origins are located and activated stochastically, leading to the random completion problem. DNA combing, kinetic modelling and other studies using Xenopus egg extracts have suggested that potential origins are much more abundant than actual initiation events and that the time-dependent rate of initiation, I(t), markedly increases through S phase to ensure the rapid completion of unreplicated gaps and a narrow distribution of completion times. However, the molecular mechanism that underlies this increase has remained obscure. Methodology/Principal Findings: Using both previous and novel DNA combing data we have confirmed that I(t) increases through S phase but have also established that it progressively decreases before the end of S phase. To explore plausible biochemical scenarios that might explain these features, we have performed comparisons between numerical simulations and DNA combing data. Several simple models were tested: i) recycling of a limiting replication fork component from completed replicons; ii) time-dependent increase in origin efficiency; iii) time-dependent increase in availability of an initially limiting factor, e.g. by nuclear import. None of these potential mechanisms could on its own account for the data. We propose a model that combines time-dependent changes in availability of a replication factor and a fork-density dependent affinity of this factor for potential origins. This novel model quantitatively and robustly accounted for the observed changes in initiation rate and fork density. Conclusions/Significance: This work provides a refined temporal profile of replication initiation rates and a robust, dynamic model that quantitatively explains replication origin usage during early embryonic S phase. These results have significant implications for the organisation of replication origins in higher eukaryotes.

A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, we explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. We analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1., Author Summary Neutralizing antibodies block infection of cells and thus are considered important to elicit with vaccines. A central problem in HIV-1 vaccine design is that HIV-1 is extremely variable and employs a number of strategies to avoid being recognized by antibodies. Despite this, a subset of infected individuals mounts potent, cross-reactive neutralizing antibody responses. We developed computational strategies for identifying correlations between mutational patterns in the HIV-1 envelope glycoproteins (gp120 and gp41) and neutralization phenotypes. We first applied these methods to define mutations that correlated with susceptibility to the potent neutralizing antibody b12, as a means to explore the appropriateness of applying our computational strategies to neutralizing antibody phenotypes within the well-understood context of b12-gp120 interactions. Signature sites of known importance were found. We then defined signatures in a panel of envelope glycoproteins sampled from HIV-1-infected individuals who made either potent or weak neutralizing antibody responses, with the hypothesis that common features of the envelope glycoproteins that elicit good antibodies in natural infection might be useful to incorporate as vaccine immunogens. Signature mutations associated with potent neutralizing antibody responses were concentrated in the coreceptor binding site of gp120 – a key region for HIV-1 entry into cells.

Arenaviridae synthesize viral mRNAs using short capped primers presumably acquired from cellular transcripts by a ‘cap-snatching’ mechanism. Here, we report the crystal structure and functional characterization of the N-terminal 196 residues (NL1) of the L protein from the prototypic arenavirus: lymphocytic choriomeningitis virus. The NL1 domain is able to bind and cleave RNA. The 2.13 Å resolution crystal structure of NL1 reveals a type II endonuclease α/β architecture similar to the N-terminal end of the influenza virus PA protein. Superimposition of both structures, mutagenesis and reverse genetics studies reveal a unique spatial arrangement of key active site residues related to the PD…(D/E)XK type II endonuclease signature sequence. We show that this endonuclease domain is conserved and active across the virus families Arenaviridae, Bunyaviridae and Orthomyxoviridae and propose that the arenavirus NL1 domain is the Arenaviridae cap-snatching endonuclease., Author Summary The Arenaviridae virus family includes several life-threatening human pathogens that cause meningitis or hemorrhagic fever. These RNA viruses replicate and transcribe their genome using an RNA synthesis machinery for which no structural data currently exist. They synthesize viral mRNAs using short capped primers presumably acquired from cellular transcripts by a ‘cap-snatching’ mechanism thought to involve the large L protein, which carries RNA-dependent RNA polymerase signature sequences. Here, we report the crystal structure and functional characterization of an isolated N-terminal domain of the L protein (NL1) from the prototypic arenavirus: lymphocytic choriomeningitis virus. The NL1 domain is able to bind and cleave RNA. The 2.13 Å resolution crystal structure of NL1 reveals a type II endonuclease α/β architecture similar to the N-terminal end of the influenza virus PA protein. Superimposition of both structures and mutagenesis studies reveal a unique spatial arrangement of key active site residues related to the PD…(D/E)XK type II endonuclease signature sequence. Reverse genetic studies show that mutation of active site residues selectively abolish transcription, not replication. We show that this endonuclease domain is conserved and active across the virus families: Arenaviridae, Bunyaviridae and Orthomyxoviridae and propose that the arenavirus NL1 domain is the Arenaviridae cap-snatching endonuclease.

PABPC1 (cytosolic poly(A)-binding protein 1) is an RNA-binding protein that binds to the poly(A) tail of mRNAs to promote translation and mRNA turnover. In addition to RNA-binding domains, PABPC1 contains a unique protein-protein interaction domain, MLLE (also known as PABC) that binds regulatory proteins and translation factors that contain a conserved 12 amino acid peptide motif termed PAM2. Eukaryotic Release Factor 3 (eRF3/GSPT1) contains two overlapping PAM2 sequences, which are required for its activity. Here, we determined the crystal structures of the MLLE domain from PABPC1 in complex with the two PAM2 regions of eRF3. The structures reveal a mechanism of cooperativity between the two PAM2 sites that increases the binding affinity but prevents the binding of more than one molecule of eRF3 to PABPC1. Relative to previous structures, the high-resolution crystal structures force a re-evaluation of the PAM2 motif and improve our understanding of the molecular basis of MLLE peptide recognition.

The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (, Author Summary Protein-protein interactions play a central role in life processes at the molecular level. The structural information on these interactions is essential for our understanding of these processes and our ability to design drugs to cure diseases. Limitations of experimental techniques to determine the structure of protein-protein complexes leave the vast majority of these complexes to be determined by computational modeling. The modeling is also important for revealing the mechanisms of the complex formation. The 3D modeling of protein complexes (protein docking) relies on the structure of the individual proteins for the prediction of their assembly. Thus the structural accuracy of the individual proteins, which often are models themselves, is critical for the docking. For the docking purposes, the accuracy of the binding sites is obviously essential, whereas the accuracy of the non-binding regions is less critical. In our study, we systematically analyze the accuracy of the binding sites in protein models produced by high-throughput techniques suitable for large-scale (e.g., genome-wide) studies. The results indicate that this accuracy is adequate for the low- to medium-resolution docking of a significant part of known protein-protein complexes.

BACKGROUND: The enzymatic hydrolysis of alpha-mannosides is catalyzed by glycoside hydrolases (GH), termed alpha-mannosidases. These enzymes are found in different GH sequence-based families. Considerable research has probed the role of higher eukaryotic "GH38" alpha-mannosides that play a key role in the modification and diversification of hybrid N-glycans; processes with strong cellular links to cancer and autoimmune disease. The most extensively studied of these enzymes is the Drosophila GH38 alpha-mannosidase II, which has been shown to be a retaining alpha-mannosidase that targets both alpha-1,3 and alpha-1,6 mannosyl linkages, an activity that enables the enzyme to process GlcNAc(Man)(5)(GlcNAc)(2) hybrid N-glycans to GlcNAc(Man)(3)(GlcNAc)(2). Far less well understood is the observation that many bacterial species, predominantly but not exclusively pathogens and symbionts, also possess putative GH38 alpha-mannosidases whose activity and specificity is unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that the Streptococcus pyogenes (M1 GAS SF370) GH38 enzyme (Spy1604; hereafter SpGH38) is an alpha-mannosidase with specificity for alpha-1,3 mannosidic linkages. The 3D X-ray structure of SpGH38, obtained in native form at 1.9 A resolution and in complex with the inhibitor swainsonine (K(i) 18 microM) at 2.6 A, reveals a canonical GH38 five-domain structure in which the catalytic "-1" subsite shows high similarity with the Drosophila enzyme, including the catalytic Zn(2+) ion. In contrast, the "leaving group" subsites of SpGH38 display considerable differences to the higher eukaryotic GH38s; features that contribute to their apparent specificity. CONCLUSIONS/SIGNIFICANCE: Although the in vivo function of this streptococcal GH38 alpha-mannosidase remains unknown, it is shown to be an alpha-mannosidase active on N-glycans. SpGH38 lies on an operon that also contains the GH84 hexosaminidase (Spy1600) and an additional putative glycosidase. The activity of SpGH38, together with its genomic context, strongly hints at a function in the degradation of host N- or possibly O-glycans. The absence of any classical signal peptide further suggests that SpGH38 may be intracellular, perhaps functioning in the subsequent degradation of extracellular host glycans following their initial digestion by secreted glycosidases.

Hydrogen constitutes nearly half of all atoms in proteins and their positions are essential for analyzing hydrogen-bonding interactions and refining atomic-level structures. However, most protein structures determined by experiments or computer prediction lack hydrogen coordinates. We present a new algorithm, HAAD, to predict the positions of hydrogen atoms based on the positions of heavy atoms. The algorithm is built on the basic rules of orbital hybridization followed by the optimization of steric repulsion and electrostatic interactions. We tested the algorithm using three independent data sets: ultra-high-resolution X-ray structures, structures determined by neutron diffraction, and NOE proton-proton distances. Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively. Furthermore, hydrogen atoms placed by HAAD have more matches with the NOE restraints and fewer clashes with heavy atoms. The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively. The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function. Both an executable and the source code of HAAD are freely available at http://zhang.bioinformatics.ku.edu/HAAD.

Background The replication of coronaviruses takes place on cytoplasmic double membrane vesicles (DMVs) originating in the endoplasmic reticulum (ER). Three trans-membrane non-structural proteins, nsp3, nsp4 and nsp6, are understood to be membrane anchors of the coronavirus replication complex. Nsp4 is localized to the ER membrane when expressed alone but is recruited into the replication complex in infected cells. It is revealed to contain four trans-membrane regions and its N- and C-termini are exposed to the cytosol. Methodology/Principal Findings We have determined the crystal structures of the C-terminal hydrophilic domain of nsp4 (nsp4C) from MHV strain A59 and a C425S site-directed mutant. The highly conserved 89 amino acid region from T408 to Q496 is shown to possess a new fold. The wild-type (WT) structure features two monomers linked by a Cys425-Cys425 disulfide bond in one asymmetric unit. The monomers are arranged with their N- and C-termini in opposite orientations to form an “open” conformation. Mutation of Cys425 to Ser did not affect the monomer structure, although the mutant dimer adopts strikingly different conformations by crystal packing, with the cross-linked C-termini and parallel N-termini of two monomers forming a “closed” conformation. The WT nsp4C exists as a dimer in solution and can dissociate easily into monomers in a reducing environment. Conclusions/Significance As nsp4C is exposed in the reducing cytosol, the monomer of nsp4C should be physiological. This structure may serve as a basis for further functional studies of nsp4.

DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Cα deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein., Author Summary Many essential biological activities require interactions between DNA and proteins. These proteins usually use certain amino acids, called DNA-binding sites, to recognize their specific DNA targets. To facilitate the search of its specific DNA targets, a DNA-binding protein often associates with nonspecific DNA and then diffuses along the DNA. Due to the weak interactions between nonspecific DNA and the protein, structural characterization of nonspecific DNA–protein complexes is experimentally challenging. This paper describes a computational modeling study on nonspecific DNA–protein complexes and comparative analysis with respect to specific DNA–protein complexes. The study found that the specific DNA-binding sites on a protein are typically favorable for nonspecific DNA and that nonspecific and specific DNA–protein interaction modes are quite similar. This similarity may reflect an important sampling step in the search for the specific DNA target sequence by a DNA-binding protein. On the basis of these observations, a novel method was proposed for predicting DNA-binding sites and binding modes of a DNA-binding protein without knowing its specific DNA target sequence. Ultimately, the combination of this method and protein structure prediction may lead the way to high throughput modeling of DNA–protein interactions.

Potassium (K+) ion channels switch between open and closed conformations. The nature of this important transition was revealed by comparing the X-ray crystal structures of the MthK channel from Methanobacterium thermoautotrophicum, obtained in its open conformation, and the KcsA channel from Streptomyces lividans, obtained in its closed conformation. We analyzed the dynamic characteristics and energetics of these homotetrameric structures in order to study the role of the intersubunit cooperativity in this transition. For this, elastic models and in silico alanine-scanning mutagenesis were used, respectively. Reassuringly, the calculations manifested motion from the open (closed) towards the closed (open) conformation. The calculations also revealed a network of dynamically and energetically coupled residues. Interestingly, the network suggests coupling between the selectivity filter and the gate, which are located at the two ends of the channel pore. Coupling between these two regions was not observed in calculations that were conducted with the monomer, which emphasizes the importance of the intersubunit interactions within the tetrameric structure for the cooperative gating behavior of the channel., Author Summary Potassium channels are found, in essence, in all kingdoms of life and all types of cells, and they are involved in key biological processes. For example, they are involved in the generation and propagation of nerve impulses in the synapse and neuron. Mutations in the proteins that form the channel may lead to diseases, such as multiple sclerosis, cystic fibrosis, and cardiac arrhythmia. Because of their involvement in these and other channelopathies, i.e., channel-related diseases, they are major drug targets. The channels switch between open (ion-conducting) and closed conformations. The structural characteristics of the transition between these conformations were studied using X-ray crystallography, spectroscopic, and single-molecule techniques, as well as computations. Here we used normal-mode analysis and in silico alanine-scanning mutagenesis to understand the molecular underpinnings of this transition. Our results suggest that the transition is mediated through a network of amino acids that are coupled to each other and connect the two ends of the pore. The importance of many of these residues was noted in previous empirical studies. The calculations also suggest that interactions between subunits of the homotetrameric structure of the channel contribute to the transition. The approach may also be useful to elucidate the mechanism of other transmembrane proteins in molecular details and to suggest key amino acids that are functionally important.

Trimeric autotransporter adhesins (TAAs) are a major class of proteins by which pathogenic proteobacteria adhere to their hosts. Prominent examples include Yersinia YadA, Haemophilus Hia and Hsf, Moraxella UspA1 and A2, and Neisseria NadA. TAAs also occur in symbiotic and environmental species and presumably represent a general solution to the problem of adhesion in proteobacteria. The general structure of TAAs follows a head-stalk-anchor architecture, where the heads are the primary mediators of attachment and autoagglutination. In the major adhesin of Bartonella henselae, BadA, the head consists of three domains, the N-terminal of which shows strong sequence similarity to the head of Yersinia YadA. The two other domains were not recognizably similar to any protein of known structure. We therefore determined their crystal structure to a resolution of 1.1 Å. Both domains are β-prisms, the N-terminal one formed by interleaved, five-stranded β-meanders parallel to the trimer axis and the C-terminal one by five-stranded β-meanders orthogonal to the axis. Despite the absence of statistically significant sequence similarity, the two domains are structurally similar to domains from Haemophilus Hia, albeit in permuted order. Thus, the BadA head appears to be a chimera of domains seen in two other TAAs, YadA and Hia, highlighting the combinatorial evolutionary strategy taken by pathogens., Author Summary The ability to adhere is an important aspect of the interaction between bacteria and their environment. Adhesion allows them to aggregate into colonies, form biofilms with other species, and colonize surfaces. Where the surfaces are provided by other organisms, adhesion can lead to a wide range of outcomes, from symbiosis to pathogenicity. In Proteobacteria, colonization of the host depends on a wide range of adhesive surface molecules, among which Trimeric Autotransporter Adhesins (TAAs) represent a major class. In electron micrographs, TAAs resemble lollipops projecting from the bacterial surface, and in all investigated cases, the adhesive properties reside in their heads. We have determined the head structure of BadA, the major adhesin of Bartonella henselae. This pathogen causes cat scratch disease in humans, but can lead to much more severe disease in immunosuppressed patients, e.g., during chemotherapy or after HIV infection. Surprisingly, domains previously seen in other TAA heads are combined in a novel assembly, illustrating how pathogens rearrange available building blocks to create new adhesive surface molecules.

High-resolution solid-state NMR spectroscopy can provide structural information of proteins that cannot be studied by X-ray crystallography or solution NMR spectroscopy. Here we demonstrate that it is possible to determine a protein structure by solid-state NMR to a resolution comparable to that by solution NMR. Using an iterative assignment and structure calculation protocol, a large number of distance restraints was extracted from (1)H/(1)H mixing experiments recorded on a single uniformly labeled sample under magic angle spinning conditions. The calculated structure has a coordinate precision of 0.6 A and 1.3 A for the backbone and side chain heavy atoms, respectively, and deviates from the structure observed in solution. The approach is expected to be applicable to larger systems enabling the determination of high-resolution structures of amyloid or membrane proteins.