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.

Background

Plasmids of Borrelia species are dynamic structures that contain a large number of repetitive genes, gene fragments, and gene fusions. In addition, the transposable element IS605/200 family, as well as degenerate forms of this IS element, are prevalent. In Helicobacter pylori , flanking regions of the IS605 transposase gene contain sequences that fold into identical small stem loops. These function in transposition at the single-stranded DNA level.

Methodology/Principal Findings

In work reported here, bioinformatics techniques were used to scan Borrelia plasmid genomes for IS605 transposable element specific stem loop sequences. Two variant stem loop motifs are found in the left and right flanking regions of the transposase gene. Both motifs appear to have dispersed in plasmid genomes and are found “free-standing” and phylogenetically conserved without the associated IS605 transposase gene or the adjacent flanking sequence. Importantly, IS605 specific stem loop sequences are also found at the 3′ ends of lipoprotein genes (PFam12 and PFam60), however the left and right sequences appear to develop their own evolutionary patterns. The lipoprotein gene-linked left stem loop sequences maintain the IS605 stem loop motif in orthologs but only at the RNA level. These show mutations whereby variants fold into phylogenetically conserved RNA-type stem loops that contain the wobble non-Watson-Crick G-U base-pairing. The right flanking sequence is associated with the family lipoprotein-1 genes. A comparison of homologs shows that the IS605 stem loop motif rapidly dissipates, but a more elaborate secondary structure appears to develop in its place.

Conclusions/Significance

Stem loop sequences specific to the transposable element IS605 are present in plasmid regions devoid of a transposase gene and significantly, are found linked to lipoprotein genes in Borrelia plasmids. These sequences are evolutionarily conserved and/or structurally developed in an RNA format. The findings show that IS605 stem loop sequences are multifaceted and are selectively conserved during evolution when the transposable element dissipates.

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, its spectral dimension, and the number of amino acids N . Using structural data from the protein data bank (PDB) and the Gaussian network model (GNM), we computeandfor 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 athttp://ub.cbm.uam.es/research/ProtNet.php

Background

Markers for longevity that reflect the health condition and predict healthy aging are extremely scarce. Such markers are, however, valuable in aging research. It has been shown previously that the N-glycosylation pattern of human immunoglobulin G (IgG) is age-dependent. Here we investigate whether N-linked glycans reflect early features of human longevity.

Methodology/Principal Findings

The Leiden Longevity Study (LLS) consists of nonagenarian sibling pairs, their offspring, and partners of the offspring serving as control. IgG subclass specific glycosylation patterns were obtained from 1967 participants in the LLS by MALDI-TOF-MS analysis of tryptic IgG Fc glycopeptides. Several regression strategies were applied to evaluate the association of IgG glycosylation with age, sex, and longevity. The degree of galactosylation of IgG decreased with increasing age. For the galactosylated glycoforms the incidence of bisecting GlcNAc increased as a function of age. Sex-related differences were observed at ages below 60 years. Compared to males, younger females had higher galactosylation, which decreased stronger with increasing age, resulting in similar galactosylation for both sexes from 60 onwards. In younger participants (<60 years of age), but not in the older age group (>60 years), decreased levels of non-galactosylated glycoforms containing a bisecting GlcNAc reflected early features of longevity.

Conclusions/Significance

We here describe IgG glycoforms associated with calendar age at all ages and the propensity for longevity before middle age. As modulation of IgG effector functions has been described for various IgG glycosylation features, a modulatory effect may be expected for the longevity marker described in this study.

Background

Functional similarity is challenging to identify when global sequence and structure similarity is low. Active-sites 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 FAST-NMR 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.

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 C _α root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods.

The first eukaryotic proline racemase (PRAC), isolated from the human Trypanosoma cruzi pathogen, is a validated therapeutic target against Chagas' disease. This essential enzyme is implicated in parasite life cycle and infectivity and its ability to trigger host B-cell nonspecific hypergammaglobulinemia contributes to parasite evasion and persistence. Using previously identified PRAC signatures and data mining we present the identification and characterization of a novel PRAC and five hydroxyproline epimerases (HyPRE) from pathogenic bacteria. Single-mutation of key HyPRE catalytic cysteine abrogates enzymatic activity supporting the presence of two reaction centers per homodimer. Furthermore, evidences are provided that Brucella abortus PrpA [for ‘proline racemase’ virulence factor A] and homologous proteins from two Brucella spp are bona fide HyPREs and not ‘one way’ directional PRACs as described elsewhere. Although the mechanisms of aminoacid racemization and epimerization are conserved between PRAC and HyPRE, our studies demonstrate that substrate accessibility and specificity partly rely on contraints imposed by aromatic or aliphatic residues distinctively belonging to the catalytic pockets. Analysis of PRAC and HyPRE sequences along with reaction center structural data disclose additional valuable elements for in silico discrimination of the enzymes. Furthermore, similarly to PRAC, the lymphocyte mitogenicity displayed by HyPREs is discussed in the context of bacterial metabolism and pathogenesis. Considering tissue specificity and tropism of infectious pathogens, it would not be surprising if upon infection PRAC and HyPRE play important roles in the regulation of the intracellular and extracellular amino acid pool profiting the microrganism with precursors and enzymatic pathways of the host.

Background

Members of the TGF-β superfamily are characterized by a highly promiscuous ligand-receptor interaction as is readily apparent from the numeral discrepancy of only seven type I and five type II receptors available for more than 40 ligands. Structural and functional studies have been used to address the question of how specific signals can be deduced from a limited number of receptor combinations and to unravel the molecular mechanisms underlying the protein-protein recognition that allow such limited specificity.

Principal Findings

In this study we have investigated how an antigen binding antibody fragment (Fab) raised against the extracellular domain of the BMP receptor type IA (BMPR-IA) recognizes the receptor's BMP-2 binding epitope and thereby neutralizes BMP-2 receptor activation. The crystal structure of the complex of the BMPR-IA ectodomain bound to the Fab AbD1556 revealed that the contact surface of BMPR-IA overlaps extensively with the contact surface for BMP-2 interaction. Although the structural epitopes of BMPR-IA to both binding partners coincides, the structures of BMPR-IA in the two complexes differ significantly. In contrast to the structural differences, alanine-scanning mutagenesis of BMPR-IA showed that the functional determinants for binding to the antibody and BMP-2 are almost identical.

Conclusions

Comparing the structures of BMPR-IA bound to BMP-2 or bound to the Fab AbD1556 with the structure of unbound BMPR-IA shows that binding of BMPR-IA to its interaction partners follows a selection fit mechanism, possibly indicating that the ligand promiscuity of BMPR-IA is inherently encoded by structural adaptability. The functional and structural analysis of the BMPR-IA binding antibody AbD1556 mimicking the BMP-2 binding epitope may thus pave the way for the design of low-molecular weight synthetic receptor binders/inhibitors.