14 research outputs found

    A flare in the optical spotted in the changing-look Seyfert NGC 3516

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    Context. We present observations from the short-term intensive optical campaign (from September 2019 to January 2020) of the changing-look Seyfert NGC 3516. This active galactic nucleus is known to have strong optical variability and has changed its type in the past. It has been in the low-activity state in the optical since 2013, with some rebrightening from the end of 2015 to the beginning of 2016, after which it remained dormant.Aims. We aim to study the photometric and spectral variability of NGC 3516 from the new observations in U- and B-bands and examine the profiles of the optical broad emission lines in order to demonstrate that this object may be entering a new state of activity.Methods. NGC 3516 has been monitored intensively for the past 4 months with an automated telescope in U and B filters, enabling accurate photometry of 0.01 precision. Spectral observations were triggered when an increase in brightness was spotted. We support our analysis of past-episodes of violent variability with the UV and X-ray long-term light curves constructed from the archival Swift/UVOT and Swift/XRT data.Results. An increase of the photometric magnitude is seen in both U and B filters to a maximum amplitude of 0.25 mag and 0.11 mag, respectively. During the flare, we observe stronger forbidden high-ionization iron lines ([FeVII] and [FeX]) than reported before, as well as the complex broad H alpha and H beta lines. This is especially seen in H alpha, which appears to be double-peaked. It seems that a very broad component of similar to 10 000 km s(-1) in width in the Balmer lines is appearing. The trends in the optical, UV, and X-ray light curves are similar, with the amplitudes of variability being significantly larger in the case of UV and X-ray bands.Conclusions. The increase of the continuum emission, the variability of the coronal lines, and the very broad component in the Balmer lines may indicate that the AGN of NGC 3516 is finally leaving the low-activity state in which it has been for the last similar to 3 years.</div

    Insertions and the emergence of novel protein structure: a structure-based phylogenetic study of insertions

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    <p>Abstract</p> <p>Background</p> <p>In protein evolution, the mechanism of the emergence of novel protein domain is still an open question. The incremental growth of protein variable regions, which was produced by stochastic insertions, has the potential to generate large and complex sub-structures. In this study, a deterministic methodology is proposed to reconstruct phylogenies from protein structures, and to infer insertion events in protein evolution. The analysis was performed on a broad range of SCOP domain families.</p> <p>Results</p> <p>Phylogenies were reconstructed from protein 3D structural data. The phylogenetic trees were used to infer ancestral structures with a consensus method. From these ancestral reconstructions, 42.7% of the observed insertions are nested insertions, which locate in previous insert regions. The average size of inserts tends to increase with the insert rank or total number of insertions in the variable regions. We found that the structures of some nested inserts show complex or even domain-like fold patterns with helices, strands and loops. Furthermore, a basal level of structural innovation was found in inserts which displayed a significant structural similarity exclusively to themselves. The β-Lactamase/D-ala carboxypeptidase domain family is provided as an example to illustrate the inference of insertion events, and how the incremental growth of a variable region is capable to generate novel structural patterns.</p> <p>Conclusion</p> <p>Using 3D data, we proposed a method to reconstruct phylogenies. We applied the method to reconstruct the sequences of insertion events leading to the emergence of potentially novel structural elements within existing protein domains. The results suggest that structural innovation is possible via the stochastic process of insertions and rapid evolution within variable regions where inserts tend to be nested. We also demonstrate that the structure-based phylogeny enables the study of new questions relating to the evolution of protein domain and biological function.</p

    FlexOracle: predicting flexible hinges by identification of stable domains

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    <p>Abstract</p> <p>Background</p> <p>Protein motions play an essential role in catalysis and protein-ligand interactions, but are difficult to observe directly. A substantial fraction of protein motions involve hinge bending. For these proteins, the accurate identification of flexible hinges connecting rigid domains would provide significant insight into motion. Programs such as GNM and FIRST have made global flexibility predictions available at low computational cost, but are not designed specifically for finding hinge points.</p> <p>Results</p> <p>Here we present the novel FlexOracle hinge prediction approach based on the ideas that energetic interactions are stronger <it>within </it>structural domains than <it>between </it>them, and that fragments generated by cleaving the protein at the hinge site are independently stable. We implement this as a tool within the Database of Macromolecular Motions, MolMovDB.org. For a given structure, we generate pairs of fragments based on scanning all possible cleavage points on the protein chain, compute the energy of the fragments compared with the undivided protein, and predict hinges where this quantity is minimal. We present three specific implementations of this approach. In the first, we consider only pairs of fragments generated by cutting at a <it>single </it>location on the protein chain and then use a standard molecular mechanics force field to calculate the enthalpies of the two fragments. In the second, we generate fragments in the same way but instead compute their free energies using a knowledge based force field. In the third, we generate fragment pairs by cutting at <it>two </it>points on the protein chain and then calculate their free energies.</p> <p>Conclusion</p> <p>Quantitative results demonstrate our method's ability to predict known hinges from the Database of Macromolecular Motions.</p

    Cross-Over between Discrete and Continuous Protein Structure Space: Insights into Automatic Classification and Networks of Protein Structures

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    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.ph

    Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

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    Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.
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