D2P2: database of disordered protein predictions

We present the Database of Disordered Protein Prediction (D2P2), available at http://d2p2.pro (including website source code). A battery of disorder predictors and their variants, VL-XT, VSL2b, PrDOS, PV2, Espritz and IUPred, were run on all protein sequences from 1765 complete proteomes (to be updated as more genomes are completed). Integrated with these results are all of the predicted (mostly structured) SCOP domains using the SUPERFAMILY predictor. These disorder/structure annotations together enable comparison of the disorder predictors with each other and examination of the overlap between disordered predictions and SCOP domains on a large scale. D2P2 will increase our understanding of the interplay between disorder and structure, the genomic distribution of disorder, and its evolutionary history. The parsed data are made available in a unified format for download as flat files or SQL tables either by genome, by predictor, or for the complete set. An interactive website provides a graphical view of each protein annotated with the SCOP domains and disordered regions from all predictors overlaid (or shown as a consensus). There are statistics and tools for browsing and comparing genomes and their disorder within the context of their position on the tree of life. © The Author(s) 2012. Published by Oxford University Press

Manganese-catalysed transfer hydrogenation of esters

Authors thank the University of St Andrews, and the EPSRC Centre for Doctoral Training in Critical Resource Catalysis (CRITICAT) for financial support [Ph.D. studentship to CO; Grant code: EP/L016419/1].Manganese catalysed ester reduction using ethanol as reductant in place of dihydrogen is reported. High yields can be achieved for a range of substrates using 1 mol% of a Mn(I) catalyst, with an alkoxide promotor. The catalyst is derived from a tridentate P,N,N ligand.Publisher PDFPeer reviewe

Real-time Semiparametric Regression via Sequential Monte Carlo

We develop and describe online algorithms for performing real-time semiparametric regression analyses. Earlier work on this topic is in Luts, Broderick & Wand (J. Comput. Graph. Statist., 2014) where online mean field variational Bayes was employed. In this article we instead develop sequential Monte Carlo approaches to circumvent well-known inaccuracies inherent in variational approaches. Even though sequential Monte Carlo is not as fast as online mean field variational Bayes, it can be a viable alternative for applications where the data rate is not overly high. For Gaussian response semiparametric regression models our new algorithms share the online mean field variational Bayes property of only requiring updating and storage of sufficient statistics quantities of streaming data. In the non-Gaussian case accurate real-time semiparametric regression requires the full data to be kept in storage. The new algorithms allow for new options concerning accuracy/speed trade-offs for real-time semiparametric regression

Manganese-catalyzed hydrogenation of amides and polyurethanes : is catalyst inhibition an additional barrier to efficient hydrogenation of amides and their derivatives?

J.L. and A.K. thank the UKRI Future Leaders Fellowship (MR/W007460/1). The authors would like to thank the University of St. Andrews and the EPSRC Centre for Doctoral Training in Critical Resource Catalysis (CRITICAT) for financial support [Ph.D. studentship to C.L.O.; Grant Code: EP/L016419/1].The hydrogenation of amides and other less electrophilic carbonyl derivatives with an N–C═O functionality requires significant improvements in scope and catalytic activity to be a genuinely useful reaction in industry. Here, we report the results of a study that examined whether such reactions are further disadvantaged by nitrogen-containing compounds such as aliphatic amines acting as inhibitors on the catalysts. In this case, an enantiomerically pure manganese catalyst previously established to be efficient in the hydrogenation of ketones, N-aryl-imines, and esters was used as a prototype of a manganese catalyst. This was accomplished by doping a model ester hydrogenation with various nitrogen-containing compounds and monitoring progress. Following from this, a protocol for the catalytic hydrogenation of amides and polyurethanes is described, including the catalytic hydrogenation of an axially chiral amide that resulted in low levels of kinetic resolution. The hypothesis of nitrogen-containing compounds acting as an inhibitor in the catalytic hydrogenation process has also been rationalized by using spectroscopy (high-pressure infrared (IR), nuclear magnetic resonance (NMR)) and mass spectrometry studies.Publisher PDFPeer reviewe

Evaluating snow microbial assemblages

Psychrophiles are organisms that grow optimally below 20C (1). The US Great Basin is home to many mountain peaks with an abundance of alpine snow environments perfect for psychrophilic habitation. We analyzed samples from three different locations, Wheeler Peak, Pacific Crest Trail, and Mount Conness, characterizing and comparing the psychrophilic communities at varying depth intervals in the snow. Polymerase chain reaction (PCR) and denaturing gradient gel electrophoresis (DGGE) showed no notable difference in community structure with depth, but there was a distinct difference when comparing different snow environments (i.e. shaded vs. full sun exposure). The chlorophyll concentration decreased as the depth of the snow increased. By creating a clone library and utilizing DNA sequencing technology we were able to obtain 16S and 18S rRNA gene sequences from samples collected from Mount Conness, which allowed us to identify microbes living in the ecosystem. This information enabled us to produce bacterial and eukaryl phylogenetic trees, giving us a clear look into the diversity of this psychrophilic community. Out of seventy bacterial results there were fifty‐three ‐Proteobacteria, thirteen Sphingobacteria, and only three Actinobacteria, with one unclassified bacteria as well. These results will guide us in our future plans for experimentation

Anomaly Detection for Symbolic Representations

A fully autonomous agent recognizes new problems, explains what causes such problems, and generates its own goals to solve these problems. Our approach to this goal-driven model of autonomy uses a methodology called the Note-Assess-Guide procedure. It instantiates a monitoring process in which an agent notes an anomaly in the world, assesses the nature and cause of that anomaly, and guides appropriate modifications to behavior. This report describes a novel approach to the note phase of that procedure. A-distance, a sliding-window statistical distance metric, is applied to numerical vector representations of intermediate states from plans generated for two symbolic domains. Using these representations, the metric is able to detect anomalous world states caused by restricting the actions available to the planner

Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer

Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer

The SUPERFAMILY 2.0 database:a significant proteome update and a new webserver

Here, we present a major update to the SUPERFAMILY database and the webserver. We describe the addition of new SUPERFAMILY 2.0 profile HMM library containing a total of 27 623 HMMs. The database now includes Superfamily domain annotations for millions of protein sequences taken from the Universal Protein Recourse Knowledgebase (UniProtKB) and the National Center for Biotechnology Information (NCBI). This addition constitutes about 51 and 45 million distinct protein sequences obtained from UniProtKB and NCBI respectively. Currently, the database contains annotations for 63 244 and 102 151 complete genomes taken from UniProtKB and NCBI respectively. The current sequence collection and genome update is the biggest so far in the history of SUPERFAMILY updates. In order to the deal with the massive wealth of information, here we introduce a new SUPERFAMILY 2.0 webserver (http://supfam.org). Currently, the webserver mainly focuses on the search, retrieval and display of Superfamily annotation for the entire sequence and genome collection in the database

A Reemerging Bright Soft X-Ray State of the Changing-look Active Galactic Nucleus 1ES 1927+654:A Multiwavelength View

1ES1927+654 is a nearby active galactic nucleus (AGN) that has shown an enigmatic outburst in optical/UV followed by X-rays, exhibiting strange variability patterns at timescales of months to years. Here we report the unusual X-ray, UV, and radio variability of the source in its postflare state (2022 January–2023 May). First, we detect an increase in the soft X-ray (0.3–2 keV) flux from 2022 May to 2023 May by almost a factor of 5, which we call the bright soft state. The hard X-ray 2–10 keV flux increased by a factor of 2, while the UV flux density did not show any significant changes (≤30%) in the same period. The integrated energy pumped into the soft and hard X-rays during this period of 11 months is ∼3.57 × 10 ^50 erg and 5.9 × 10 ^49 erg, respectively. From the energetics, it is evident that whatever is producing the soft excess (SE) is pumping out more energy than either the UV or hard X-ray source. Since the energy source presumably is ultimately the accretion of matter onto the supermassive black hole, the SE-emitting region must be receiving the majority of this energy. In addition, the source does not follow the typical disk–corona relation found in AGNs, neither in the initial flare (from 2017 to 2019) nor in the current bright soft state (2022–2023). We found that the core (<1 pc) radio emission at 5 GHz gradually increased until 2022 March, but showed a dip in 2022 August. The Güdel–Benz relation ( L _radio / L _X-ray ∼ 10 ^−5 ), however, is still within the expected range for radio-quiet AGNs, and further follow-up radio observations are currently being undertaken