On improving the selection of Thellier-type paleointensity data

The selection of paleointensity data is a challenging, but essential step for establishing data reliability. There is, however, no consensus as to how best to quantify paleointensity data and which data selection processes are most effective. To address these issues, we begin to lay the foundations for a more unified and theoretically justified approach to the selection of paleointensity data. We present a new compilation of standard definitions for paleointensity statistics to help remove ambiguities in their calculation. We also compile the largest‐to‐date data set of raw paleointensity data from historical locations and laboratory control experiments with which to test the effectiveness of commonly used sets of selection criteria. Although most currently used criteria are capable of increasing the proportion of accurate results accepted, criteria that are better at excluding inaccurate results tend to perform poorly at including accurate results and vice versa. In the extreme case, one widely used set of criteria, which is used by default in the ThellierTool software (v4.22), excludes so many accurate results that it is often statistically indistinguishable from randomly selecting data. We demonstrate that, when modified according to recent single domain paleointensity predictions, criteria sets that are no better than a random selector can produce statistically significant increases in the acceptance of accurate results and represent effective selection criteria. The use of such theoretically derived modifications places the selection of paleointensity data on a more justifiable theoretical foundation and we encourage the use of the modified criteria over their original forms

Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation

The Earth’s inner core grows by the freezing of liquid iron at its surface. The point in history at which this process initiated marks a step-change in the thermal evolution of the planet. Recent computational and experimental studies1,2,3,4,5 have presented radically differing estimates of the thermal conductivity of the Earth’s core, resulting in estimates of the timing of inner-core nucleation ranging from less than half a billion to nearly two billion years ago. Recent inner-core nucleation (high thermal conductivity) requires high outer-core temperatures in the early Earth that complicate models of thermal evolution. The nucleation of the core leads to a different convective regime6 and potentially different magnetic field structures that produce an observable signal in the palaeomagnetic record and allow the date of inner-core nucleation to be estimated directly. Previous studies searching for this signature have been hampered by the paucity of palaeomagnetic intensity measurements, by the lack of an effective means of assessing their reliability, and by shorter-timescale geomagnetic variations. Here we examine results from an expanded Precambrian database of palaeomagnetic intensity measurements7 selected using a new set of reliability criteria8. Our analysis provides intensity-based support for the dominant dipolarity of the time-averaged Precambrian field, a crucial requirement for palaeomagnetic reconstructions of continents. We also present firm evidence for the existence of very long-term variations in geomagnetic strength. The most prominent and robust transition in the record is an increase in both average field strength and variability that is observed to occur between a billion and 1.5 billion years ago. This observation is most readily explained by the nucleation of the inner core occurring during this interval9; the timing would tend to favour a modest value of core thermal conductivity and supports a simple thermal evolution model for the Earth

Advancing Precambrian palaeomagnetism with the PALEOMAGIA and PINT(_QPI) databases.

State-of-the-art measurements of the direction and intensity of Earth's ancient magnetic field have made important contributions to our understanding of the geology and palaeogeography of Precambrian Earth. The PALEOMAGIA and PINT(QPI) databases provide thorough public collections of important palaeomagnetic data of this kind. They comprise more than 4,100 observations in total and have been essential in supporting our international collaborative efforts to understand Earth's magnetic history on a timescale far longer than that of the present Phanerozoic Eon. Here, we provide an overview of the technical structure and applications of both databases, paying particular attention to recent improvements and discoveries

Актуальні проблеми розвитку виноградства та виноробства

В статті розглянуто сучасні тенденції та проблеми розвитку виноградарства та виноробства України. Надано рекомендації щодо пріоритетних напрямків розвитку виноробних підприємств.The modern tendencies and development problems of Ukraine viticulture and winemaking industry are considered in the article. The regards priority areas recommendations of winemaking enterprises development are given

Deciphering the folding kinetics of transmembrane helical proteins

Nearly a quarter of genomic sequences and almost half of all receptors that are likely to be targets for drug design are integral membrane proteins. Understanding the detailed mechanisms of the folding of membrane proteins is a largely unsolved, key problem in structural biology. Here, we introduce a general model and use computer simulations to study the equilibrium properties and the folding kinetics of a $C_{\alpha}$-based two helix bundle fragment (comprised of 66 amino-acids) of Bacteriorhodopsin. Various intermediates are identified and their free energy are calculated toghether with the free energy barrier between them. In 40% of folding trajectories, the folding rate is considerably increased by the presence of non-obligatory intermediates acting as traps. In all cases, a substantial portion of the helices is rapidly formed. This initial stage is followed by a long period of consolidation of the helices accompanied by their correct packing within the membrane. Our results provide the framework for understanding the variety of folding pathways of helical transmembrane proteins

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell

Carcinoembryonic Antigen Gene Family

The carcinoembryonic antigen (CEA) gene family belongs to the immunoglobulin supergene family and can be divided into two main subgroups based on sequence comparisons. In humans it is clustered on the long arm of chromosome 19 and consists of approximately 20 genes. The CEA subgroup genes code for CEA and its classical crossreacting antigens, which are mainly membrane-bound, whereas the other subgroup genes encode the pregnancy-specific glycoproteins (PSG), which are secreted. Splice variants of individual genes and differential post-translational modifications of the resulting proteins, e.g., by glycosylation, indicate a high complexity in the number of putative CEA-related molecules. So far, only a limited number of CEA-related antigens in humans have been unequivocally assigned to a specific gene. Rodent CEA-related genes reveal a high sequence divergence and, in part, a completely different domain organization than the human CEA gene family, making it difficult to determine individual gene counterparts. However, rodent CEA-related genes can be assigned to human subgroups based on similarity of expression patterns, which is characteristic for the subgroups. Various functions have been determined for members of the CEA subgroup in vitro, including cell adhesion, bacterial binding, an accessory role for collagen binding or ecto-ATPases activity. Based on all that is known so far on its biology, the clinical outlook for the CEA family has been reassessed

Waterdock 2.0: Water placement prediction for Holo-structures with a pymol plugin.

Water is often found to mediate interactions between a ligand and a protein. It can play a significant role in orientating the ligand within a binding pocket and contribute to the free energy of binding. It would thus be extremely useful to be able to accurately predict the position and orientation of water molecules within a binding pocket. Recently, we developed the WaterDock protocol that was able to predict 97% of the water molecules in a test set. However, this approach generated false positives at a rate of over 20% in most cases and whilst this might be acceptable for some applications, in high throughput scenarios this is not desirable. Here we tackle this problem via the inclusion of knowledge regarding the solvation structure of ligand functional groups. We call this new protocol WaterDock2 and demonstrate that this protocol maintains a similar true positive rate to the original implementation but is capable of reducing the false-positive rate by over 50%. To improve the usability of the method, we have also developed a plugin for the popular graphics program PyMOL. The plugin also contains an implementation of the original WaterDock.GAR is supported by the Memorial Sloan Kettering Cancer Center, NIH grant P30 CA008748

Accurate calculation of the absolute free energy of binding for drug molecules

Accurate prediction of binding affinities has been a central goal of computational chemistry for decades, yet remains elusive. Despite good progress, the required accuracy for use in a drug-discovery context has not been consistently achieved for drug-like molecules. Here, we perform absolute free energy calculations based on a thermodynamic cycle for a set of diverse inhibitors binding to bromodomain-containing protein 4 (BRD4) and demonstrate that a mean absolute error of 0.6 kcal mol−1 can be achieved. We also show a similar level of accuracy (1.0 kcal mol−1) can be achieved in pseudo prospective approach. Bromodomains are epigenetic mark readers that recognize acetylation motifs and regulate gene transcription, and are currently being investigated as therapeutic targets for cancer and inflammation. The unprecedented accuracy offers the exciting prospect that the binding free energy of drug-like compounds can be predicted for pharmacologically relevant targets