A Search for leptophilic Z_(l) boson at future linear colliders

We study the possible dynamics associated with leptonic charge in future linear colliders. Leptophilic massive vector boson, Z_(l), have been investigated through the process e^(+)e^(-) -> mu^(+)mu^(-). We have shown that ILC and CLIC will give opportunity to observe Z_(l) with masses up to the center of mass energy if the corresponding coupling constant g_(l) exceeds 10^(-3).Comment: 12 pages, 10 figure

Ecological and conceptual consequences of Arctic pollution

This is the final version. Available on open access from Wiley via the DOI in this recordAlthough the effect of pollution on forest health and decline received much attention in the 1980s, it has not been considered to explain the ‘Divergence Problem’ in dendroclimatology; a decoupling of tree growth from rising air temperatures since the 1970s. Here we use physical and biogeochemical measurements of hundreds of living and dead conifers to reconstruct the impact of heavy industrialisation around Norilsk in northern Siberia. Moreover, we develop a forward model with surface irradiance forcing to quantify long‐distance effects of anthropogenic emissions on the functioning and productivity of Siberia’s taiga. Downwind from the world’s most polluted Arctic region, tree mortality rates of up to 100% have destroyed 24,000 km2 boreal forest since the 1960s, coincident with dramatic increases in atmospheric sulphur, copper, and nickel concentrations. In addition to regional ecosystem devastation, we demonstrate how ‘Arctic Dimming’ can explain the circumpolar ‘Divergence Problem’, and discuss implications on the terrestrial carbon cycle.Forest ServiceMinistry of Science and Higher EducationRussian Science Foundatio

An AP Endonuclease 1–DNA Polymerase β Complex: Theoretical Prediction of Interacting Surfaces

Abasic (AP) sites in DNA arise through both endogenous and exogenous mechanisms. Since AP sites can prevent replication and transcription, the cell contains systems for their identification and repair. AP endonuclease (APEX1) cleaves the phosphodiester backbone 5′ to the AP site. The cleavage, a key step in the base excision repair pathway, is followed by nucleotide insertion and removal of the downstream deoxyribose moiety, performed most often by DNA polymerase beta (pol-β). While yeast two-hybrid studies and electrophoretic mobility shift assays provide evidence for interaction of APEX1 and pol-β, the specifics remain obscure. We describe a theoretical study designed to predict detailed interacting surfaces between APEX1 and pol-β based on published co-crystal structures of each enzyme bound to DNA. Several potentially interacting complexes were identified by sliding the protein molecules along DNA: two with pol-β located downstream of APEX1 (3′ to the damaged site) and three with pol-β located upstream of APEX1 (5′ to the damaged site). Molecular dynamics (MD) simulations, ensuring geometrical complementarity of interfaces, enabled us to predict interacting residues and calculate binding energies, which in two cases were sufficient (∼−10.0 kcal/mol) to form a stable complex and in one case a weakly interacting complex. Analysis of interface behavior during MD simulation and visual inspection of interfaces allowed us to conclude that complexes with pol-β at the 3′-side of APEX1 are those most likely to occur in vivo. Additional multiple sequence analyses of APEX1 and pol-β in related organisms identified a set of correlated mutations of specific residues at the predicted interfaces. Based on these results, we propose that pol-β in the open or closed conformation interacts and makes a stable interface with APEX1 bound to a cleaved abasic site on the 3′ side. The method described here can be used for analysis in any DNA-metabolizing pathway where weak interactions are the principal mode of cross-talk among participants and co-crystal structures of the individual components are available

A Score of the Ability of a Three-Dimensional Protein Model to Retrieve Its Own Sequence as a Quantitative Measure of Its Quality and Appropriateness

BACKGROUND: Despite the remarkable progress of bioinformatics, how the primary structure of a protein leads to a three-dimensional fold, and in turn determines its function remains an elusive question. Alignments of sequences with known function can be used to identify proteins with the same or similar function with high success. However, identification of function-related and structure-related amino acid positions is only possible after a detailed study of every protein. Folding pattern diversity seems to be much narrower than sequence diversity, and the amino acid sequences of natural proteins have evolved under a selective pressure comprising structural and functional requirements acting in parallel. PRINCIPAL FINDINGS: The approach described in this work begins by generating a large number of amino acid sequences using ROSETTA [Dantas G et al. (2003) J Mol Biol 332:449-460], a program with notable robustness in the assignment of amino acids to a known three-dimensional structure. The resulting sequence-sets showed no conservation of amino acids at active sites, or protein-protein interfaces. Hidden Markov models built from the resulting sequence sets were used to search sequence databases. Surprisingly, the models retrieved from the database sequences belonged to proteins with the same or a very similar function. Given an appropriate cutoff, the rate of false positives was zero. According to our results, this protocol, here referred to as Rd.HMM, detects fine structural details on the folding patterns, that seem to be tightly linked to the fitness of a structural framework for a specific biological function. CONCLUSION: Because the sequence of the native protein used to create the Rd.HMM model was always amongst the top hits, the procedure is a reliable tool to score, very accurately, the quality and appropriateness of computer-modeled 3D-structures, without the need for spectroscopy data. However, Rd.HMM is very sensitive to the conformational features of the models' backbone

A Mathematical Framework for Protein Structure Comparison

Comparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set

A novel method to compare protein structures using local descriptors

<p>Abstract</p> <p>Background</p> <p>Protein structure comparison is one of the most widely performed tasks in bioinformatics. However, currently used methods have problems with the so-called "difficult similarities", including considerable shifts and distortions of structure, sequential swaps and circular permutations. There is a demand for efficient and automated systems capable of overcoming these difficulties, which may lead to the discovery of previously unknown structural relationships.</p> <p>Results</p> <p>We present a novel method for protein structure comparison based on the formalism of local descriptors of protein structure - DEscriptor Defined Alignment (DEDAL). Local similarities identified by pairs of similar descriptors are extended into global structural alignments. We demonstrate the method's capability by aligning structures in difficult benchmark sets: curated alignments in the SISYPHUS database, as well as SISY and RIPC sets, including non-sequential and non-rigid-body alignments. On the most difficult RIPC set of sequence alignment pairs the method achieves an accuracy of 77% (the second best method tested achieves 60% accuracy).</p> <p>Conclusions</p> <p>DEDAL is fast enough to be used in whole proteome applications, and by lowering the threshold of detectable structure similarity it may shed additional light on molecular evolution processes. It is well suited to improving automatic classification of structure domains, helping analyze protein fold space, or to improving protein classification schemes. DEDAL is available online at <url>http://bioexploratorium.pl/EP/DEDAL</url>.</p

Athlome Project Consortium: a concerted effort to discover genomic and other "omic" markers of athletic performance.

Despite numerous attempts to discover genetic variants associated with elite athletic performance, injury predisposition, and elite/world-class athletic status, there has been limited progress to date. Past reliance on candidate gene studies predominantly focusing on genotyping a limited number of single nucleotide polymorphisms or the insertion/deletion variants in small, often heterogeneous cohorts (i.e., made up of athletes of quite different sport specialties) have not generated the kind of results that could offer solid opportunities to bridge the gap between basic research in exercise sciences and deliverables in biomedicine. A retrospective view of genetic association studies with complex disease traits indicates that transition to hypothesis-free genome-wide approaches will be more fruitful. In studies of complex disease, it is well recognized that the magnitude of genetic association is often smaller than initially anticipated, and, as such, large sample sizes are required to identify the gene effects robustly. A symposium was held in Athens and on the Greek island of Santorini from 14-17 May 2015 to review the main findings in exercise genetics and genomics and to explore promising trends and possibilities. The symposium also offered a forum for the development of a position stand (the Santorini Declaration). Among the participants, many were involved in ongoing collaborative studies (e.g., ELITE, GAMES, Gene SMART, GENESIS, and POWERGENE). A consensus emerged among participants that it would be advantageous to bring together all current studies and those recently launched into one new large collaborative initiative, which was subsequently named the Athlome Project Consortium

Western Black Sea currents by the ship measurements and satellite imagery

Observations based on CTD, ADCP and satellite infrared measurements were carried out in the spring seasons of 1993 and 1994 in the framework of CoMSBlack and NATO TU-Black Sea international programs, to describe the western Black Sea circulation. In this paper, we present comparisons of satellite images with the measured currents and geostrophic flow fields in the upper ocean, with a purpose of describing the mese-scale circulation features. Some statistical and energetic parameters were also analyzed to compare circulation patterns for these two years