1,471 research outputs found

    Strong covalent bonding between two graphene layers

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    We show that two graphene layers stacked directly on top of each other (AA stacking) form strong chemical bonds when the distance between planes is 0.156 nm. Simultaneously, C-C in-plane bonds are considerably weakened from partial double-bond (0.141 nm) to single bond (0.154 nm). This polymorphic form of graphene bilayer is meta-stable w.r.t. the one bound by van der Waals forces at a larger separation (0.335 nm) with an activation energy of 0.16 eV/cell. Similarly to the structure found in hexaprismane, C forms four single bonds in a geometry mixing 90^{0} and 120^{0} angles. Intermediate separations between layers can be stabilized under external anisotropic stresses showing a rich electronic structure changing from semimetal at van der Waals distance, to metal when compressed, to wide gap semiconductor at the meta-stable minimum.Comment: tar gzip latex 4 pages 4 figure

    Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment

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    In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment

    Prediction failure blocks the use of local semantic context

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    Before accumulation of recent experimental evidence, prediction was thought to be too prone to failure and thus too costly for language comprehension. Although prediction is now widely assumed, questions about the costs of prediction failure and recovery still remain. An event-related potentials study using highly constraining Italian sentence contexts addressed these questions. It manipulated how predictive local contexts were for target nouns after cueing comprehenders to the status of global sentential predictions with article gender congruence. Predictive local contexts reduced target noun N400 amplitude when the preceding article’s gender was congruent with global predictions, but not when gender was incongruent. This suggests that prediction failure impeded the facilitative use of local context for target nouns. Predictive local contexts following gender incongruence also elicited a broader late frontal positivity on target nouns, suggesting further recovery difficulties. Prediction failures, therefore, are not cost-free, and recovery from these failures requires further consideratio

    Angular Forces Around Transition Metals in Biomolecules

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    Quantum-mechanical analysis based on an exact sum rule is used to extract an semiclassical angle-dependent energy function for transition metal ions in biomolecules. The angular dependence is simple but different from existing classical potentials. Comparison of predicted energies with a computer-generated database shows that the semiclassical energy function is remarkably accurate, and that its angular dependence is optimal.Comment: Tex file plus 4 postscript figure

    Therapeutic target-site variability in α1-antitrypsin characterized at high resolution

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    The intrinsic propensity of [alpha]1-antitrypsin to undergo conformational transitions from its metastable native state to hyperstable forms provides a motive force for its antiprotease function. However, aberrant conformational change can also occur via an intermolecular linkage that results in polymerization. This has both loss-of-function and gain-of-function effects that lead to deficiency of the protein in human circulation, emphysema and hepatic cirrhosis. One of the most promising therapeutic strategies being developed to treat this disease targets small molecules to an allosteric site in the [alpha]1-antitrypsin molecule. Partial filling of this site impedes polymerization without abolishing function. Drug development can be improved by optimizing data on the structure and dynamics of this site. A new 1.8 Å resolution structure of [alpha]1-antitrypsin demonstrates structural variability within this site, with associated fluctuations in its upper and lower entrance grooves and ligand-binding characteristics around the innermost stable enclosed hydrophobic recess. These data will allow a broader selection of chemotypes and derivatives to be tested in silico and in vitro when screening and developing compounds to modulate conformational change to block the pathological mechanism while preserving function

    Introduction to protein folding for physicists

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    The prediction of the three-dimensional native structure of proteins from the knowledge of their amino acid sequence, known as the protein folding problem, is one of the most important yet unsolved issues of modern science. Since the conformational behaviour of flexible molecules is nothing more than a complex physical problem, increasingly more physicists are moving into the study of protein systems, bringing with them powerful mathematical and computational tools, as well as the sharp intuition and deep images inherent to the physics discipline. This work attempts to facilitate the first steps of such a transition. In order to achieve this goal, we provide an exhaustive account of the reasons underlying the protein folding problem enormous relevance and summarize the present-day status of the methods aimed to solving it. We also provide an introduction to the particular structure of these biological heteropolymers, and we physically define the problem stating the assumptions behind this (commonly implicit) definition. Finally, we review the 'special flavor' of statistical mechanics that is typically used to study the astronomically large phase spaces of macromolecules. Throughout the whole work, much material that is found scattered in the literature has been put together here to improve comprehension and to serve as a handy reference.Comment: 53 pages, 18 figures, the figures are at a low resolution due to arXiv restrictions, for high-res figures, go to http://www.pabloechenique.co

    A Bayesian test for the appropriateness of a model in the biomagnetic inverse problem

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    This paper extends the work of Clarke [1] on the Bayesian foundations of the biomagnetic inverse problem. It derives expressions for the expectation and variance of the a posteriori source current probability distribution given a prior source current probability distribution, a source space weight function and a data set. The calculation of the variance enables the construction of a Bayesian test for the appropriateness of any source model that is chosen as the a priori infomation. The test is illustrated using both simulated (multi-dipole) data and the results of a study of early latency processing of images of human faces. [1] C.J.S. Clarke. Error estimates in the biomagnetic inverse problem. Inverse Problems, 10:77--86, 1994.Comment: 13 pages, 16 figures. Submitted to Inverse Problem

    In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

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    The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the ”M–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation
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