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1702 Publications visible to you, out of a total of 1702
How ARVC-Related Mutations Destabilize Desmoplakin: An MD Study

Abstract (Expand)

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a familial heart disease linked to mutations in several desmosomal proteins, but the specific effects of these mutations on the molecular level … are poorly understood. Among the many documented ARVC-related genetic variants, a striking hotspot of nine mutations has been identified in the plakin domain of desmoplakin. This hotspot can be found at the meeting point of three different subdomains of desmoplakin: two spectrin repeats and a Src homology 3 domain. We set out to understand the effect of these mutations. We determine, using molecular dynamics simulations, how these mutations affect the mechanics of this interface, performing two different classes of simulations. First, we sample the dynamics of the plakin domain, in particular the tendency of the interdomain hinge to buckle, and then we apply an external force onto the constructs and determine the force necessary to break them. We find that surface-exposed mutations are not affecting the dynamics to a very large degree but that most buried mutations make the junction more flexible and decrease the rupture forces observed. Our data suggest that buried ARVC mutations destabilize desmoplakin and thereby impair desmosome integrity under tension.

Authors: Csaba Daday, Laura Marlene Mateyka, Frauke Gräter

Date Published: 1st Mar 2019

Publication Type: Journal

Topology-Driven Single-Molecule Conductance of Carbon Nanothreads

Abstract (Expand)

Highly conductive single-molecule junctions typically involve π-conjugated molecular bridges, whose frontier molecular orbital energy levels can be fine-tuned to best match the Fermi level of the leads. … Fully saturated wires, e.g., alkanes, are typically thought of as insulating rather than highly conductive. However, in this work, we demonstrate in silico that significant zero-bias conductance can be achieved in such systems by means of topology. Specifically, caged saturated hydrocarbons offering multiple σ-conductance channels afford transmission far beyond what could be expected based upon conventional superposition laws, particularly if these pathways are composed entirely from quaternary carbon atoms. Computed conductance of molecular bridges based on carbon nanothreads, e.g., polytwistane, is not only of appreciable magnitude; it also shows a very slow decay with increasing nanogap, similarly to the case of π-conjugated wires. These findings offer a way to manipulate the transport properties of molecular systems by means of their topology, alternatively to the traditionally invoked electronic structure.

Authors: Ganna Gryn’ova, Clémence Corminboeuf

Date Published: 11th Feb 2019

Publication Type: Journal

Influence of Transmembrane Helix Mutations on Cytochrome P450-Membrane Interactions and Function

Abstract

Not specified

Authors: Ghulam Mustafa, Prajwal P. Nandekar, Tyler J. Camp, Neil J. Bruce, Michael C. Gregory, Stephen G. Sligar, Rebecca C. Wade

Date Published: 1st Feb 2019

Publication Type: Journal

Identifying a First-Order Phase Transition in Neutron-Star Mergers through Gravitational Waves

Abstract

Not specified

Authors: Andreas Bauswein, Niels-Uwe F. Bastian, David B. Blaschke, Katerina Chatziioannou, James A. Clark, Tobias Fischer, Micaela Oertel

Date Published: 1st Feb 2019

Publication Type: Journal

Observing the post-merger signal of GW170817-like events with improved gravitational-wave detectors

Abstract

Not specified

Authors: Andoni Torres-Rivas, Katerina Chatziioannou, Andreas Bauswein, James Alexander Clark

Date Published: 1st Feb 2019

Publication Type: Journal

Remnants and ejecta of thermonuclear electron-capture supernovae. Constraining oxygen-neon deflagrations in high-density white dwarfs

Abstract

Not specified

Authors: S. Jones, F. K. Röpke, C. Fryer, A. J. Ruiter, I. R. Seitenzahl, L. R. Nittler, S. T. Ohlmann, R. Reifarth, M. Pignatari, K. Belczynski

Date Published: 1st Feb 2019

Publication Type: Journal

Probabilistic photometric redshift estimation in massive digital sky surveys via machine learning

Abstract (Expand)

The problem of photometric redshift estimation is a major subject in astronomy, since the need of estimating distances for a huge number of sources, as required by the data deluge of the recent years. … The ability to estimate redshifts through spectroscopy does not scale with this avalanche of data. Photometric redshifts provide the required redshift estimates at the cost of some precision. The success of several forthcoming missions is highly dependent on the availability of photometric redshifts. The purpose of this thesis is to provide innovative methods for photometric redshift estimation. Two models are proposed. The first is fully-automatized, based on the combination of a convolutional neural network with a mixture density network, to predict probabilistic multimodal redshifts directly from images. The second model is features-based, performing a massive combination of photometric parameters to apply a forward selection in a huge feature space. The proposed models perform very efficiently compared to some of the most common models used in the literature. An important part of the work is dedicated to the correct estimation of the errors and prediction quality. The proposed models are very general and can be applied to different topics in astronomy and beyond.

Author: Antonio D'Isanto

Date Published: 1st Feb 2019

Publication Type: Doctoral Thesis

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