Electronic quantization in dielectric nanolaminates

The scientific background in the field of the laser induced damage processes in optical coatings has been significantly extended during the last decades. Especially for the ultra-short pulse regime a clear correlation between the electronic material parameters and the laser damage threshold could be demonstrated. In the present study, the quantization in nanolaminates is investigated to gain a deeper insight into the behavior of the blue shift of the bandgap in specific coating materials as well as to find approximations for the effective mass of the electrons. The theoretical predictions are correlated to the measurements. © 2016 SPIE. Downloading of the abstract is permitted for personal use only.Ministry for Science and Culture of Lower SaxonyVolkswagen Stiftun

Methionine Sulfoxides on Prion Protein Helix-3 Switch on the α-Fold Destabilization Required for Conversion

BACKGROUND: The conversion of the cellular prion protein (PrP(C)) into the infectious form (PrP(Sc)) is the key event in prion induced neurodegenerations. This process is believed to involve a multi-step conformational transition from an alpha-helical (PrP(C)) form to a beta-sheet-rich (PrP(Sc)) state. In addition to the conformational difference, PrP(Sc) exhibits as covalent signature the sulfoxidation of M213. To investigate whether such modification may play a role in the misfolding process we have studied the impact of methionine oxidation on the dynamics and energetics of the HuPrP(125-229) alpha-fold. METHODOLOGY/PRINCIPAL FINDINGS: Using molecular dynamics simulation, essential dynamics, correlated motions and signal propagation analysis, we have found that substitution of the sulfur atom of M213 by a sulfoxide group impacts on the stability of the native state increasing the flexibility of regions preceding the site of the modification and perturbing the network of stabilizing interactions. Together, these changes favor the population of alternative states which maybe essential in the productive pathway of the pathogenic conversion. These changes are also observed when the sulfoxidation is placed at M206 and at both, M206 and M213. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the sulfoxidation of Helix-3 methionines might be the switch for triggering the initial alpha-fold destabilization required for the productive pathogenic conversion

ELIXIR and Toxicology: a community in development [version 2; peer review: 2 approved]

Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology, and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities

CYP 2D6 Binding Affinity Predictions Using Multiple Ligand and Protein Conformations

Because of the large flexibility and malleability of Cytochrome P450 enzymes (CYPs), in silico prediction of CYP binding affinities to drugs and other xenobiotic compounds is a true challenge. In the current work, we use an iterative linear interaction energy (LIE) approach to compute CYP binding affinities from molecular dynamics (MD) simulation. In order to improve sampling of conformational space, we combine results from simulations starting with different relevant protein-ligand geometries. For calculated binding free energies of a set of thiourea compounds binding to the flexible CYP 2D6 isoform, improved correlation with experiment was obtained by combining results ofMDruns starting from distinct protein conformations and ligand-binding orientations. This accuracy was obtained from relatively short MD simulations, which makes our approach computationally attractive for automated calculations of ligand-binding affinities to flexible proteins such as CYPs. © 2013 by the authors; licensee MDPI, Basel, Switzerland

A Comparison Between QM/MM And QM/QM Based Fitting of Condensed-Phase Atomic Polarizabilities

Recently we reported a combined QM/MM approach to estimate condensed-phase values of atomic polarizabilities for use in (bio)molecular simulation. The setup relies on a MM treatment of the solvent when determining atomic polarizabilities to describe the response of a QM described solute to its external electric field. In this work, we study the effect of using alternative descriptions of the solvent molecules when evaluating atomic polarizabilities of a methanol solute. In a first step, we show that solute polarizabilities are not significantly affected upon substantially increasing the MM dipole moments towards values that are typically reported in literature for water solvent molecules. Subsequently, solute polarization is evaluated in the presence of a QM described solvent (using the frozen-density embedding method). In the latter case, lower oxygen polarizabilities were obtained than when using MM point charges to describe the solvent, due to introduction of Pauli-repulsion effects. This journal is © the Partner Organisations 2014

Improving the iterative linear interaction energy approach using automated recognition of configurational transitions.

Recently an iterative method was proposed to enhance the accuracy and efficiency of ligand-protein binding affinity prediction through linear interaction energy (LIE) theory. For ligand binding to flexible Cytochrome P450s (CYPs), this method was shown to decrease the root-mean-square error and standard deviation of error prediction by combining interaction energies of simulations starting from different conformations. Thereby, different parts of protein-ligand conformational space are sampled in parallel simulations. The iterative LIE framework relies on the assumption that separate simulations explore different local parts of phase space, and do not show transitions to other parts of configurational space that are already covered in parallel simulations. In this work, a method is proposed to (automatically) detect such transitions during the simulations that are performed to construct LIE models and to predict binding affinities. Using noise-canceling techniques and splines to fit time series of the raw data for the interaction energies, transitions during simulation between different parts of phase space are identified. Boolean selection criteria are then applied to determine which parts of the interaction energy trajectories are to be used as input for the LIE calculations. Here we show that this filtering approach benefits the predictive quality of our previous CYP 2D6-aryloxypropanolamine LIE model. In addition, an analysis is performed of the gain in computational efficiency that can be obtained from monitoring simulations using the proposed filtering method and by prematurely terminating simulations accordingly. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00894-015-2883-y) contains supplementary material, which is available to authorized users