Relation between sequence and structure of HIV-1 protease inhibitor complexes: a model system for the analysis of protein flexibility.

The flexibility of different regions of HIV-1 protease was examined by using a database consisting of 73 X-ray structures that differ in terms of sequence, ligands or both. The root-mean-square differences of the backbone for the set of structures were shown to have the same variation with residue number as those obtained from molecular dynamics simulations, normal mode analyses and X-ray B-factors. This supports the idea that observed structural changes provide a measure of the inherent flexibility of the protein, although specific interactions between the protease and the ligand play a secondary role. The results suggest that the potential energy surface of the HIV-1 protease is characterized by many local minima with small energetic differences, some of which are sampled by the different X-ray structures of the HIV-1 protease complexes. Interdomain correlated motions were calculated from the structural fluctuations and the results were also in agreement with molecular dynamics simulations and normal mode analyses. Implications of the results for the drug-resistance engendered by mutations are discussed briefly.

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

NO rebinding to myoglobin: a reactive molecular dynamics study.

The rebinding of NO to myoglobin after photolysis is studied using the 'reactive molecular dynamics' method. In this approach the energy of the system is evaluated on two potential energy surfaces that include the heme-ligand interactions which change between liganded and unliganded myoglobin. This makes it possible to take into account in a simple way, the high dimensionality of the transition seam connecting the reactant and product states. The dynamics of the dissociated NO molecules are examined, and the geometrical and energetic properties of the transition seam are studied. Analysis of the frequency of recrossing shows that the height of the effective rebinding barrier is dependent on the time after photodissociation. This effect is due mainly to protein relaxation and may contribute to the experimentally observed non-exponential rebinding rate of NO, as has been suggested previously.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Measuring surface potential changes on leaves.

We provide here a detailed protocol for studying the changes in electrical surface potential of leaves. This method has been developed over the years by plant physiologists and is currently used in different variants in many laboratories. The protocol records surface potential changes to measure long-distance electrical signals induced by diverse stimuli such as leaf wounding or current injection. This technique can be used to determine signaling speeds, to measure the connectivity between different plant organs and-by exploiting mutant plants-to identify transporters and ion channels involved in electrical signaling. The approach can be combined with the analysis of mRNA expression and of metabolite concentrations to correlate electrical signaling to specific physiological events. We describe how to use this protocol on Arabidopsis, looking at the effects of leaf wounding; however, it is broadly applicable to other plants and can be used to study other aspects of plant physiology. After wound infliction, surface potential recording takes ∼20 min per plant.

Direct simulation of interface dynamics: linking capillary pressure, interfacial area and surface energy

We perform direct numerical simulations of drainage by solving Navier- Stokes equations in the pore space and employing the Volume Of Fluid (VOF) method to track the evolution of the fluid-fluid interface. After demonstrating that the method is able to deal with large viscosity contrasts and to model the transition from stable flow to viscous fingering, we focus on the definition of macroscopic capillary pressure. When the fluids are at rest, the difference between inlet and outlet pressures and the difference between the intrinsic phase average pressure coincide with the capillary pressure. However, when the fluids are in motion these quantities are dominated by viscous forces. In this case, only a definition based on the variation of the interfacial energy provides an accurate measure of the macroscopic capillary pressure and allows separating the viscous from the capillary pressure components.

Direct numerical simulations of interface dynamics to link capillary pressure and total surface energy

The flow of two immiscible fluids through a porous medium depends on the complex interplay between gravity, capillarity, and viscous forces. The interaction between these forces and the geometry of the medium gives rise to a variety of complex flow regimes that are difficult to describe using continuum models. Although a number of pore-scale models have been employed, a careful investigation of the macroscopic effects of pore-scale processes requires methods based on conservation principles in order to reduce the number of modeling assumptions. In this work we perform direct numerical simulations of drainage by solving Navier-Stokes equations in the pore space and employing the Volume Of Fluid (VOF) method to track the evolution of the fluid-fluid interface. After demonstrating that the method is able to deal with large viscosity contrasts and model the transition from stable flow to viscous fingering, we focus on the macroscopic capillary pressure and we compare different definitions of this quantity under quasi-static and dynamic conditions. We show that the difference between the intrinsic phase-average pressures, which is commonly used as definition of Darcy-scale capillary pressure, is subject to several limitations and it is not accurate in presence of viscous effects or trapping. In contrast, a definition based on the variation of the total surface energy provides an accurate estimate of the macroscopic capillary pressure. This definition, which links the capillary pressure to its physical origin, allows a better separation of viscous effects and does not depend on the presence of trapped fluid clusters.

Oligomerization of the alpha 1a- and alpha 1b-adrenergic receptor subtypes. Potential implications in receptor internalization.

We combined biophysical, biochemical, and pharmacological approaches to investigate the ability of the alpha 1a- and alpha 1b-adrenergic receptor (AR) subtypes to form homo- and hetero-oligomers. Receptors tagged with different epitopes (hemagglutinin and Myc) or fluorescent proteins (cyan and green fluorescent proteins) were transiently expressed in HEK-293 cells either individually or in different combinations. Fluorescence resonance energy transfer measurements provided evidence that both the alpha 1a- and alpha 1b-AR can form homo-oligomers with similar transfer efficiency of approximately 0.10. Hetero-oligomers could also be observed between the alpha 1b- and the alpha 1a-AR subtypes but not between the alpha 1b-AR and the beta2-AR, the NK1 tachykinin, or the CCR5 chemokine receptors. Oligomerization of the alpha 1b-AR did not require the integrity of its C-tail, of two glycophorin motifs, or of the N-linked glycosylation sites at its N terminus. In contrast, helix I and, to a lesser extent, helix VII were found to play a role in the alpha 1b-AR homo-oligomerization. Receptor oligomerization was not influenced by the agonist epinephrine or by the inverse agonist prazosin. A constitutively active (A293E) as well as a signaling-deficient (R143E) mutant displayed oligomerization features similar to those of the wild type alpha 1b-AR. Confocal imaging revealed that oligomerization of the alpha1-AR subtypes correlated with their ability to co-internalize upon exposure to the agonist. The alpha 1a-selective agonist oxymetazoline induced the co-internalization of the alpha 1a- and alpha 1b-AR, whereas the alpha 1b-AR could not co-internalize with the NK1 tachykinin or CCR5 chemokine receptors. Oligomerization might therefore represent an additional mechanism regulating the physiological responses mediated by the alpha 1a- and alpha 1b-AR subtypes.

Siliceous deep-sea sponge Monorhaphis chuni: A potential paleoclimate archive in ancient animals

The deep-sea sponge Monorhaphis chuni forms giant basal spicules, which can reach lengths of 3 m; they represent the largest biogenic silica structures on Earth that is formed from an individual metazoan. The spicules offer a unique opportunity to record environmental change of past oceanic and climatic conditions. A giant spicule collected in the East China Sea in a depth of 1110 m was investigated. The oxygen isotopic composition and Mg/Ca ratios determined along center-to-surface segments are used as geochemical proxies for the assessment of seawater paleotemperatures. Calculations are based on the assumption that the calculated temperature near the surface of the spicule is identical with the average ambient temperature of 4 degrees C. A seawater temperature of 1.9 degrees C is inferred for the beginning of the lifespan of the Monorhaphis specimen. The temperature increases smoothly to 2.3 degrees C, to be followed by sharply increased and variable temperatures up to 6-10 degrees C. In the outer part of the spicule, the inferred seawater temperature is about 4 degrees C. The lifespan of the spicule can be estimated to 11,000 +/- 3000 years using the long-term trend of the inferred temperatures fitted to the seawater temperature age relationships since the Last Glacial Maximum. Specimens of Monorhaphis therefore represents one the oldest living animals on Earth. The remarkable temperature spikes of the ambient seawater occurring 9500-3100 years B.P. are explained by discharges of hydrothermal fluids in the neighborhood of the spicule. The irregular lamellar organization of the spicule and the elevated Mn concentrations during the high-temperature growth are consistent with a hydrothermal fluid input. (C) 2012 Elsevier B.V. All rights reserved.

The pollutant diethylhexyl phthalate regulates hepatic energy metabolism via species-specific PPARalpha-dependent mechanisms.

Background: The modulation of energetic homeostasis by pollutants has recently emerged as a potential contributor to the onset of metabolic disorders. Diethylhexyl phthalate (DEHP) is a widely used industrial plasticizer to which humans are widely exposed. Phthalates can activate the three peroxisome proliferatoractivated receptor (PPAR) isotypes on cellular models and induce peroxisome proliferation in rodents.Objectives: In this study, we aimed to evaluate the systemic and metabolic consequences of DEHP exposure that have remained so far unexplored and to characterize the underlying molecular mechanisms of action.Methods: As a proof of concept and mechanism, genetically engineered mouse models of PPARs were exposed to high doses of DEHP, followed by metabolic and molecular analyses.Results: DEHP-treated mice were protected from diet-induced obesity via PPARalpha-dependent activation of hepatic fatty acid catabolism, whereas the activity of neither PPARbeta nor PPARgamma was affected. However, the lean phenotype observed in response to DEHP in wild-type mice was surprisingly abolished in PPARalpha-humanized mice. These species differences are associated with a different pattern of coregulator recruitment.Conclusion: These results demonstrate that DEHP exerts species-specific metabolic actions that rely to a large extent on PPARalpha signaling and highlight the metabolic importance of the species-specific activation of PPARalpha by xenobiotic compounds. Editor's SummaryDiethylhexyl phthalate (DEHP) is an industrial plasticizer used in cosmetics, medical devices, food packaging, and other applications. Evidence that DEHP metabolites can activate peroxisome proliferatoractivated receptors (PPARs) involved in fatty acid oxidation (PPARalpha and PPARbeta) and adiposite function and insulin resistance (PPARgamma) has raised concerns about potential effects of DEHP on metabolic homeostasis. In rodents, PPARalpha activation also induces hepatic peroxisome proliferation, but this response to PPARalpha activation is not observed in humans. Feige et al. (p. 234) evaluated systemic and metabolic consequences of high-dose oral DEHP in combination with a high-fat diet in wild-type mice and genetically engineered mouse PPAR models. The authors report that mice exposed to DEHP gained less weight than controls, without modifying their feeding behavior; they also exhibited lower triglyceride levels, smaller adipocytes, and improved glucose tolerance compared with controls. These effects, which were observed in mice fed both high-fat and standard diets, appeared to be mediated by PPARalpha-dependent activation of hepatic fatty acid catabolism without apparent involvement of PPARbeta or PPARgamma. However, mouse models that expressed human (versus mouse) PPARalpha tended to gain more weight on a high-fat diet than their DHEP-unexposed counterparts. The authors conclude that findings support species-specific metabolic effects of DEHP mediated by PPARalpha activation.

Oxidative potential of a panel of carbonaceous and metallic nanoparticles

Characterisation of nanoparticles (NP) based on size distribution, surface area, reactivity, and aggregation status of nanoparticles (NP) are of prime importance because they are usually closely related to toxicity. To date, most of the toxicity studies are quite time and money consuming. In the present study we report the oxidative properties of a panel of various NP (four Carbonaceous, nine Metal oxides, and one Metal as showed in Table 1) assessed with an acellular reactivity test measuring dithiothreitol (DTT) consumption (Sauvain et al. 2008). Such a test allows determining the ability of NP to catalyse the transfer of electrons from DTT to oxygen. DTT is used as a reductant species. NP were diluted and sonicated in Tween 80® to a final concentration of 50 g/mL. Printex 90 was diluted 5 times before doing the DTT assay because of its expected higher activity. Suspensions were characterised for NP size distribution by Nanoparticle Tracking Analysis (Nanosight©). Fresh solutions were incubated with DTT (100 μM). Aliquots were taken every 5 min and the remaining DTT was determined by reacting it with DTNB. The reaction rate was determined for NP suspensions and blank in parallel. The mean Brownian size distribution of NP agglomerates in suspension is presented in Table 1. D values correspond to 10th, and 50th percentiles of the particle diameters. All the NP agglomerated in Tween 80 with a D50 size corresponding to at least twice their primary size, except for Al2O3 (300 nm). The DTT test showed Printex 90 sample to be the most reactive one, followed by Diesel EPA and Nanotubes. Most of the metallic NP was nonresponding toward this test, except for NiO and Ag which reacted positively and ZnO which presented the most negative reactivity (see Figure 1). This last observation suggests that electron transfer between DTT and oxygen is hindered in presence of ZnO compared with the blank. Such "stabilization" could be attributable to ZnO dissolution and complexation between Zn2+ ions and DTT.

Application of a roughness-length representation to parameterize energy loss in 3-D numerical simulations of large rivers

Recent technological advances in remote sensing have enabled investigation of the morphodynamics and hydrodynamics of large rivers. However, measuring topography and flow in these very large rivers is time consuming and thus often constrains the spatial resolution and reach-length scales that can be monitored. Similar constraints exist for computational fluid dynamics (CFD) studies of large rivers, requiring maximization of mesh-or grid-cell dimensions and implying a reduction in the representation of bedform-roughness elements that are of the order of a model grid cell or less, even if they are represented in available topographic data. These ``subgrid'' elements must be parameterized, and this paper applies and considers the impact of roughness-length treatments that include the effect of bed roughness due to ``unmeasured'' topography. CFD predictions were found to be sensitive to the roughness-length specification. Model optimization was based on acoustic Doppler current profiler measurements and estimates of the water surface slope for a variety of roughness lengths. This proved difficult as the metrics used to assess optimal model performance diverged due to the effects of large bedforms that are not well parameterized in roughness-length treatments. However, the general spatial flow patterns are effectively predicted by the model. Changes in roughness length were shown to have a major impact upon flow routing at the channel scale. The results also indicate an absence of secondary flow circulation cells in the reached studied, and suggest simpler two-dimensional models may have great utility in the investigation of flow within large rivers. Citation: Sandbach, S. D. et al. (2012), Application of a roughness-length representation to parameterize energy loss in 3-D numerical simulations of large rivers, Water Resour. Res., 48, W12501, doi: 10.1029/2011WR011284.

Detailed DEM analysis of a rockslide scar to characterize the basal sliding surface of active rockslides

The basal sliding surfaces in large rockslides are often composed of several surfaces and possess a complex geometry. The exact morphology and location in three dimensions of the sliding surface remains generally unknown, in spite of extensive field and subsurface investigations, such as those at the Åknes rockslide (western Norway). This knowledge is crucial for volume estimations, failure mechanisms, and numerical slope stability modeling. This paper focuses on the geomorphologic characterization of the basal sliding surface of a postglacial rockslide scar in the vicinity of Åknes. This scar displays a stepped basal sliding surface formed by dip slopes of the gneiss foliation linked together by steeply dipping fractures. A detailed characterization of the rockslide scar by means of high-resolution digital elevation models permits statistical parameters of dip angle, spacing, persistence, and roughness of foliation surfaces and step fractures to be obtained. The characteristics are used for stochastic simulations of stepped basal sliding surfaces at the Åknes rockslide. These findings are compared with previous models based on geophysical investigations. This study discusses the investigation of rockslide scars and rock outcrops for a better understanding of potential rockslides. This work identifies possible basal sliding surface locations, which is a valuable input for volume estimates, design and location of monitoring instrumentation, and numerical slope stability modeling.

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2K(b) system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method.