Is it the shape of the cavity, or the shape of the water in the cavity?

Historical interpretations of the thermodynamics characterizing biomolecular recognition have marginalized the role of water. An important (even, perhaps, dominant) contribution to molecular recognition in water comes from the “hydrophobic effect,” in which non-polar portions of a ligand interact preferentially with non-polar regions of a protein. Water surrounds the ligand, and water fills the binding pocket of the protein: when the protein-ligand complex forms, and hydrophobic surfaces of the binding pocket and the ligand approach one another, the molecules (and hydrogen-bonded networks of molecules) of water associated with both surfaces rearrange and, in part, entirely escape into the bulk solution. It is now clear that neither of the two most commonly cited rationalizations for the hydrophobic effect—an entropy-dominated hydrophobic effect, in which ordered waters at the surface of the ligand, and water at the surface of the protein, are released to the bulk upon binding, and a “lock-and-key” model, in which the surface of a ligand interacts directly with a surface of a protein having a complementary shape–can account for water-mediated interactions between the ligand and the protein, and neither is sufficient to account for the experimental observation of both entropy- andenthalpy-dominated hydrophobic effects. What is now clear is that there is no single hydrophobic effect, with a universally applicable, common, thermodynamic description: different processes (i.e., partitioning between phases of different hydrophobicity, aggregation in water, and binding) with different thermodynamics, depend on the molecular-level details of the structures of the molecules involved, and of the aggregates that form. A “water-centric” description of the hydrophobic effect in biomolecular recognition focuses on the structures of water surrounding the ligand, and of water filling the binding pocket of the protein, both before and after binding. This view attributes the hydrophobic effect to changes in the free energy of the networks of hydrogen bonds that are formed, broken, or re-arranged when two hydrophobic surfaces approach (but do not necessarily contact) one another. The details of the molecular topography (and the polar character) of the mole- cular surfaces play an important role in determining the structure of these networks of hydrogen-bonded waters, and in the thermodynamic description of the hydrophobic effect(s). Theorists have led the formulation of this “water-centric view”, although experiments are now supplying support for it. It poses complex problems for would-be “designers” of protein-ligand interactions, and for so-called “rational drug design”.Chemistry and Chemical Biolog

Selective Precipitation and Purification of Monovalent Proteins Using Oligovalent Ligands and Ammonium Sulfate

This paper describes a method for the selective precipitation and purification of a monovalent protein (carbonic anhydrase is used as a demonstration) from cellular lysate using ammonium sulfate and oligovalent ligands. The oligovalent ligands induce the formation of protein–ligand aggregates, and at an appropriate concentration of dissolved ammonium sulfate, these complexes precipitate. The purification involves three steps: (i) the removal of high-molecular-weight impurities through the addition of ammonium sulfate to the crude cell lysate; (ii) the introduction of an oligovalent ligand and the selective precipitation of the target protein–ligand aggregates from solution; and (iii) the removal of the oligovalent ligand from the precipitate by dialysis to release the target protein. The increase of mass and volume of the proteins upon aggregate formation reduces their solubility, and results in the selective precipitation of these aggregates. We recovered human carbonic anhydrase, from crude cellular lysate, in 82% yield and 95% purity with a trivalent benzene sulfonamide ligand. This method provides a chromatography-free strategy of purifying monovalent proteins—for which appropriate oligovalent ligands can be synthesized—and combines the selectivity of affinity-based purification with the convenience of salt-induced precipitation.Chemistry and Chemical Biolog

ELM Characteristics in MAST

Edge localized mode (ELM) characteristics in a large spherical tokamak (ST) with significant auxiliary heating are explored. High confinement is achieved in mega ampere spherical tokamak (MAST) at low ELM frequencies even though the ELMs exhibit many type III characteristics. These ELMs are associated with a reduction in the pedestal density but no significant change in the pedestal temperature or temperature profile, indicating that energy is convected from the pedestal region into the scrape-off layer. Power to the targets during an ELM arrives predominantly at the low field outboard side. ELM effluxes are observed up to 20 cm from the plasma edge at the outboard mid-plane and are associated with the radial motion of a feature at an average velocity of 0.75 km s-1. The target balance observed in MAST is potentially rather favourable for the ST since H-mode access is facilitated in a regime where ELM losses flow mostly to the large wetted area, outboard targets and, in addition, the target heat loads are reduced by an even distribution of power between the upper and lower targets

The Binding of Benzoarylsulfonamide Ligands to Human Carbonic Anhydrase is Insensitive to Formal Fluorination of the Ligand

Auf das Wasser kommt es an: Konservierte Bindungsgeometrie, enthalpiegetriebene Bindungsweise und nichtunterscheidbare Bindungsaffinitäten für fluorierte und nichtfluorierte Liganden von humaner Carbonsäureanhydrase (siehe Bild) stützen die Theorie, dass das Schlüssel-Schloss-Modell einen wichtigen Bestandteil des Bindungsvorgangs unbeachtet lässt: das Wasser, das die Bindungstasche des Proteins füllt und den Liganden umgibt.Chemistry and Chemical Biolog

Evaluating functional brain organization in individuals and identifying contributions to network overlap

Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems

Effective connectivity measured using optogenetically evoked hemodynamic signals exhibits topography distinct from resting state functional connectivity in the mouse

Brain connectomics has expanded from histological assessment of axonal projection connectivity (APC) to encompass resting state functional connectivity (RS-FC). RS-FC analyses are efficient for whole-brain mapping, but attempts to explain aspects of RS-FC (e.g., interhemispheric RS-FC) based on APC have been only partially successful. Neuroimaging with hemoglobin alone lacks specificity for determining how activity in a population of cells contributes to RS-FC. Wide-field mapping of optogenetically defined connectivity could provide insights into the brain\u27s structure-function relationship. We combined optogenetics with optical intrinsic signal imaging to create an efficient, optogenetic effective connectivity (Opto-EC) mapping assay. We examined EC patterns of excitatory neurons in awake, Thy1-ChR2 transgenic mice. These Thy1-based EC (Thy1-EC) patterns were evaluated against RS-FC over the cortex. Compared to RS-FC, Thy1-EC exhibited increased spatial specificity, reduced interhemispheric connectivity in regions with strong RS-FC, and appreciable connection strength asymmetry. Comparing the topography of Thy1-EC and RS-FC patterns to maps of APC revealed that Thy1-EC more closely resembled APC than did RS-FC. The more general method of Opto-EC mapping with hemoglobin can be determined for 100 sites in single animals in under an hour, and is amenable to other neuroimaging modalities. Opto-EC mapping represents a powerful strategy for examining evolving connectivity-related circuit plasticity

Elections and Ethnic Civil War

Existing research on how democratization may influence the risk of civil war tends to consider only changes in the overall level of democracy and rarely examines explicitly the postulated mechanisms relating democratization to incentives for violence. The authors argue that typically highlighted key mechanisms imply that elections should be especially likely to affect ethnic groups’ inclination to resort to violence. Distinguishing between types of conflict and the order of competitive elections, the authors find that ethnic civil wars are more likely to erupt after competitive elections, especially after first and second elections following periods of no polling. When disaggregating to the level of individual ethnic groups and conflicts over territory or government, the authors find some support for the notion that ethno-nationalist mobilization and sore-loser effects provoke postelectoral violence. More specifically, although large groups in general are more likely to engage in governmental conflicts, they are especially likely to do so after noncompetitive elections. Competitive elections, however, strongly reduce the risk of conflict. </jats:p