Role of the Cys loop and transmembrane domain in the allosteric modulation of α4β2 nicotinic acetylcholine receptors

​Allosteric modulators of pentameric ligand gated ion channels (pLGICs) are thought to act on elements of the pathways that couple agonist binding to channel gating. Using α4β2 nicotinic acetylcholine receptors (nAChRs) and the α4β2-selective positive modulators 17β-estradiol (βEST) and desformylflustrabromine (dFBr), we have identified pathways that link the binding sites for these modulators to the Cys loop, a region that is critical for channel gating in all pLGICs. Previous studies have shown that the binding site for potentiating βEST is in the C-terminal (post-M4 region) of the α4 subunit. Here, using homology modelling in combination with mutagenesis and electrophysiology, we identified the binding site for potentiating dFBr on the top-half of a cavity between the third (M3) and fourth transmembrane (M4) α-helices of the α4 subunit. We found that the binding sites for βEST and dFBr communicate with the Cys loop, through interactions between the last residue of post-M4 and F170 of the conserved FPF sequence of the Cys loop, and that these interactions affect potentiating efficacy. In addition, interactions between a residue in M3 (Y309) and F167, a residue adjacent to the Cys loop FPF motif, also affect dFBr potentiating efficacy. Thus, the Cys loop acts as a key control element in the allosteric transduction pathway for potentiating βEST and dFBr. Overall, we propose that positive allosteric modulators that bind the M3-M4 cavity or post-M4 region increase the efficacy of channel gating through interactions with the Cys loop

Quantifying Water-Mediated Protein–Ligand Interactions in a Glutamate Receptor: A DFT Study

It is becoming increasingly clear that careful treatment of water molecules in ligand–protein interactions is required in many cases if the correct binding pose is to be identified in molecular docking. Water can form complex bridging networks and can play a critical role in dictating the binding mode of ligands. A particularly striking example of this can be found in the ionotropic glutamate receptors. Despite possessing similar chemical moieties, crystal structures of glutamate and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) in complex with the ligand-binding core of the GluA2 ionotropic glutamate receptor revealed, contrary to all expectation, two distinct modes of binding. The difference appears to be related to the position of water molecules within the binding pocket. However, it is unclear exactly what governs the preference for water molecules to occupy a particular site in any one binding mode. In this work we use density functional theory (DFT) calculations to investigate the interaction energies and polarization effects of the various components of the binding pocket. Our results show (i) the energetics of a key water molecule are more favorable for the site found in the glutamate-bound mode compared to the alternative site observed in the AMPA-bound mode, (ii) polarization effects are important for glutamate but less so for AMPA, (iii) ligand–system interaction energies alone can predict the correct binding mode for glutamate, but for AMPA alternative modes of binding have similar interaction energies, and (iv) the internal energy is a significant factor for AMPA but not for glutamate. We discuss the results within the broader context of rational drug-design

Nonparametric identification of regulatory interactions from spatial and temporal gene expression data

<p>Abstract</p> <p>Background</p> <p>The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but current methods are limited in their ability to make correct predictions.</p> <p>Results</p> <p>Here we describe a novel approach which uses nonparametric statistics to generate ordinary differential equation (ODE) models from expression data. Compared to other dynamical methods, our approach requires minimal information about the mathematical structure of the ODE; it does not use qualitative descriptions of interactions within the network; and it employs new statistics to protect against over-fitting. It generates spatio-temporal maps of factor activity, highlighting the times and spatial locations at which different regulators might affect target gene expression levels. We identify an ODE model for <it>eve </it>mRNA pattern formation in the <it>Drosophila melanogaster </it>blastoderm and show that this reproduces the experimental patterns well. Compared to a non-dynamic, spatial-correlation model, our ODE gives 59% better agreement to the experimentally measured pattern. Our model suggests that protein factors frequently have the potential to behave as both an activator and inhibitor for the same <it>cis</it>-regulatory module depending on the factors' concentration, and implies different modes of activation and repression.</p> <p>Conclusions</p> <p>Our method provides an objective quantification of the regulatory potential of transcription factors in a network, is suitable for both low- and moderate-dimensional gene expression datasets, and includes improvements over existing dynamic and static models.</p

An Integrated Paleomagnetic, Multimethod- Paleointensity, and Radiometric Study on Cretaceous and Paleogene Lavas From the Lesser Caucasus: Geomagnetic and Tectonic Implications

Sixteen rhyolitic and dacitic Cretaceous and Paleocene-Eocene lavas from the Lesser Caucasus have been subjected to paleomagnetic and multimethod paleointensity experiments to analyze the variations of the Earth's magnetic field. Paleointensity experiments were performed with two methods. Thellier-type experiments with the IZZI method on 65 specimens (nine flows) yielded 15 successful determinations and experiments with the multispecimen method on 14 samples (seven flows) yielded two successful determinations. The joint analysis of the results obtained with both methods produced a mean FuK = (19.9 ± 3.7) µT for upper Cretaceous and FPg = (20.7 ± 3.3) µT for Paleogene sites. Low virtual axial dipole moments for the Cretaceous (3.4 × 1022 Am2) and Paleogene (3.5 × 1022 Am2) samples support the idea of a lower average dipole moment during periods of stable polarity of the Earth magnetic field. Mean flow paleomagnetic directions did not match expected upper Cretaceous to Paleogene directions calculated from the European Apparent Polar Wander Path. While inclination results roughly agreed with expected values, a group of sites showed nearly North-South paleodeclinations (D = 1.1° ± 14.2°), and another group displayed eastward deviated paleodeclinations (D = 72.9° ± 26.6°). These results suggest the occurrence of nearly vertical-axis rotations, probably as a result of continental collision since Oligocene. In addition to paleomagnetic and palaeointensity analyses, new K-Ar absolute age determinations have been performed on three of the studied sites, yielding Late Cretaceous ages (78.7 ± 1.7, 79.7 ± 1.6, and 83.4 ± 1.8 Ma (2σ)).Project PID2019-105796GB-100/AEI/10.13039/501100011033 (Agencia Estatal de Investigación, Spain). M. Calvo-Rathert acknowledges funding from the Fulbright Commission and the Spanish Ministry of Science, Innovation, and Universities for a research stay at Hawaii University at Manoa. A. Goguitchaichvili acknowledges financial support from UNAM-PAPIIT no. IN101920. N. García-Redondo acknowledges financial support from Junta de Castilla y León and the European Research Development Fund (ERDF). EHB acknowledges financial support for laboratory maintenance and measurements to SOEST-HIGP and National Science Foundation grants. These is SOEST 11143 and HIGP 2420 contribution

Playing is Performing – Video Games as Performance

acceptedVersionPeer reviewe

Binding Site Turnover Produces Pervasive Quantitative Changes in Transcription Factor Binding between Closely Related Drosophila Species

Genome-wide comparison of transcription factor binding between related Drosophila species highlights how sequence changes affect the biochemical events that underlie animal development

Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity