Access of Extracellular Cations to their Binding Sites in Na,K-ATPase: Role of the Second Extracellular Loop of the α Subunit

Na,K-ATPase, the main active transport system for monovalent cations in animal cells, is responsible for maintaining Na+ and K+ gradients across the plasma membrane. During its transport cycle it binds three cytoplasmic Na+ ions and releases them on the extracellular side of the membrane, and then binds two extracellular K+ ions and releases them into the cytoplasm. The fourth, fifth, and sixth transmembrane helices of the α subunit of Na,K-ATPase are known to be involved in Na+ and K+ binding sites, but the gating mechanisms that control the access of these ions to their binding sites are not yet fully understood. We have focused on the second extracellular loop linking transmembrane segments 3 and 4 and attempted to determine its role in gating. We replaced 13 residues of this loop in the rat α1 subunit, from E314 to G326, by cysteine, and then studied the function of these mutants using electrophysiological techniques. We analyzed the results using a structural model obtained by homology with SERCA, and ab initio calculations for the second extracellular loop. Four mutants were markedly modified by the sulfhydryl reagent MTSET, and we investigated them in detail. The substituted cysteines were more readily accessible to MTSET in the E1 conformation for the Y315C, W317C, and I322C mutants. Mutations or derivatization of the substituted cysteines in the second extracellular loop resulted in major increases in the apparent affinity for extracellular K+, and this was associated with a reduction in the maximum activity. The changes produced by the E314C mutation were reversed by MTSET treatment. In the W317C and I322C mutants, MTSET also induced a moderate shift of the E1/E2 equilibrium towards the E1(Na) conformation under Na/Na exchange conditions. These findings indicate that the second extracellular loop must be functionally linked to the gating mechanism that controls the access of K+ to its binding site

Local Alignment Refinement Using Structural Assessment

Homology modeling is the most commonly used technique to build a three-dimensional model for a protein sequence. It heavily relies on the quality of the sequence alignment between the protein to model and related proteins with a known three dimensional structure. Alignment quality can be assessed according to the physico-chemical properties of the three dimensional models it produces

Polyelectrolyte Adsorption on Charged Particles in the Debye−Hückel Approximation. A Monte Carlo Approach

Monte Carlo simulations are used to study in the Debye−Hückel approximation the complexation between a polyelectrolyte and an oppositely charged spherical particle. Attention is focused on the effect of chain length and ionic concentration on (i) the adsorption/desorption limit, (ii) the interfacial structure of the adsorbed layer, and (iii) the overcharging issue. In particular, we are interested in polyelectrolyte adsorption on particles whose surface area is small to allow the polyelectrolyte to spread to the same extent on a flat surface. The extent of polyelectrolyte adsorption is found to be the result of two competing effects: the electrostatic repulsion between the chain monomers which forces the polyelectrolyte to adopt extended conformations in solutions and limits the number of monomers which may be attached to the particle, and the electrostatic attractive interactions between the particle and the monomers forcing the chain to undergo a structural transition and collapse at the particle surface. To overcome the loss of entropy per monomer due to adsorption, it is shown that a stronger electrostatic attraction, with decreasing ionic concentration, is needed for the short chains. Below that critical ionic concentration, it is found that the degree of adsorption increases with the decrease in both the chain length and ionic strength. Trains are favored at low degrees of chain polymerization while loops are favored more when increasing the size of the chain. Above a critical chain length, electrostatic repulsions between the adsorbed monomers force the polyelectrolyte to form a protuding tail in solution. Charge inversion is also observed. Indeed, depending on the polyelectrolyte length, the number of monomers close to the particle surface is higher than it is necessary to neutralize it. Charge inversion is found to increase with the ionic concentration of the solution.</p

Collapse transitions of a supersized neutral chain due to irreversibly adsorbed small colloidal particles

We performed Monte Carlo simulations to study the destabilization processes of large neutral and flexible polymer chains due to irreversibly adsorbed colloidal particles attached to the chains like beads on a necklace. The particles are modeled as charged spherical units which interact with each other via repulsive electrostatic and attractive van der Waals (vdW) potentials. The usual Monte Carlo search procedure is extended and carefully checked to completely sample the chain conformational space and achieve dense conformations in the limit of both strong attractive and repulsive interaction potentials. Configurational properties, such as the radius of gyration, the end-to-end length, and the Kuhn length, are calculated as a function of the intensity of the vdW interactions and ionic strength values. It is observed that chains exhibit a new range of possible conformations compared to the classical random walk and self avoiding walk chains or polyelectrolytes. In the limit of low salt concentration, by gradually increasing vdW interactions, chains undergo a cascade of transitions from extended structures to dumbbells, from dumbbells to pearl necklaces, and from pearl necklaces to collapsed coils. Because of strong competition between the vdW and electrostatic forces, the distance along the chain between the interacting particles, and the sampling limitations, these transitions are found to sample metastable domains and to depend on the initial conformations. To gain insight into the spatial organization of the collapsed conformations, the pair correlation functions of both monomers and particles are calculated. It is shown that collapsed conformations which are the result of strong particle–particle interactions exhibit two distinct parts: a hard core mainly composed of particles and a surrounding polymeric shell composed of loops and tails. Possible effects of such a collapsed transition on the kinetics of flocculation of a mixture containing large flexible chains and small adsorbing colloidal particles are discussed

Influence of energy minimization for six different predictors CDIE/All (A), RDIE/All (B), GBMV2/All (C), ProsaII/All (D), ANOLEA/All (E) and ANOLEA/SSE (F) applied to the test case 1flp helix1.

<p>The six corresponding profiles and their standard deviation are shown for minimized and non minimized models, with plain and dotted lines, respectively.</p

Optimization of the ANOLEA/SSE Local predictor specificity.

<p>The highest specificity is attained for an inter-residue distance cut-off of all pairs of heavy atoms of 4 Å as deduced from the scan by step of 0.5 Å from 2 to 6 Å for all the test cases. ANOLEA/SSE Local predictor scores for 1flp helix1 test case versus alignment offset to the structural alignment and for different inter-residue distance of all pairs of heavy atoms (from 2 Å (smallest sphere) to 6 Å (biggest sphere)).</p

For each test case, the SSE in the ROI is colored in red on a protein ribbon representation and is defined by a red rectangle in the alignments.

<p>The different alignments are represented and the corresponding score using the ANOLEA/SSE Local predictor is plotted. In T0141 test case, the “new strands” label in the alignment picture represents the position of a beta finger present in the structure of T0141 but absent in the 1aro_L template.</p

Flowchart of the method.

<p>A reference structural alignment of the target and the template is generated by the MALIGN3D command in MODELLER <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002645#pone.0002645-Sanchez2" target="_blank">[11]</a> (step 1). The initial target-template sequence alignment is realized by T_COFFEE (step 2). The regions of interest (ROI), defined as misaligned secondary structure elements together with their adjacent loops, are identified by comparison of the initial target-template sequence alignment with the reference structural alignment. A set of alignments to evaluate is generated using an exhaustive ungapped search in the ROI (step 3). Hundred models for each alignment are built using MODELLER (step 4). For each model, an energy minimization is done in vacuum using CHARMM (step 5). The energy for the minimized models is calculated (step 6). The secondary structure is assigned with DSSP <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002645#pone.0002645-Qiu1" target="_blank">[24]</a> and the predictor's scores are calculated (step 7). After all alignments are processed, a statistical analysis using the statistical package R (<a href="http://www.R-project.org" target="_blank">http://www.R-project.org</a>) is further performed on the predictor to associate a degree of confidence to the prediction (step 8) and the best alignment is determined (step 9). See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002645#s2" target="_blank">Materials and Methods</a> for details.</p