Energy gap and proximity effect in MgB2MgB_2 superconducting wires

Measurements of the penetration depth $\lambda (T,H)$ in the presence of a DC magnetic field were performed in $MgB_2$ wires. In as-prepared wires $\lambda (T,H<130 Oe)$ shows a strong diamagnetic downturn below $\approx 10 K$. A DC magnetic field of $130 Oe$ completely suppressed the downturn. The data are consistent with proximity coupling to a surface $Mg$ layer left during synthesis. A theory for the proximity effect in the clean limit, together with an assumed distribution of the $Mg$ layer thickness, qualitatively explains the field and temperature dependence of the data. Removal of the $Mg$ by chemical etching results in an exponential temperature dependence for $\lambda (T)$ with an energy gap of $2 \Delta (0)/T_c\approx 1.54$ ($\Delta(0) \approx 2.61 meV$), in close agreement with recent measurements on commercial powders and single crystals. This minimum gap is only 44% of the BCS weak coupling value, implying substantial anisotropy.Comment: RevTeX 4, 4 EPS figure

Reflectionless tunneling in ballistic normal-metal--superconductor junctions

We investigate the phenomenon of reflectionless tunneling in ballistic normal-metal--superconductor (NS) structures, using a semiclassical formalism. It is shown that applied magnetic field and superconducting phase difference both impair the constructive interference leading to this effect, but in a qualitatively different way. This is manifested both in the conductance and in the shot noise properties of the system considered. Unlike diffusive systems, the features of the conductance are sharp, and enable fine spatial control of the current, as well as single channel manipulations. We discuss the possibility of conducting experiments in ballistic semiconductor-superconductor structures with smooth interfaces and some of the phenomena, specific to such structures, that could be measured. A general criterion for the barrier at NS interfaces, though large, to be effectively transparent to pair current is obtained.Comment: published versio

Metropolis simulations of Met-Enkephalin with solvent-accessible area parameterizations

We investigate the solvent-accessible area method by means of Metropolis simulations of the brain peptide Met-Enkephalin at 300$K$. For the energy function ECEPP/2 nine atomic solvation parameter (ASP) sets are studied. The simulations are compared with one another, with simulations with a distance dependent electrostatic permittivity $\epsilon (r)$, and with vacuum simulations ($\epsilon =2$). Parallel tempering and the biased Metropolis techniques RM$_1$ are employed and their performance is evaluated. The measured observables include energy and dihedral probability densities (pds), integrated autocorrelation times, and acceptance rates. Two of the ASP sets turn out to be unsuitable for these simulations. For all other systems selected configurations are minimized in search of the global energy minima, which are found for the vacuum and the $\epsilon(r)$ system, but for none of the ASP models. Other observables show a remarkable dependence on the ASPs. In particular, we find three ASP sets for which the autocorrelations at 300$$K are considerably smaller than for vacuum simulations.Comment: 10 pages and 8 figure

Energy dependent counting statistics in diffusive superconducting tunnel junctions

We present an investigation of the energy dependence of the full charge counting statistics in diffusive normal-insulating-normal-insulating-superconducting junctions. It is found that the current in general is transported via a correlated transfer of pairs of electrons. Only in the case of strongly asymmetric tunnel barriers or energies much larger than the Thouless energy is the pair transfer uncorrelated. The second cumulant, the noise, is found to depend strongly on the applied voltage and temperature. For a junction resistance dominated by the tunnel barrier to the normal reservoir, the differential shot noise shows a double peak feature at voltages of the order of the Thouless energy, a signature of an ensemble averaged electron-hole resonance.Comment: 8 pages, 5 figure

Carbohydrate-Aromatic Interactions in Proteins

Protein-carbohydrate interactions play pivotal roles in health and disease. However, defining and manipulating these interactions has been hindered by an incomplete understanding of the underlying fundamental forces. To elucidate common and discriminating features in carbohydrate recognition, we have analyzed quantitatively X-ray crystal structures of proteins with noncovalently bound carbohydrates. Within the carbohydrate-binding pockets, aliphatic hydrophobic residues are disfavored, whereas aromatic side chains are enriched. The greatest preference is for tryptophan with an increased prevalence of 9-fold. Variations in the spatial orientation of amino acids around different monosaccharides indicate specific carbohydrate C-H bonds interact preferentially with aromatic residues. These preferences are consistent with the electronic properties of both the carbohydrate C-H bonds and the aromatic residues. Those carbohydrates that present patches of electropositive saccharide C-H bonds engage more often in CH-π interactions involving electron-rich aromatic partners. These electronic effects are also manifested when carbohydrate-aromatic interactions are monitored in solution: NMR analysis indicates that indole favorably binds to electron-poor C-H bonds of model carbohydrates, and a clear linear free energy relationships with substituted indoles supports the importance of complementary electronic effects in driving protein-carbohydrate interactions. Together, our data indicate that electrostatic and electronic complementarity between carbohydrates and aromatic residues play key roles in driving protein-carbohydrate complexation. Moreover, these weak noncovalent interactions influence which saccharide residues bind to proteins, and how they are positioned within carbohydrate-binding sites

Quasiclassical theory of superconductivity: a multiple interface geometry

The purpose of the paper is to suggest a new method which allows one to study multiple coherent reflection/transmissions by partially transparent interfaces (e.g. in multi-layer mesoscopic structures or grain boundaries in high-Tc's) in the framework of the quasiclassical theory of superconductivity. It is argued that typically the trajectory of the particle is a simply connected tree (no loops) with knots, i.e. the points where interface scattering events occur and ballistic pieces of the trajectory are mixed. A linear boundary condition for the 2-component trajectory "wave function" which factorizes matrix (retarded) Green's function, is formulated for an arbitrary interface, specular or diffusive. To show the usage of the method, the current response to the vector potential (the total superfluid density rho_s) of a SS' sandwich with the different signs of the order parameter in S and S', is calculated. In this model, a few percent of reflection by the SS' interface transforms the paramagnetic response (rho_s < 0) created by the zero-energy Andreev bound states near an ideal interface (see Fauchere et al. PRL, 82, 3336 (1999), cond-mat/9901112), into the usual diamagnetic one (rho_s >0).Comment: Extended abstract submitted to "Electron Transport in Mesoscopic Systems", Satellite conference to LT22, Goteborg, 12-15 August, 1999. 2 pages Minor changes + the text height problem fixe

Incorporating Distant Sequence Features and Radial Basis Function Networks to Identify Ubiquitin Conjugation Sites

Ubiquitin (Ub) is a small protein that consists of 76 amino acids about 8.5 kDa. In ubiquitin conjugation, the ubiquitin is majorly conjugated on the lysine residue of protein by Ub-ligating (E3) enzymes. Three major enzymes participate in ubiquitin conjugation. They are – E1, E2 and E3 which are responsible for activating, conjugating and ligating ubiquitin, respectively. Ubiquitin conjugation in eukaryotes is an important mechanism of the proteasome-mediated degradation of a protein and regulating the activity of transcription factors. Motivated by the importance of ubiquitin conjugation in biological processes, this investigation develops a method, UbSite, which uses utilizes an efficient radial basis function (RBF) network to identify protein ubiquitin conjugation (ubiquitylation) sites. This work not only investigates the amino acid composition but also the structural characteristics, physicochemical properties, and evolutionary information of amino acids around ubiquitylation (Ub) sites. With reference to the pathway of ubiquitin conjugation, the substrate sites for E3 recognition, which are distant from ubiquitylation sites, are investigated. The measurement of F-score in a large window size (−20∼+20) revealed a statistically significant amino acid composition and position-specific scoring matrix (evolutionary information), which are mainly located distant from Ub sites. The distant information can be used effectively to differentiate Ub sites from non-Ub sites. As determined by five-fold cross-validation, the model that was trained using the combination of amino acid composition and evolutionary information performs best in identifying ubiquitin conjugation sites. The prediction sensitivity, specificity, and accuracy are 65.5%, 74.8%, and 74.5%, respectively. Although the amino acid sequences around the ubiquitin conjugation sites do not contain conserved motifs, the cross-validation result indicates that the integration of distant sequence features of Ub sites can improve predictive performance. Additionally, the independent test demonstrates that the proposed method can outperform other ubiquitylation prediction tools

Structural Similarity and Classification of Protein Interaction Interfaces

Interactions between proteins play a key role in many cellular processes. Studying protein-protein interactions that share similar interaction interfaces may shed light on their evolution and could be helpful in elucidating the mechanisms behind stability and dynamics of the protein complexes. When two complexes share structurally similar subunits, the similarity of the interaction interfaces can be found through a structural superposition of the subunits. However, an accurate detection of similarity between the protein complexes containing subunits of unrelated structure remains an open problem

SNOSite: Exploiting Maximal Dependence Decomposition to Identify Cysteine S-Nitrosylation with Substrate Site Specificity

S-nitrosylation, the covalent attachment of a nitric oxide to (NO) the sulfur atom of cysteine, is a selective and reversible protein post-translational modification (PTM) that regulates protein activity, localization, and stability. Despite its implication in the regulation of protein functions and cell signaling, the substrate specificity of cysteine S-nitrosylation remains unknown. Based on a total of 586 experimentally identified S-nitrosylation sites from SNAP/L-cysteine-stimulated mouse endothelial cells, this work presents an informatics investigation on S-nitrosylation sites including structural factors such as the flanking amino acids composition, the accessible surface area (ASA) and physicochemical properties, i.e. positive charge and side chain interaction parameter. Due to the difficulty to obtain the conserved motifs by conventional motif analysis, maximal dependence decomposition (MDD) has been applied to obtain statistically significant conserved motifs. Support vector machine (SVM) is applied to generate predictive model for each MDD-clustered motif. According to five-fold cross-validation, the MDD-clustered SVMs could achieve an accuracy of 0.902, and provides a promising performance in an independent test set. The effectiveness of the model was demonstrated on the correct identification of previously reported S-nitrosylation sites of Bos taurus dimethylarginine dimethylaminohydrolase 1 (DDAH1) and human hemoglobin subunit beta (HBB). Finally, the MDD-clustered model was adopted to construct an effective web-based tool, named SNOSite (http://csb.cse.yzu.edu.tw/SNOSite/), for identifying S-nitrosylation sites on the uncharacterized protein sequences