Quantum clustering and network analysis of MD simulation trajectories to probe the conformational ensembles of protein-ligand interactions

In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.

Effect of convection on domain growth during demixing transitions in fluids

Current analytical work on the effect of convection on the late stages of spinodal decomposition in liquids is briefly described. The morphology formed during the spinodal decomposition process depends on the relative composition of the two species. Droplet spinodal decomposition occurs when the concentration of one of the species is small. Convective transport has a significant effect on the scaling laws in the late-stage coarsening of droplets in translational or shear flows. In addition, convective transport could result in an attractive interaction between non-Brownian droplets which could lead to coalescence. The effect of convective transport for the growth of random interfaces in a near-symmetric quench was analysed using an area distribution function, which gives the distribution of surface area of the interface in curvature space. It was found that the curvature of the interface decreases proportional to time t in the late stages of spinodal decomposition, and the surface area also decreases proportional to t.

DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins

Depth measures the extent of atom/residue burial within a protein. It correlates with properties such as protein stability, hydrogen exchange rate, protein-protein interaction hot spots, post-translational modification sites and sequence variability. Our server, DEPTH, accurately computes depth and solvent-accessible surface area (SASA) values. We show that depth can be used to predict small molecule ligand binding cavities in proteins. Often, some of the residues lining a ligand binding cavity are both deep and solvent exposed. Using the depth-SASA pair values for a residue, its likelihood to form part of a small molecule binding cavity is estimated. The parameters of the method were calibrated over a training set of 900 high-resolution X-ray crystal structures of single-domain proteins bound to small molecules (molecular weight < 1.5 KDa). The prediction accuracy of DEPTH is comparable to that of other geometry-based prediction methods including LIGSITE, SURFNET and Pocket-Finder (all with Matthew's correlation coefficient of similar to 0.4) over a testing set of 225 single and multi-chain protein structures. Users have the option of tuning several parameters to detect cavities of different sizes, for example, geometrically flat binding sites. The input to the server is a protein 3D structure in PDB format. The users have the option of tuning the values of four parameters associated with the computation of residue depth and the prediction of binding cavities. The computed depths, SASA and binding cavity predictions are displayed in 2D plots and mapped onto 3D representations of the protein structure using Jmol. Links are provided to download the outputs. Our server is useful for all structural analysis based on residue depth and SASA, such as guiding site-directed mutagenesis experiments and small molecule docking exercises, in the context of protein functional annotation and drug discovery.

The repertoire of protein kinases encoded in the draft version of the human genome: atypical variations and uncommon domain combinations

Background: Phosphorylation by protein kinases is central to cellular signal transduction. Abnormal functioning of kinases has been implicated in developmental disorders and malignancies. Their activity is regulated by second messengers and by the binding of associated domains, which are also influential in translocating the catalytic component to their substrate sites, in mediating interaction with other proteins and carrying out their biological roles. Results: Using sensitive profile-search methods and manual analysis, the human genome has been surveyed for protein kinases. A set of 448 sequences, which show significant similarity to protein kinases and contain the critical residues essential for kinase function, have been selected for an analysis of domain combinations after classifying the kinase domains into subfamilies. The unusual domain combinations in particular kinases suggest their involvement in ubiquitination pathways and alternative modes of regulation for mitogen-activated protein kinase kinases (MAPKKs) and cyclin-dependent kinase (CDK)-like kinases. Previously unexplored kinases have been implicated in osteoblast differentiation and embryonic development on the basis of homology with kinases of known functions from other organisms. Kinases potentially unique to vertebrates are involved in highly evolved processes such as apoptosis, protein translation and tyrosine kinase signaling. In addition to coevolution with the kinase domain, duplication and recruitment of non-catalytic domains is apparent in signaling domains such as the PH, DAG-PE, SH2 and SH3 domains. Conclusions: Expansion of the functional repertoire and possible existence of alternative modes of regulation of certain kinases is suggested by their uncommon domain combinations. Experimental verification of the predicted implications of these kinases could enhance our understanding of their biological roles.

A new parallel overlapped domain decomposition method for nonlinear dynamic finite element analysis

In this paper a new parallel algorithm for nonlinear transient dynamic analysis of large structures has been presented. An unconditionally stable Newmark-beta method (constant average acceleration technique) has been employed for time integration. The proposed parallel algorithm has been devised within the broad framework of domain decomposition techniques. However, unlike most of the existing parallel algorithms (devised for structural dynamic applications) which are basically derived using nonoverlapped domains, the proposed algorithm uses overlapped domains. The parallel overlapped domain decomposition algorithm proposed in this paper has been formulated by splitting the mass, damping and stiffness matrices arises out of finite element discretisation of a given structure. A predictor-corrector scheme has been formulated for iteratively improving the solution in each step. A computer program based on the proposed algorithm has been developed and implemented with message passing interface as software development environment. PARAM-10000 MIMD parallel computer has been used to evaluate the performances. Numerical experiments have been conducted to validate as well as to evaluate the performance of the proposed parallel algorithm. Comparisons have been made with the conventional nonoverlapped domain decomposition algorithms. Numerical studies indicate that the proposed algorithm is superior in performance to the conventional domain decomposition algorithms. (C) 2003 Elsevier Ltd. All rights reserved.

Transmission electron microscopy study of domain structures in ferroelectric SrBi2Nb2O9 ceramics

A transmission electron microscopy study has been carried out on the domain structures of SrBi2Nb2O9 (SBN) ferroelectric ceramics which belong to the Aurivillius family of bismuth layered perovskite oxides. SBN is a potential candidate for Ferroelectric Random access memory (FeRAM) applications. The 90° ferroelectric domains and antiphase boundaries (APBs) were identified with dark field imaging techniques using different superlattice reflections which arise as a consequence of octahedral rotations and cationic shifts. The 90° domain walls are irregular in shape without any faceting. The antiphase boundaries are less dense compared to that of SrBi2Ta2O9(SBT). The electron microscopy observations are correlated with the polarization fatigue nature of the ceramic where the domain structures possibly play a key role in the fatigue- free behavior of the Aurivillius family of ferroelectric oxides.

Electrical and optical characterization of conducting polymers by THz time-domain spectroscopy

The absorption and index of refraction of polypyrrole (PPy) and poly-3-methylthiophene (PMeT), from low frequencies up to 4 THz, have been measured by tera-Herz (THz) time-domain spectroscopy. The complex conductance was obtained over this range of frequency. Highly conducting metallic samples follow the Drude model, whereas less conducting ones fit the localization-modified Drude model. The carrier scattering time and mobility in conducting polymers can be directly determined from these measurements.

The carboxy terminal WD domain of the pre-mRNA splicing factor Prp17p is critical for function

In Saccharomyces cerevisiae, Prp17p is required for the efficient completion of the second step of pre-mRNA splicing. The function and interacting factors for this protein have not been elucidated. We have performed a mutational analysis of yPrp17p to identify protein domains critical for function. A series of deletions were made throughout the region spanning the N-terminal 158 amino acids of the protein, which do not contain any identified structural motifs. The C-terminal portion (amino acids 160–455) contains a WD domain containing seven WD repeats. We determined that a minimal functional Prp17p consists of the WD domain and 40 amino acids N-terminal to it. We generated a three-dimensional model of the WD repeats in Prp17p based on the crystal structure of the [beta]-transducin WD domain. This model was used to identify potentially important amino acids for in vivo functional characterization. Through analysis of mutations in four different loops of Prp17p that lie between [beta] strands in the WD repeats, we have identified four amino acids, 235TETG238, that are critical for function. These amino acids are predicted to be surface exposed and may be involved in interactions that are important for splicing. Temperature-sensitive prp17 alleles with mutations of these four amino acids are defective for the second step of splicing and are synthetically lethal with a U5 snRNA loop I mutation, which is also required for the second step of splicing. These data reinforce the functional significance of this region within the WD domain of Prp17p in the second step of splicing.

Synthesis and DNA binding studies of Ni(II), Co(II), Cu(II) and Zn(II) metal complexes of N(1),N(5)-bis[pyridine-2-methylene]-thiocarbohydrazone Schiff-base ligand

The thiocarbohydrazone Schiff-base ligand with a nitrogen and sulphur donor was synthesized through condensation of pyridine-2-carbaldehyde and thiocarbohydrazide. Schiff-base ligands have the ability to conjugate with metal salts. A series of metal complexes with a general formula [MCl(2)(H(2)L)]center dot nH(2)O (M=Ni, Co, Cu and Zn) were synthesized by forming complexes of the N(1),N5-bis[pyridine-2-methylene]thiocarbohydrazone (H2L) Schiff-base ligand. These metal complexes and ligand were characterized by using ultraviolet-visible (UV-Vis), Fourier Transform Infrared (FT-IR), (1)H and (13)C NMR spectroscopy and mass spectroscopy, physicochemical characterization, CHNS and conductivity. The biological activity of the synthesized ligand was investigated by using Escherichia coli DNA as target. The DNA interaction of the synthesized ligand and complexes on E. coli plasmid DNA was investigated in the aqueous medium by UV-Vis spectroscopy and the binding constant (K(b)) was calculated. The DNA binding studies showed that the metal complexes had an improved interaction due to trans-geometrical isomers of the complexes than ligand isomers in cis-positions. (C) 2011 Elsevier B.V. All rights reserved.

Domain-wall creep driven by spin torque in nanoscale ferromagnetic cylinders

We have explored the mechanism of spin-torque-driven domain-wall (DW) depinning in cylindrical nanowires of nickel using noise in electrical resistance. We find that the spectral slope of noise is a sensitive probe to the DW kinetics that reveals a creeplike behavior of the DWs at the depinning threshold, and diffusive DW motion at higher spin-torque drive. Different regimes of DW kinetics were characterized by universal kinetic exponents.

Speech Enhancement using Intra-frame Dependency in DCT Domain

In this paper, we present a new speech enhancement approach, that is based on exploiting the intra-frame dependency of discrete cosine transform (DCT) domain coefficients. It can be noted that the existing enhancement techniques treat the transformdomain coefficients independently. Instead of this traditional approach of independently processing the scalars, we split the DCT domain noisy speech vector into sub-vectors and each sub-vector is enhanced independently. Through this sub-vector based approach, the higher dimensional enhancement advantage, viz. non-linear dependency, is exploited. In the developed method, each clean speech sub-vector is modeled using a Gaussian mixture (GM) density. We show that the proposed Gaussian mixture model (GMM) based DCT domain method, using sub-vector processing approach, provides better performance than the conventional approach of enhancing the transform domain scalar components independently. Performance improvement over the recently proposed GMM based time domain approach is also shown.

Linear Filtering in MDCT domain

In this paper, expressions for convolution multiplication properties of MDCT are derived starting from the equivalent DFT representations. Using these expressions, methods for implementing linear filtering through block convolution in the MDCT domain are presented. The implementation is exact for symmetric filters and approximate for non-symmetric filters in the case of rectangular window based MDCT. For a general MDCT window function, the filtering is done on the windowed segments and hence the convolution is approximate for symmetric as well as non-symmetric filters. This approximation error is shown to be perceptually insignificant for symmetric impulse response filters. Moreover, the inherent $50 \%$ overlap between adjacent frames used in MDCT computation does reduce this approximation error similar to smoothing of other block processing errors. The presented techniques are useful for compressed domain processing of audio signals.

GMM basedbayesian approach to speech enhancement in signal/transform domain

Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator.The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.