Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

Background: Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results: In the present analysis, starting from C alpha positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions: Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens.

Area Optimized H.264 Intra Prediction Architecture for 1080p HD Resolution

High performance video standards use prediction techniques to achieve high picture quality at low bit rates. The type of prediction decides the bit rates and the image quality. Intra Prediction achieves high video quality with significant reduction in bit rate. This paper present an area optimized architecture for Intra prediction, for H.264 decoding at HDTV resolution with a target of achieving 60 fps. The architecture was validated on Virtex-5 FPGA based platform. The architecture achieves a frame rate of 64 fps. The architecture is based on multi-level memory hierarchy to reduce latency and ensure optimum resources utilization. It removes redundancy by reusing same functional blocks across different modes. The proposed architecture uses only 13% of the total LUTs available on the Xilinx FPGA XC5VLX50T.

HD resolution intra prediction architecture for H.264 decoder

High performance video standards use prediction techniques to achieve high picture quality at low bit rates. The type of prediction decides the bit rates and the image quality. Intra Prediction achieves high video quality with significant reduction in bit rate. This paper presents novel area optimized architecture for Intra prediction of H.264 decoding at HDTV resolution. The architecture has been validated on a Xilinx Virtex-5 FPGA based platform and achieved a frame rate of 64 fps. The architecture is based on multi-level memory hierarchy to reduce latency and ensure optimum resources utilization. It removes redundancy by reusing same functional blocks across different modes. The proposed architecture uses only 13% of the total LUTs available on the Xilinx FPGA XC5VLX50T.

Modified linear prediction method for directions of arrival estimation of narrow-band plane waves

A modified linear prediction (MLP) method is proposed in which the reference sensor is optimally located on the extended line of the array. The criterion of optimality is the minimization of the prediction error power, where the prediction error is defined as the difference between the reference sensor and the weighted array outputs. It is shown that the L2-norm of the least-squares array weights attains a minimum value for the optimum spacing of the reference sensor, subject to some soft constraint on signal-to-noise ratio (SNR). How this minimum norm property can be used for finding the optimum spacing of the reference sensor is described. The performance of the MLP method is studied and compared with that of the linear prediction (LP) method using resolution, detection bias, and variance as the performance measures. The study reveals that the MLP method performs much better than the LP technique.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

X-ray Structure of Gelonin at 1.8 Å Resolution

Gelonin is a single chain ribosome inactivating protein (RIP) with potential application in the treatment of cancer and AIDS. Diffraction quality crystals grown using PEG3350, belong to the space group P2(1), with it a = 49.4 Angstrom b = 44.9 Angstrom, c = 137.4 Angstrom and beta = 98.4 degrees, and contain two molecules in the asymmetric unit. Diffraction data collected to 1.8 Angstrom resolution has a R(m) value of 7.3%. Structure of gelonin has been solved by the molecular replacement method, using ricin A chain as the search model. Crystallographic refinement using X-PLOR resulted in a model for which the r.m.s deviations from ideal bond lengths and bond angles are 0.012 Angstrom and 2.7 degrees, respectively The final R-factor is 18.4% for 39,806 reflections for which I > 1.0 sigma(I).The C-alpha atoms of the two molecules in the asymmetric unit superpose to within 0.38 Angstrom for 247 atom pairs. The overall fold of gelonin is similar to that of other RIPs such as ricin A chain and alpha-momorcharin, the r.m.s.d. for C-alpha superpositions being 1.3 and 1.4 Angstrom, respectively The-catalytic residues (Glu166, Arg169 and Tyr113) in the active site form a hydrogen bond scheme similar to that observed in other RIPs. The conformation of Tyr74 in the active site, however, is significantly different from that in alpha-momorcharin. Three well defined water molecules are located in the active site cavity and one of them, X319, superposes to within 0.2 Angstrom of a corresponding water molecule in the structure of alpha-momorcharin. Any of the three could be the substrate water molecule in the hydrolysis reaction catalysed by gelonin.Difference electron density for a N-linked sugar moiety has been observed near only one of the two potential glycosylation sites in the sequence. The amino acid at position 239 has been established as Lys by calculation of omit electron density maps.The two cysteine residues in the sequence, Cys44 and Cys50, form a disulphide bond, and are therefore not available for disulphide conjugation with antibodies. Based on the structure, the region of the molecule that is involved in intradimer interactions is suggested to be suitable for introducing a Cys residue for purposes of conjugation with an antibody to produce useful immunotoxins.

A High-Resolution Transmission of the Precipitation Process in a Electron Microscopy Study Dilute Ti-N Alloy

The precipitation processes in dilute nitrogen alloys of titanium have been examined in detail by conventional transmission electron microscopy (CTEM) and high-resolution electron microscopy (HREM). The alloy Ti-2 at. pct N on quenching from its high-temperature beta phase field has been found to undergo early stages of decomposition. The supersaturated solid solution (alpha''-hcp) on decomposition gives rise to an intimately mixed, irresolvable product microstructure. The associated strong tweed contrast presents difficulties in understanding the characteristic features of the process. Therefore, HREM has been carried out with a view to getting a clear picture of the decomposition process. Studies on the quenched samples of the alloy suggest the formation of solute-rich zones of a few atom layers thick, randomly distributed throughout the matrix. On aging, these zones grow to a size beyond which the precipitate/matrix interfaces appear to become incoherent and the alpha' (tetragonal) product phase is seen distinctly. The structural details, the crystallography of the precipitation process, and the sequence of precipitation reaction in the system are illustrated.

Numerical prediction of load-displacement behaviors of adhesively bonded joints at different extension rates and temperatures

The present work focuses on simulation of nonlinear mechanical behaviors of adhesively bonded DLS (double lap shear) joints for variable extension rates and temperatures using the implicit ABAQUS solver. Load-displacement curves of DLS joints at nine combinations of extension rates and environmental temperatures are initially obtained by conducting tensile tests in a UTM. The joint specimens are made from dual phase (DP) steel coupons bonded with a rubber-toughened adhesive. It is shown that the shell-solid model of a DLS joint, in which substrates are modeled with shell elements and adhesive with solid elements, can effectively predict the mechanical behavior of the joint. Exponent Drucker-Prager or Von Mises yield criterion together with nonlinear isotropic hardening is used for the simulation of DLS joint tests. It has been found that at a low temperature (-20 degrees C), both Von Mises and exponent Drucker-Prager criteria give close prediction of experimental load-extension curves. However. at a high temperature (82 degrees C), Von Mises condition tends to yield a perceptibly softer joint behavior, while the corresponding response obtained using exponent Drucker-Prager criterion is much closer to the experimental load-displacement curve.

High-resolution refinement of orthorhombic bovine pancreatic phospholipase A2

The X-ray structure of recombinant bovine pancreatic phospholipase A(2) (PLA2), which specifically catalyzes the cleavage of the sn-2 acylester bond of phospholipids, has been refined at 1.5 Angstrom resolution. The crystal belongs to the space group P2(1)2(1)2(1) with unit-cell parameters a = 47.12, b = 64.59 and c = 38.14 Angstrom similar to the native enzyme reported previously by Dijkstra et nl. [J. Mel. Biol. (1981), 147, 97-123]. The refinement converged to an R value of 18.4% (R-free = 22.8%) for 16 374 reflections between 10.0 and 1.5 Angstrom resolution. The surface-loop residues (60-70) art: ordered in the present orthorhombic recombinant enzyme, but disordered in the trigonal recombinant enzyme. The active-site residues, His48, Asp99, and the catalytic water superimpose well with the trigonal form. Besides the catalytic water which is hydrogen bonded to His48, it is often seen that there is a second water attached to the same N atom of His48 and simultaneously hydrogen bonded to the O atom of Asp49. It is thought that the second water facilitates the tautomerism of His48 for enzyme catalysis, The catalytic water is also hydrogen bonded to the equatorial water coordinated to the calcium ion, In addition to the equatorial water, there is also an axial calcium water and the additional structural water. These five common water molecules are hydrogen bonded to the additional 16 water molecules in the present orthorhombic structure which may further enhance the structural integrity of the active site. Besides the protein and one calcium ion, a total of 134 water molecules were located in the present high-resolution refinement.

CSSP (Consensus Secondary Structure Prediction): a web-based server for structural biologists

Sequence-structure correlation studies are important in deciphering the relationships between various structural aspects, which may shed light on the protein-folding problem. The first step of this process is the prediction of secondary structure for a protein sequence of unknown three-dimensional structure. To this end, a web server has been created to predict the consensus secondary structure using well known algorithms from the literature. Furthermore, the server allows users to see the occurrence of predicted secondary structural elements in other structure and sequence databases and to visualize predicted helices as a helical wheel plot. The web server is accessible at http://bioserver1.physics.iisc.ernet.in/cssp/.

Crop Classification using Biologically-inspired Techniques with High Resolution Satellite Image

Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN

An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Novel ultrahigh resolution silverless photothermal imaging in obliquely deposited amorphous Se-Ge films

A new photothermal imaging process which utilizes no silver has been demonstrated in obliquely deposited Se-Ge films. Band-gap irradiation of Se-Ge films has been found to give rise to phases of the type SeOx, GeO, and Se as borne by x-ray initiated Auger electron spectroscopy and x-ray photoelectron spectroscopy. Annealing of SeOx leads to the formation of SeO2. The large (several orders of magnitude) difference in vapor pressures of SeO2 and Se-Ge films results in differential evaporation of the films when annealed around 200 °C, thereby leading to imaging. Such a large contrast in evaporation rates between the exposed and unexposed regions has great potential applications in high resolution image storage and phase holography. Applied Physics Letters is copyrighted by The American Institute of Physics.

Image reconstruction with laterally truncated projections in helical cone-beam CT: Linear prediction based projection completion techniques

Lateral or transaxial truncation of cone-beam data can occur either due to the field of view limitation of the scanning apparatus or iregion-of-interest tomography. In this paper, we Suggest two new methods to handle lateral truncation in helical scan CT. It is seen that reconstruction with laterally truncated projection data, assuming it to be complete, gives severe artifacts which even penetrates into the field of view. A row-by-row data completion approach using linear prediction is introduced for helical scan truncated data. An extension of this technique known as windowed linear prediction approach is introduced. Efficacy of the two techniques are shown using simulation with standard phantoms. A quantitative image quality measure of the resulting reconstructed images are used to evaluate the performance of the proposed methods against an extension of a standard existing technique.