Maltose Binding Protein Is Partially Structured in Its Molten Globule State

Seven double cysteine mutants of maltose binding protein (MBP) were generated with one each in the active cleft at position 298 and the second cysteine distributed over both domains of the protein. These cysteines were spin labeled and distances between the labels in biradical pairs determined by pulsed double electron-electron resonance (DEER) measurements. The values were compared with theoretical predictions of distances between the labels in biradicals constructed by molecular modeling from the crystal structure of MBP without maltose and were found to be in excellent agreement. MBP is in a molten globule state at pH 3.3 and is known to still bind its substrate maltose. The nitroxide spin label was sufficiently stable under these conditions. In preliminary experiments, DEER measurements were carried out with one of the mutants yielding a broad distance distribution as was to be expected if there is no explicit tertiary structure and the individual helices pointing into all possible directions.

Device Fabrication of insoluble donor-acceptor-donor structured molecule by pulsed laser deposition- A comparative study using different laser source

Many of the conducting polymers though having good material property are not solution processable. Hence an alternate method of fabrication of film by pulsed laser deposition, was explored in this work. PDTCPA, a donor-acceptor-donor type of polymer having absorption from 900 nm to 300 nm was deposited by both UV and IR laser to understand the effect of deposition parameters on the film quality. It was observed that the laser ablation of PDTCPA doesn't alter its chemical structure hence retaining the chemical integrity of the polymer. Microscopic studies of the ablated film shows that the IR laser ablated films were particulate in nature while UV laser ablated films are deposited as smooth continuous layer. The morphology of the film influences its electrical characteristics as current-voltage characteristic of these films shows that films deposited by UV laser are p rectifying while those by IR laser are more of resistor in nature.

Information content of molecular graph and prediction of gas phase thermal entropy of organic compounds

Entropy is a fundamental thermodynamic property that has attracted a wide attention across domains, including chemistry. Inference of entropy of chemical compounds using various approaches has been a widely studied topic. However, many aspects of entropy in chemical compounds remain unexplained. In the present work, we propose two new information-theoretical molecular descriptors for the prediction of gas phase thermal entropy of organic compounds. The descriptors reflect the bulk and size of the compounds as well as the gross topological symmetry in their structures, all of which are believed to determine entropy. A high correlation () between the entropy values and our information-theoretical indices have been found and the predicted entropy values, obtained from the corresponding statistically significant regression model, have been found to be within acceptable approximation. We provide additional mathematical result in the form of a theorem and proof that might further help in assessing changes in gas phase thermal entropy values with the changes in molecular structures. The proposed information-theoretical molecular descriptors, regression model and the mathematical result are expected to augment predictions of gas phase thermal entropy for a large number of chemical compounds.

Ground motion prediction equation considering combined dataset of recorded and simulated ground motions

Himalayan region is one of the most active seismic regions in the world and many researchers have highlighted the possibility of great seismic event in the near future due to seismic gap. Seismic hazard analysis and microzonation of highly populated places in the region are mandatory in a regional scale. Region specific Ground Motion Predictive Equation (GMPE) is an important input in the seismic hazard analysis for macro- and micro-zonation studies. Few GMPEs developed in India are based on the recorded data and are applicable for a particular range of magnitudes and distances. This paper focuses on the development of a new GMPE for the Himalayan region considering both the recorded and simulated earthquakes of moment magnitude 5.3-8.7. The Finite Fault simulation model has been used for the ground motion simulation considering region specific seismotectonic parameters from the past earthquakes and source models. Simulated acceleration time histories and response spectra are compared with available records. In the absence of a large number of recorded data, simulations have been performed at unavailable locations by adopting Apparent Stations concept. Earthquakes recorded up to 2007 have been used for the development of new GMPE and earthquakes records after 2007 are used to validate new GMPE. Proposed GMPE matched very well with recorded data and also with other highly ranked GMPEs developed elsewhere and applicable for the region. Comparison of response spectra also have shown good agreement with recorded earthquake data. Quantitative analysis of residuals for the proposed GMPE and region specific GMPEs to predict Nepal-India 2011 earthquake of Mw of 5.7 records values shows that the proposed GMPE predicts Peak ground acceleration and spectral acceleration for entire distance and period range with lower percent residual when compared to exiting region specific GMPEs. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

D-A-D-structured conducting polymer-modified electrodes for detection of lead(II) ions in water

Donor-acceptor-donor-structured thiophene derivative-based conducting polymer poly(7,9-dithiophene-2yl-8H-cyclopentaa]acenaphthalene-8-one) was chemically synthesized. This polymer was used to modify both glassy-carbon and carbon-paste electrode, which was used to detect lead(II) ions present in water in the range of 1 mM to 0.1 mu M. Cyclic voltammetry confirms the formation of the co-ordination complex between the soft segment of polymer and the dissolved lead ion. Anodic stripping voltammetry was carried out by the modified electrode to determine the lower limit of detection of dissolved lead(II) species in the solution. Differential adsorptive stripping and impedance measurements were also conducted to find the lowest possible response of the as-synthesized polymer to lead(II) ion in water. The electrochemical performance of the modified electrodes at different pH (4, 7 and 9) environments was carried out by stripping voltammetry, to get optimum sensitivity and stability under these conditions. Finally, interference analysis was carried out to detect the modified electrode's sensitivity towards lead ion affinity in water.

CFD Analysis of two phase flow with a prediction of torque demand of a Bi-lobe rotor of a mixing chamber

An attempt to study the fluid dynamic behavior of two phase flow comprising of solid and liquid with nearly equal density in a geometrical case that has an industrial significance in theareas like processing of polymers, food, pharma ceutical, paints. In this work,crystalline silica is considered as the dispersed medium in glycerin. In the CFD analysis carried out,the two phase components are considered to be premixed homogeneously at the initial state. The flow in a cylinder that has an axially driven bi-lobe rotor, a typical blender used in polymer industry for mixing or kneading to render the multi-component mixture to homogeneous condition is considered. A viscous, incompressible, isothermal flow is considered with an assumption that the components do not undergo any physical change and the solids are rigid and mix in fully wetting conditions. Silica with a particle diameter of 0.4 mm is considered and flow is analyzed for different mixing fractions. An industry standard CFD code is used for solving 3D-RANS equations. As the outcome of the study the torque demand by the bi-lobe rotor for different mixture fractions which are estimated show a behavioral consistency to the expected physical phenomena occurring in the domain considered.

Prediction of the stiffness of nanoclay-polypropylene composites using a monte carlo finite element analysis approach

The present work deals with the prediction of stiffness of an Indian nanoclay-reinforced polypropylene composite (that can be termed as a nanocomposite) using a Monte Carlo finite element analysis (FEA) technique. Nanocomposite samples are at first prepared in the laboratory using a torque rheometer for achieving desirable dispersion of nanoclay during master batch preparation followed up with extrusion for the fabrication of tensile test dog-bone specimens. It has been observed through SEM (scanning electron microscopy) images of the prepared nanocomposite containing a given percentage (3–9% by weight) of the considered nanoclay that nanoclay platelets tend to remain in clusters. By ascertaining the average size of these nanoclay clusters from the images mentioned, a planar finite element model is created in which nanoclay groups and polymer matrix are modeled as separate entities assuming a given homogeneous distribution of the nanoclay clusters. Using a Monte Carlo simulation procedure, the distribution of nanoclay is varied randomly in an automated manner in a commercial FEA code, and virtual tensile tests are performed for computing the linear stiffness for each case. Values of computed stiffness modulus of highest frequency for nanocomposites with different nanoclay contents correspond well with the experimentally obtained measures of stiffness establishing the effectiveness of the present approach for further applications.

A Donor-Acceptor-Donor Structured Organic Conductor with S center dot center dot center dot S Chalcogen Bonding

A novel thiophene derivative 7,9-di(thiophen-2-yl)-8H-cyclopentaa]acenaphthylen-8-one (DTCPA) is shown to exhibit high electrical conductivity (1.97 x 10(-2) +/- 0.0018 S/cm at RT) in the crystalline state. The material shows two orders of increase in conductivity from normal solid to single crystalline state. The crystal structure has S center dot center dot center dot S chalcogen bonding, C-H center dot center dot center dot O hydrogen bonding, and pi center dot center dot center dot pi stacking as the major intermolecular interactions. The nature and strength of the S center dot center dot center dot S interactions in this structure have been evaluated by theoretical charge density analysis, and its contribution to the crystal packing quantified by Hirshfeld surface analysis. Further, thermal and morphological characterizations have been carried out, and the second harmonic generation (SHG) efficiency has been measured using the Kurtz-Perry method.

Intelligent prediction of ground vibration in coal formations using ANN

The present paper details the prediction of blast induced ground vibration, using artificial neural network. The data was generated from five different coal mines. Twenty one different parameters involving rock mass parameters, explosive parameters and blast design parameters, were used to develop the one comprehensive ANN model for five different coal bearing formations. A total of 131 datasets was used to develop the ANN model and 44 datasets was used to test the model. The developed ANN model was compared with the USBM model. The prediction capability to predict blast induced ground vibration, of the comprehensive ANN model was found to be superior.

Cybernetic modeling of adaptive prediction of environmental changes by microorganisms

Microorganisms exhibit varied regulatory strategies such as direct regulation, symmetric anticipatory regulation, asymmetric anticipatory regulation, etc. Current mathematical modeling frameworks for the growth of microorganisms either do not incorporate regulation or assume that the microorganisms utilize the direct regulation strategy. In the present study, we extend the cybernetic modeling framework to account for asymmetric anticipatory regulation strategy. The extended model accurately captures various experimental observations. We use the developed model to explore the fitness advantage provided by the asymmetric anticipatory regulation strategy and observe that the optimal extent of asymmetric regulation depends on the selective pressure that the microorganisms experience. We also explore the importance of timing the response in anticipatory regulation and find that there is an optimal time, dependent on the extent of asymmetric regulation, at which microorganisms should respond anticipatorily to maximize their fitness. We then discuss the advantages offered by the cybernetic modeling framework over other modeling frameworks in modeling the asymmetric anticipatory regulation strategy. (C) 2013 Published by Elsevier Inc.

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: Implications for three-dimensional modeling

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naive Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (approximate to 85%) and specific (approximate to 95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. Proteins 2014; 82:1219-1234. (c) 2013 Wiley Periodicals, Inc.

Synthesis of self-light-scattering wrinkle structured ZnO photoanode by sol-gel method for dye-sensitized solar cells

A special morphological zinc oxide (ZnO) photoanode for dye-sensitized solar cell was fabricated by simple sol-gel drop casting technique. This film shows a wrinkled structure resembling the roots of banyan tree, which acts as an effective self scattering layer for harvesting more visible light and offers an easy transport path for photo-injected electrons. These ZnO electrode of low thickness (similar to 5 mu m) gained an enhanced short-circuit current density of 6.15 mA/cm(2), open-circuit voltage of 0.67 V, fill factor of 0.47 and overall conversion efficiency of 1.97 % under 1 sun illumination. This shows a high conversion efficiency and a superior performance than that of ZnO nanoparticle-based photoanode (eta similar to 1.13 %) of high thickness (similar to 8 mu m).

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.