431 resultados para STRUCTURAL OPTIMIZATION


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Peptidyl-tRNA hydrolase cleaves the ester bond between tRNA and the attached peptide in peptidyl-tRNA in order to avoid the toxicity resulting from its accumulation and to free the tRNA available for further rounds in protein synthesis. The structure of the enzyme from Mycobacteritan tuberculosis has been determined in three crystal forms. This structure and the structure of the enzyme frorn Escherichia coli in its crystal differ substantially on account of the binding of the C terminus of the E. coli enzyme to the peptide-binding site of a neighboring molecule in the crystal. A detailed examination of this difference led to an elucidation of the plasticity of the binding site of the enzyme. The peptide-binding site of the enzyme is a cleft between the body, of the molecule and a polypepticle Y stretch involving a loop and a helix. This stretch is in the open conformation when the enzyme is in the free state as in the crystals of M. tuberculosis peptidyl-tRNA hydrolase. Furthermore, there is no physical continuity between the tRNA and the peptide-binding sites. The molecule in the E. coli crystal mimics the peptide-bound enzyme molecule. The peptide stretch referred to earlier now closes on the bound peptide. Concurrently, a channel connecting the tRNA and the peptide-binding site opens primarily through the concerted movement of two residues. Thus, the crystal structure of M. tuberculosis peptidyl-tRNA hydrolase when compared with the crystal structure of the E. coli enzyme, leads to a model of structural changes associated with enzyme action on the basis of the plasticity of the molecule. (c) 2007 Elsevier Ltd. All rights reserved.

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Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

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Hole-doped perovskites such as La1-xCaxMnO3 present special magnetic and magnetotransport properties, and it is commonly accepted that the local atomic structure around Mn ions plays a crucial role in determining these peculiar features. Therefore experimental techniques directly probing the local atomic structure, like x-ray absorption spectroscopy (XAS), have been widely exploited to deeply understand the physics of these compounds. Quantitative XAS analysis usually concerns the extended region [extended x-ray absorption fine structure (EXAFS)] of the absorption spectra. The near-edge region [x-ray absorption near-edge spectroscopy (XANES)] of XAS spectra can provide detailed complementary information on the electronic structure and local atomic topology around the absorber. However, the complexity of the XANES analysis usually prevents a quantitative understanding of the data. This work exploits the recently developed MXAN code to achieve a quantitative structural refinement of the Mn K-edge XANES of LaMnO3 and CaMnO3 compounds; they are the end compounds of the doped manganite series LaxCa1-xMnO3. The results derived from the EXAFS and XANES analyses are in good agreement, demonstrating that a quantitative picture of the local structure can be obtained from XANES in these crystalline compounds. Moreover, the quantitative XANES analysis provides topological information not directly achievable from EXAFS data analysis. This work demonstrates that combining the analysis of extended and near-edge regions of Mn K-edge XAS spectra could provide a complete and accurate description of Mn local atomic environment in these compounds.

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An effective transcriptional response to redox stimuli is of particular importance for Mycobacterium tuberculosis, as it adapts to the environment of host alveoli and macrophages. The M. tuberculosis a factor sigma(L) regulates the expression of genes involved in cell-wall and polyketide syntheses. sigma(L) interacts with the cytosolic anti-sigma domain of a membrane-associated protein, RslA. Here we demonstrate that RslA binds Zn2+ and can sequester sigma(L) in a reducing environment. In response to an oxidative stimulus, proximal cysteines in the CXXC motif of RslA form a disulfide bond, releasing bound Zn2+. This results in a substantial rearrangement of the sigma(L)/RslA complex, leading to an 8-fold decrease in the affinity of RslA for sigma(L). The crystal structure of the -35-element recognition domain of sigma(L), sigma(L)(4), bound to RslA reveals that RslA inactivates sigma(L) by sterically occluding promoter DNA and RNpolymerase binding sites. The crystal structure further reveals that the cysteine residues that coordinate Zn2+ in RslA are solvent exposed in the complex, thus providing a structural basis for the redox sensitivity of RslA. The biophysical parameters of sigma(L)/RslA interactions provide a template for understanding how variations in the rate of Zn2+ release and associated conformational changes could regulate the activity of a Zn2+-associated anti-sigma factor. (C) 2010 Elsevier Ltd. All rights reserved.

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Hydrothermal treatment of a slurry of badly crystalline (beta(bc)) nickel hydroxide at different temperatures (65-170 degrees C) results in the progressive ordering of the structure by the step-wise elimination of disorders. Interstratification is eliminated at 140 degrees C, while cation vacancies are eliminated at 170 degrees C. A small percentage of stacking faults continue to persist even in `crystalline' samples. Electrochemical investigations show that the crystalline nickel hydroxide has a very low (0.4 e/Ni) reversible charge storage capacity. An incidence of at least 15% stacking faults combined with cation vacancies is essential for nickel hydroxide to perform close to its theoretical (1 e/ Ni) discharge capacity. (c) 2005 The Electrochemical Society.

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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

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Background: MHC/HLA class II molecules are important components of the immune system and play a critical role in processes such as phagocytosis. Understanding peptide recognition properties of the hundreds of MHC class II alleles is essential to appreciate determinants of antigenicity and ultimately to predict epitopes. While there are several methods for epitope prediction, each differing in their success rates, there are no reports so far in the literature to systematically characterize the binding sites at the structural level and infer recognition profiles from them. Results: Here we report a new approach to compare the binding sites of MHC class II molecules using their three dimensional structures. We use a specifically tuned version of our recent algorithm, PocketMatch. We show that our methodology is useful for classification of MHC class II molecules based on similarities or differences among their binding sites. A new module has been used to define binding sites in MHC molecules. Comparison of binding sites of 103 MHC molecules, both at the whole groove and individual sub-pocket levels has been carried out, and their clustering patterns analyzed. While clusters largely agree with serotypic classification, deviations from it and several new insights are obtained from our study. We also present how differences in sub-pockets of molecules associated with a pair of autoimmune diseases, narcolepsy and rheumatoid arthritis, were captured by PocketMatch(13). Conclusion: The systematic framework for understanding structuralvariations in MHC class II molecules enables large scale comparison of binding grooves and sub-pockets, which is likely to have direct implications towards predicting epitopes and understanding peptide binding preferences.

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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

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Background: MHC/HLA class II molecules are important components of the immune system and play a critical role in processes such as phagocytosis. Understanding peptide recognition properties of the hundreds of MHC class II alleles is essential to appreciate determinants of antigenicity and ultimately to predict epitopes. While there are several methods for epitope prediction, each differing in their success rates, there are no reports so far in the literature to systematically characterize the binding sites at the structural level and infer recognition profiles from them. Results: Here we report a new approach to compare the binding sites of MHC class II molecules using their three dimensional structures. We use a specifically tuned version of our recent algorithm, PocketMatch. We show that our methodology is useful for classification of MHC class II molecules based on similarities or differences among their binding sites. A new module has been used to define binding sites in MHC molecules. Comparison of binding sites of 103 MHC molecules, both at the whole groove and individual sub-pocket levels has been carried out, and their clustering patterns analyzed. While clusters largely agree with serotypic classification, deviations from it and several new insights are obtained from our study. We also present how differences in sub-pockets of molecules associated with a pair of autoimmune diseases, narcolepsy and rheumatoid arthritis, were captured by PocketMatch(13). Conclusion: The systematic framework for understanding structural variations in MHC class II molecules enables large scale comparison of binding grooves and sub-pockets, which is likely to have direct implications towards predicting epitopes and understanding peptide binding preferences.

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The complex crystallizes in the space group P21/c with four formula units in a unit cell of dimensionsa= 12.747, b= 7.416, c= 17.894 A and/3= 90.2 °. The structure has been solved by the symbolic addition procedure using three dimensional photographic data and refined to an R value of 0.079 for 2019 observed reflexions. The pyramidal nature of the two hetero nitrogen atoms in the antipyrine molecule is inter:nediate between that observed in free antipyrine and in some of its metal complexes. The molecule is more polar than that in crystals of free antipyrine but less so compared with that in metal complexes. In the salicylic acid molecule, the hydroxyl group forms an internal hydrogen bond with one of the oxygen atoms in the carboxyl group. The association between the salicylic acid and the antipyrine molecules is achieved through an intermolecular hydrogen bond with the other carboxyl oxygen atom in the salicylic acid molecule as the proton donor and the carboxyl oxygen atom of the antipyrine molecule as the acceptor

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We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

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The problem of identification of parameters of a beam-moving oscillator system based on measurement of time histories of beam strains and displacements is considered. The governing equations of motion here have time varying coefficients. The parameters to be identified are however time invariant and consist of mass, stiffness and damping characteristics of the beam and oscillator subsystems. A strategy based on dynamic state estimation method, that employs particle filtering algorithms, is proposed to tackle the identification problem. The method can take into account measurement noise, guideway unevenness, spatially incomplete measurements, finite element models for supporting structure and moving vehicle, and imperfections in the formulation of the mathematical models. Numerical illustrations based on synthetic data on beam-oscillator system are presented to demonstrate the satisfactory performance of the proposed procedure.

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A detailed mechanics based model is developed to analyze the problem of structural instability in slender aerospace vehicles. Coupling among the rigid-body modes, the longitudinal vibrational modes and the transverse vibrational modes due to asymmetric lifting-body cross-section are considered. The model also incorporates the effects of aerodynamic pressure and the propulsive thrust of the vehicle. The model is one-dimensional, and it can be employed to idealized slender vehicles with complex shapes. Condition under which a flexible body with internal stress waves behaves like a perfect rigid body is derived. Two methods are developed for finite element discretization of the system: (1) A time-frequency Fourier spectral finite element method and (2) h-p finite element method. Numerical results using the above methods are presented in Part II of this paper. (C) 2010 Elsevier Ltd. All rights reserved.

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Purpose: A number of proteome studies have been performed recently to identify pheromone-related protein expression and their molecular function using genetically modified rodents' urine. However, no such studies have used Indian commensal rodents; interestingly, in a previous investigation, we confirmed the presence of volatile molecules in commensal rodents urine and these molecules seem to be actively involved in pheromonal communication. Therefore, the present study aims to identify the major urinary protein [MUP] present in commensal rat urine, which will help us to understand the protein's expression pattern and intrinsic properties among the rodents globally. Experimental Design: Initially, the total urinary proteins were separated by 1-D and 2-D electrophoresis and then subsequently analyzed by Matrix Assisted Laser Desorption Ionization-Time of Flight and Mass Spectrometer (MALDI-TOF/MS). Furthermore, they were then fragmented with the aid of a Tandem Mass Spectrometer (TOF/TOF) and the identified sequences aligned and confirmed using similarity with the deduced primary structures of members of the lipocalin superfamily.Results: The SDS-PAGE protein profiles showed distinct proteins with molecular masses of 15, 22.4, 25, 28, 42, 50, 55, 68, and 91 kDa. Of these proteins, the 22.4 kDa protein was considered to be target candidate. When 2D electrophoresis was carried out, about similar to 50 spots were detected with different masses and various pI ranges. The 22.4 kDa protein was found to have a pI of about 4.9. This 22.4 kDa protein spot was digested and subjected to mass spectrometry; it was identified as rat MUP. The fragmented peptides from the rat MUP at 935, 1026, 1192, and 1303 m/z were further fragmented with the aid of MS/MS and generated de novo sequence and this confirmed this protein to be the MUP present in the urine of commensal rats.Conclusion: The present investigation confirms the presence of MUP with a molecular mass of 22.4 kDa in the urine of commensal rats. This protein may be involved in the binding of volatile molecules and opens up a discussion about how volatile and non-volatile molecules in the commensal rats' urine may contribute chemo-communication.