27 resultados para Structure Prediction Servers

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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It was expected that there are a coil (289 similar to 325) and two a helix (alpha(1)368 similar to 373, alpha(2)381 similar to 388) structures in p53 protein C-terminal region based on its mRNA secondary structure template and Chou-Fasman's protein secondary structure principle of prediction. The result was conformed by the other four methods of protein secondary structure prediction that are based on the multiple sequence alignment (accuracy = 73.20%). Combine with the 31 amino acids crystal structure of the oligomerization, the three dimensional conformation of p53 C-terminal 108 residues was built using the SGI INDIGO(2) computer. This structure further expounds the relationship among those biological function domains of p53 C- terminus at three-dimensional level.

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Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor

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The primary mutation m.3460G > A occurs with a very low frequency (similar to 1%) in Chinese patients with Leber hereditary optic neuropathy (LHON). Up to now, there is no comprehensive study of Chinese patients harboring this mutation. We characterized six unrelated probands with m.3460G > A in this study, which were identified from 1,626 patients with LHON or suspected with LHON. The overall penetrance of LHON (25.6% [10/39]) in four pedigrees with m.3460G > A was substantially lower than those families with m.11778G > A (33.3% [619/1859]) as reported in our previous study. Intriguingly, family Le688 with a heteroplasmic m.3460G > A presented a lower penetrance (12.5%) than the other three families with a homoplasmic mutation. There is an elevated gender bias (affected male to affected female = 4:1) in the four families with m.3460G > A compared to those LHON families with m.11778G > A (2.4:1). Complete mtDNA sequencing indicated that the six matrilines belonged to haplogroups B4d1, F2, A5b, M12a, D4b2b, and D4b2, respectively. We did not identify any potential secondary mutation(s) that will affect or be associated with the penetrance of LHON in the six probands by using an evolutionary analysis and protein secondary-structure prediction. Taken together, our results suggested that the m.3460G > A mutation occurred multiple times in Chinese LHON patients. The heteroplasmic status of mutation m.3460G > A might influence the penetrance of LHON in family Le688.

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The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

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How to refine a near-native structure to make it closer to its native conformation is an unsolved problem in protein-structure and protein-protein complex-structure prediction. In this article, we first test several scoring functions for selecting locally resampled near-native protein-protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance-scaled Ideal-gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein-InteRaction Energy) for optimization and re-ranking. Significant improvement of final top-1 ranked structures over initial near-native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed.

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Thymidylate synthase (TS), an essential enzyme for catalyzing the biosynthesis of thymidylate, is a critical therapeutic target in cancer therapy. Recent studies have shown that TS functions as an RNA-binding protein by interacting with two different sequences on its own mRNA, thus, repressing translational efficiency. In this study, peptides binding TS RNA with high affinity were isolated using mRNA display from a large peptide library (>10(13) different sequences). The randomized library was subjected up to twelve rounds of in vitro selection and amplification. Comparing the amino acid composition of the selected peptides (12th round, R12) with those from the initial random library (round zero, R0), the basic and aromatic residues in the selected peptides were enriched significantly, suggesting that these peptide regions might be important in the peptide-TS mRNA interaction. Categorizing the amino acids at each random position based on their physicochemical properties and comparing the distributions with those of the initial random pool, an obvious basic charge characteristic was found at positions 1, 12, 17 and 18, suggesting that basic side chains participate in RNA binding. Secondary structure prediction showed that the selected peptides of R12 pool represented a helical propensity compared with R0 pool, and the regions were rich in basic residues. The electrophoretic gel mobility shift and in vitro translation assays showed that the peptides selected using mRNA display could bind TS RNA specifically and inhibit the translation of TS mRNA. Our results suggested that the identified peptides could be used as new TS inhibitors and developed to a novel class of anticancer agents.

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In order to carry out high-precision three-dimensional "integration" for the characteristics of the secondary seismic exploration for Biyang Depression, in the implementation process, through a combination of scientific research and production, summed up high-precision seismic acquisition, processing and interpretation technologies suitable for the eastern part of the old liberated areas, achieved the following results: 1. high-precision complex three-dimensional seismic exploration technology series suitable for shallow depression Biyang block group. To highlight the shallow seismic signal, apply goal-based observing system design, trail from the small panel to receive and protect the shallow treatment of a range of technologies; to explain the use of three-dimensional visualization and coherent combination of full-body three-dimensional fine interpretation identification of the 50-100 m below the unconformity surface and its formation of about 10 meters of the distribution of small faults and improve the small block and stratigraphic unconformity traps recognition. 2. high-precision series of three-dimensional seismic exploration technology suitable for deep depression Biyang low signal to noise ratio of information. Binding model using forward and lighting technology, wide-angle observation system covering the design, multiple suppression and raise the energy of deep seismic reflection processing and interpretation of detailed, comprehensive reservoir description, such as research and technology, identified a number of different types of traps. 3. high-precision seismic exploration technology series for the southern Biyang Depression high steep three-dimensional structure. The use of new technology of seismic wave scattering theory and high-precision velocity model based on pre-stack time migration and depth migration imaging of seismic data and other high-precision processing technology, in order to identify the southern steep slope of the local structure prediction and analysis of sandstone bedrock surface patterns provide a wealth of information.

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In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.

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A method for the prediction of gas permeabilities (P) through polymers from their chemical structure has been developed on the basis of the ratio of molar free volume to molar cohesive energy, V(f)/E(coh). The permeation of small gas molecules through polymer membranes is dependent on the chain packing density measured by V(f) and segmental motion of polymer chains measured by E(coh). But no simple relationship between P and V(f) or E(coh) alone was found. The permeability data of more than 60 polymers covering 7 orders of magnitude for six gases have been treated with linear regression analysis. All plots of log P vs. V(f)/E(coh) gave good straight lines. It is also found that a linear relationship holds when plotting both the intercepts and slopes of log P vs. V(f)/E(coh) lines against square of the diameters of gas molecules. Therefore, the permeabilities of all the non-swelling gases through a great variety of polymers can be estimated using two correlations above. Moreover, this method is more accurate than others in the literature and may found useful for the selection of gas separation or barrier membrane materials.

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A two-dimensional (2-D) vortex-induced vibration (VIV) prediction model for high aspect ratio (LID) riser subjected to uniform and sheared flow is studied in this paper. The nonlinear structure equations are considered. The near wake dynamics describing the fluctuating nature of vortex shedding is modeled using classical van der Pol equation. A new approach was applied to calibrate the empirical parameters in the wake oscillator model. Compared the predicted results with the experimental data and computational fluid dynamic (CFD) results. Good agreements are observed. It can be concluded that the present model can be used as simple computational tool in predicting some aspects of VIV of long flexible structures. (C) 2008 Elsevier Ltd. All rights reserved.

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The Reynolds-averaged Navier-Stokes equations for describing the turbulent flow in a straight square duct are formulated with two different turbulence models. The governing equations are then expanded as a multi-deck structure in a plane perpendicular to the streamwise direction, with each deck characterized by its dominant physical forces as commonly carried out in analytical work using triple-deck expansion. The resulting equations are numerically integrated using higher polynomial (H-P) finite element technique for each cross-sectional plane to be followed by finite difference representation in the streamwise direction until a fully developed state is reached. The computed results using the two different turbulence models show fair agreement with each other, and concur with the vast body of available experimental data. There is also general agreement between our results and the recent numerical works anisotropic k-epsilon turbulence model.

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Many diseases are believed to be related to abnormal protein folding. In the first step of such pathogenic structural changes, misfolding occurs in regions important for the stability of the native structure. This destabilizes the normal protein conformation, while exposing the previously hidden aggregation-prone regions, leading to subsequent errors in the folding pathway. Sites involved in this first stage can be deemed switch regions of the protein, and can represent perfect binding targets for drugs to block the abnormal folding pathway and prevent pathogenic conformational changes. In this study, a prediction algorithm for the switch regions responsible for the start of pathogenic structural changes is introduced. With an accuracy of 94%, this algorithm can successfully find short segments covering sites significant in triggering conformational diseases (CDs) and is the first that can predict switch regions for various CDs. To illustrate its effectiveness in dealing with urgent public health problems, the reason of the increased pathogenicity of H5N1 influenza virus is analyzed; the mechanisms of the pandemic swine-origin 2009 A(H1N1) influenza virus in overcoming species barriers and in infecting large number of potential patients are also suggested. It is shown that the algorithm is a potential tool useful in the study of the pathology of CDs because: (1) it can identify the origin of pathogenic structural conversion with high sensitivity and specificity, and (2) it provides an ideal target for clinical treatment.

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By the use of partial least squares (PLS) method and 27 quantum chemical descriptors computed by PM3 Hamiltonian, a statistically significant QSPR were obtained for direct photolysis quantum yields (Y) of selected Polychlorinated dibenzo-p-dioxins (PCDDs). The QSPR can be used for prediction. The direct photolysis quantum yields of the PCDDs are dependent on the number of chlorine atoms bonded with the parent structures, the character of the carbon-oxygen bonds, and molecular polarity. Increasing bulkness and polarity of PCDDs lead to decrease of log Y values. Increasing the frontier molecular orbital energies (E-lumo and E-homo) and heat of formation (HOF) values leads to increase of log Y values. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Based on some fundamental quantum chemical descriptors computed by PM3 Hamiltonian, by the use of partial least-squares (PLS) analysis, a significant quantitative structure-property relationship (QSPR) model for logK(ow) of polychlorinated dibenzo-p-dioxins and dibenzo-p-furans (PCDD/Fs) was obtained. The QSPR can be used for prediction. The intermolecular dispersive interactions and thus the bulkness of the PCDD/Fs are the main factors affecting the logK(ow). The more chlorines in the PCDD/F molecule, the greater the logK(ow) values. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Using first-principles band structure methods, we have systematically studied the electronic structures, magnetic stabilities, and half-metal properties of 3d transition-metal (TM) doped Rocksalt MgO compounds TMMg3O4 (TM = V, Cr, Mn, Fe, Co, and Ni). The calculations reveal that only CrMg3O4 has a ferromagnetic stability among the six compounds, which is explained by double-exchange mechanism. The magnetic stability is affected by the doping concentration of TM if the top valance band is composed of partially occupied t(2g) states. In addition, CrMg3O4 is a half-metallic ferromagnet. The origins of half-metallic and ferromagnetic properties are explored. The Curie temperature (T-c) of CrMg3O4 is 182 K. And it is hard for CrMg3O4 to deform due to the large bulk modulus and shear modulus, so it is a promising spintronic material. Our calculations provide the first available information on the magnetic properties of 3d TM-doped MgO.