884 resultados para Data structures
Resumo:
Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein `structure prediction' problem.
Resumo:
Two new one-dimensional heterometallic complexes, Mn3Na(L)(4)(CH3CO2)(MeOH)(2)]-(ClO4)(2)center dot 3H(2)O (1), Mn3Na(L)(4)(CH3CH2CO2)-(MeOH)(2)](ClO4)(2)center dot 2MeOH center dot H2O (2) LH2 = 2-methyl-2-(2-pyridyl)propane-1,3-diol], have been synthesized and characterized by X-ray crystallography. Both complexes feature Mn-II and Na-I ions in trigonal-prismatic geometries that are linked to octahedral Mn-IV ions by alkoxy bridges. Variable-temperature direct- and alternating-current magnetic susceptibility data indicated a spin ground state of S = 11/2 for both complexes. Density functional theory calculations performed on 1 supported this conclusion.
Resumo:
Planar imidazolium cation based gemini surfactants 16-Im-n-Im-16], 2Br(-) (where n = 2, 3, 4, 5, 6, 8, 10, and 12), exhibit different morphologies and internal packing arrangements by adopting different supramolecular assemblies in aqueous media depending on their number of spacer methylene units (CH2)(n). Detailed measurements of the small-angle neutron-scattering (SANS) cross sections from different imidazolium-based surfactant micelles in aqueous media (D2O) are reported. The SANS data, containing the information of aggregation behavior of such surfactants in the molecular level, have been analyzed on the basis of the Hayter and Penfold model for the macro ion solution to compute the interparticle structure factor S(Q) taking into account the screened Coulomb interactions between the dimeric surfactant micelles. The characteristic changes in the SANS spectra of the dimeric surfactant with n = 4 due to variation of temperature have also been investigated. These data are then compared with the SANS characterization data of the corresponding gemini micelles containing tetrahedral ammonium ion based polar headgroups. The critical micellar concentration of each surfactant micelle (cmc) has been determined using pyrene as an extrinsic fluorescence probe. The variation of cmc as a function of spacer chain length has been explained in terms of conformational variation and progressive looping of the spacer into the micellar interior upon increasing the n values. Small-angle neutron-scattering (SANS) cross sections from different mixed micelles composed of surfactants with ammonium headgroups, 16-A(0), 16-Am-n-Am-16], 2Br(-) (where n = 4), 16-I-0, and 16-Im-n-Im-16], 2Br(-) (where n = 4), in aqueous media (D2O) have also been analyzed. The aggregate composition matches with that predicted from the ideal mixing model.
Resumo:
Precise specification of the vertical distribution of cloud optical properties is important to reduce the uncertainty in quantifying the radiative impacts of clouds. The new global observations of vertical profiles of clouds from the CloudSat mission provide opportunities to describe cloud structures and to improve parameterization of clouds in the weather and climate prediction models. In this study, four years (2007-2010) of observations of vertical structure of clouds from the CloudSat cloud profiling radar have been used to document the mean vertical structure of clouds associated with the Indian summer monsoon (ISM) and its intra-seasonal variability. Active and break monsoon spells associated with the intra-seasonal variability of ISM have been identified by an objective criterion. For the present analysis, we considered CloudSat derived column integrated cloud liquid and ice water, and vertically profiles of cloud liquid and ice water content. Over the South Asian monsoon region, deep convective clouds with large vertical extent (up to 14 km) and large values of cloud water and ice content are observed over the north Bay of Bengal. Deep clouds with large ice water content are also observed over north Arabian Sea and adjoining northwest India, along the west coast of India and the south equatorial Indian Ocean. The active monsoon spells are characterized by enhanced deep convection over the Bay of Bengal, west coast of India and northeast Arabian Sea and suppressed convection over the equatorial Indian Ocean. Over the Bay of Bengal, cloud liquid water content and ice water content is enhanced by similar to 90 and similar to 200 % respectively during the active spells. An interesting feature associated with the active spell is the vertical tilting structure of positive CLWC and CIWC anomalies over the Arabian Sea and the Bay of Bengal, which suggests a pre-conditioning process for the northward propagation of the boreal summer intra-seasonal variability. It is also observed that during the break spells, clouds are not completely suppressed over central India. Instead, clouds with smaller vertical extent (3-5 km) are observed due to the presence of a heat low type of circulation. The present results will be useful for validating the vertical structure of clouds in weather and climate prediction models.
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The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.
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Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.
Resumo:
Protein structure space is believed to consist of a finite set of discrete folds, unlike the protein sequence space which is astronomically large, indicating that proteins from the available sequence space are likely to adopt one of the many folds already observed. In spite of extensive sequence-structure correlation data, protein structure prediction still remains an open question with researchers having tried different approaches (experimental as well as computational). One of the challenges of protein structure prediction is to identify the native protein structures from a milieu of decoys/models. In this work, a rigorous investigation of Protein Structure Networks (PSNs) has been performed to detect native structures from decoys/ models. Ninety four parameters obtained from network studies have been optimally combined with Support Vector Machines (SVM) to derive a general metric to distinguish decoys/models from the native protein structures with an accuracy of 94.11%. Recently, for the first time in the literature we had shown that PSN has the capability to distinguish native proteins from decoys. A major difference between the present work and the previous study is to explore the transition profiles at different strengths of non-covalent interactions and SVM has indeed identified this as an important parameter. Additionally, the SVM trained algorithm is also applied to the recent CASP10 predicted models. The novelty of the network approach is that it is based on general network properties of native protein structures and that a given model can be assessed independent of any reference structure. Thus, the approach presented in this paper can be valuable in validating the predicted structures. A web-server has been developed for this purpose and is freely available at http://vishgraph.mbu.iisc.ernet.in/GraProStr/PSN-QA.html.
Resumo:
Thiolases are essential CoA-dependent enzymes in lipid metabolism. In the present study we report the crystal structures of trypanosomal and leishmanial SCP2 (sterol carrier protein, type-2)-thiolases. Trypanosomatidae cause various widespread devastating (sub)-tropical diseases, for which adequate treatment is lacking. The structures reveal the unique geometry of the active site of this poorly characterized subfamily of thiolases. The key catalytic residues of the classical thiolases are two cysteine residues, functioning as a nucleophile and an acid/base respectively. The latter cysteine residue is part of a CxG motif. Interestingly, this cysteine residue is not conserved in SCP2-thiolases. The structural comparisons now show that in SCP2-thiolases the catalytic acid/base is provided by the cysteine residue of the HDCF motif, which is unique for this thiolase subfamily. This HDCF cysteine residue is spatially equivalent to the CxG cysteine residue of classical thiolases. The HDCF cysteine residue is activated for acid/base catalysis by two main chain NH-atoms, instead of two water molecules, as present in the CxG active site. The structural results have been complemented with enzyme activity data, confirming the importance of the HDCF cysteine residue for catalysis. The data obtained suggest that these trypanosomatid SCP2-thiolases are biosynthetic thiolases. These findings provide promise for drug discovery as biosynthetic thiolases catalyse the first step of the sterol biosynthesis pathway that is essential in several of these parasites.
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Peripherally heterofunctionalized hyperbranched polymers (HBPs) undergo immiscibility-driven self-segregation of the outer segments to form Janus molecular entities (Macromolecules 2012, 45, 2348). In HBPs prepared via AB2 type self-condensation, single-step peripheral heterofunctionalization would lead to random distribution of the two types of terminal units, namely, homofunctionalized (homo-T) and heterofunctionalized (hetero-T) termini. Here, we examine the role of such hetero-T units on the self-segregation of heterofunctionalized pseudodendritic hyperbranched polydithioacetals. Three different heterofunctionalized HB dithioacetals bearing roughly 50 mol % each of docsyl (C-22) and MPEG-350 chains at the periphery were prepared: one of them carried a statistical distribution of homo-T and hetero-T units, and the other carried only two types of homo-T (-TR1R1 and -TR2R2) termini, whereas the third carried largely hetero-T (-TR1R2) termini. Careful examination of DSC and SAXS data reveals that the self-segregation is most effective in HBPs devoid of hetero-T units; interestingly, however, it also showed that randomly heterofunctionalized HBPs self-segregated nearly as effectively.
Resumo:
Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.
Resumo:
Secondary-structure elements (SSEs) play an important role in the folding of proteins. Identification of SSEs in proteins is a common problem in structural biology. A new method, ASSP (Assignment of Secondary Structure in Proteins), using only the path traversed by the C atoms has been developed. The algorithm is based on the premise that the protein structure can be divided into continuous or uniform stretches, which can be defined in terms of helical parameters, and depending on their values the stretches can be classified into different SSEs, namely -helices, 3(10)-helices, -helices, extended -strands and polyproline II (PPII) and other left-handed helices. The methodology was validated using an unbiased clustering of these parameters for a protein data set consisting of 1008 protein chains, which suggested that there are seven well defined clusters associated with different SSEs. Apart from -helices and extended -strands, 3(10)-helices and -helices were also found to occur in substantial numbers. ASSP was able to discriminate non--helical segments from flanking -helices, which were often identified as part of -helices by other algorithms. ASSP can also lead to the identification of novel SSEs. It is believed that ASSP could provide a better understanding of the finer nuances of protein secondary structure and could make an important contribution to the better understanding of comparatively less frequently occurring structural motifs. At the same time, it can contribute to the identification of novel SSEs. A standalone version of the program for the Linux as well as the Windows operating systems is freely downloadable and a web-server version is also available at .
Resumo:
The power of X-ray crystal structure analysis as a technique is to `see where the atoms are'. The results are extensively used by a wide variety of research communities. However, this `seeing where the atoms are' can give a false sense of security unless the precision of the placement of the atoms has been taken into account. Indeed, the presentation of bond distances and angles to a false precision (i.e. to too many decimal places) is commonplace. This article has three themes. Firstly, a basis for a proper representation of protein crystal structure results is detailed and demonstrated with respect to analyses of Protein Data Bank entries. The basis for establishing the precision of placement of each atom in a protein crystal structure is non-trivial. Secondly, a knowledge base harnessing such a descriptor of precision is presented. It is applied here to the case of salt bridges, i.e. ion pairs, in protein structures; this is the most fundamental place to start with such structure-precision representations since salt bridges are one of the tenets of protein structure stability. Ion pairs also play a central role in protein oligomerization, molecular recognition of ligands and substrates, allosteric regulation, domain motion and alpha-helix capping. A new knowledge base, SBPS (Salt Bridges in Protein Structures), takes these structural precisions into account and is the first of its kind. The third theme of the article is to indicate natural extensions of the need for such a description of precision, such as those involving metalloproteins and the determination of the protonation states of ionizable amino acids. Overall, it is also noted that this work and these examples are also relevant to protein three-dimensional structure molecular graphics software.
Resumo:
Kinases are ubiquitous enzymes that are pivotal to many biochemical processes. There are contrasting views on the phosphoryl-transfer mechanism in propionate kinase, an enzyme that reversibly transfers a phosphoryl group from propionyl phosphate to ADP in the final step of non-oxidative catabolism of L-threonine to propionate. Here, X-ray crystal structures of propionate- and nucleotide-bound Salmonella typhimurium propionate kinase are reported at 1.8-2.0 angstrom resolution. Although the mode of nucleotide binding is comparable to those of other members of the ASKHA superfamily, propionate is bound at a distinct site deeper in the hydrophobic pocket defining the active site. The propionate carboxyl is at a distance of approximate to 5 angstrom from the -phosphate of the nucleotide, supporting a direct in-line transfer mechanism. The phosphoryl-transfer reaction is likely to occur via an associative S(N)2-like transition state that involves a pentagonal bipyramidal structure with the axial positions occupied by the nucleophile of the substrate and the O atom between the - and the -phosphates, respectively. The proximity of the strictly conserved His175 and Arg236 to the carboxyl group of the propionate and the -phosphate of ATP suggests their involvement in catalysis. Moreover, ligand binding does not induce global domain movement as reported in some other members of the ASKHA superfamily. Instead, residues Arg86, Asp143 and Pro116-Leu117-His118 that define the active-site pocket move towards the substrate and expel water molecules from the active site. The role of Ala88, previously proposed to be the residue determining substrate specificity, was examined by determining the crystal structures of the propionate-bound Ala88 mutants A88V and A88G. Kinetic analysis and structural data are consistent with a significant role of Ala88 in substrate-specificity determination. The active-site pocket-defining residues Arg86, Asp143 and the Pro116-Leu117-His118 segment are also likely to contribute to substrate specificity.
Resumo:
Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
The magnetic structures and the magnetic phase transitions in the Mn-doped orthoferrite TbFeO3 studied using neutron powder diffraction are reported. Magnetic phase transitions are identified at T-N(Fe/Mn) approximate to 295K where a paramagnetic-to-antiferromagnetic transition occurs in the Fe/Mn sublattice, T-SR(Fe/Mn) approximate to 26K where a spin-reorientation transition occurs in the Fe/Mn sublattice and T-N(R) approximate to 2K where Tb-ordering starts to manifest. At 295 K, the magnetic structure of the Fe/Mn sublattice in TbFe0.5Mn0.5O3 belongs to the irreducible representation Gamma(4) (G(x)A(y)F(z) or Pb'n'm). A mixed-domain structure of (Gamma(1) + Gamma(4)) is found at 250K which remains stable down to the spin re-orientation transition at T-SR(Fe/Mn) approximate to 26K. Below 26K and above 250 K, the majority phase (>80%) is that of Gamma(4). Below 10K the high-temperature phase Gamma(4) remains stable till 2K. At 2 K, Tb develops a magnetic moment value of 0.6(2) mu(B)/f.u. and orders long-range in F-z compatible with the Gamma(4) representation. Our study confirms the magnetic phase transitions reported already in a single crystal of TbFe0.5Mn0.5O3 and, in addition, reveals the presence of mixed magnetic domains. The ratio of these magnetic domains as a function of temperature is estimated from Rietveld refinement of neutron diffraction data. Indications of short-range magnetic correlations are present in the low-Q region of the neutron diffraction patterns at T < T-SR(Fe/Mn). These results should motivate further experimental work devoted to measure electric polarization and magnetocapacitance of TbFe0.5Mn0.5O3. (C) 2016 AIP Publishing LLC.