Multifunctional 3D printing of heterogeneous hydrogel structures

PubMed Central

Nadernezhad, Ali; Khani, Navid; Skvortsov, Gözde Akdeniz; Toprakhisar, Burak; Bakirci, Ezgi; Menceloglu, Yusuf; Unal, Serkan; Koc, Bahattin

2016-01-01

Multimaterial additive manufacturing or three-dimensional (3D) printing of hydrogel structures provides the opportunity to engineer geometrically dependent functionalities. However, current fabrication methods are mostly limited to one type of material or only provide one type of functionality. In this paper, we report a novel method of multimaterial deposition of hydrogel structures based on an aspiration-on-demand protocol, in which the constitutive multimaterial segments of extruded filaments were first assembled in liquid state by sequential aspiration of inks into a glass capillary, followed by in situ gel formation. We printed different patterned objects with varying chemical, electrical, mechanical, and biological properties by tuning process and material related parameters, to demonstrate the abilities of this method in producing heterogeneous and multi-functional hydrogel structures. Our results show the potential of proposed method in producing heterogeneous objects with spatially controlled functionalities while preserving structural integrity at the switching interface between different segments. We anticipate that this method would introduce new opportunities in multimaterial additive manufacturing of hydrogels for diverse applications such as biosensors, flexible electronics, tissue engineering and organ printing. PMID:27630079

Predicting nucleic acid binding interfaces from structural models of proteins

PubMed Central

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2011-01-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767

Extending existing structural identifiability analysis methods to mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2018-01-01

The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

An accurate and efficient method for piezoelectric coated functional devices based on the two-dimensional Green’s function for a normal line force and line charge

NASA Astrophysics Data System (ADS)

Hou, Peng-Fei; Zhang, Yang

2017-09-01

Because most piezoelectric functional devices, including sensors, actuators and energy harvesters, are in the form of a piezoelectric coated structure, it is valuable to present an accurate and efficient method for obtaining the electro-mechanical coupling fields of this coated structure under mechanical and electrical loads. With this aim, the two-dimensional Green’s function for a normal line force and line charge on the surface of coated structure, which is a combination of an orthotropic piezoelectric coating and orthotropic elastic substrate, is presented in the form of elementary functions based on the general solution method. The corresponding electro-mechanical coupling fields of this coated structure under arbitrary mechanical and electrical loads can then be obtained by the superposition principle and Gauss integration. Numerical results show that the presented method has high computational precision, efficiency and stability. It can be used to design the best coating thickness in functional devices, improve the sensitivity of sensors, and improve the efficiency of actuators and energy harvesters. This method could be an efficient tool for engineers in engineering applications.

Protein–DNA Interactions: The Story so Far and a New Method for Prediction

DOE PAGES

Jones, Susan; Thornton, Janet M.

2003-01-01

This review describes methods for the prediction of DNA binding function, and specifically summarizes a new method using 3D structural templates. The new method features the HTH motif that is found in approximately one-third of DNAbinding protein families. A library of 3D structural templates of HTH motifs was derived from proteins in the PDB. Templates were scanned against complete protein structures and the optimal superposition of a template on a structure calculated. Significance thresholds in terms of a minimum root mean squared deviation (rmsd) of an optimal superposition, and a minimum motif accessible surface area (ASA), have been calculated. Inmore » this way, it is possible to scan the template library against proteins of unknown function to make predictions about DNA-binding functionality.« less

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Density functional study of molecular interactions in secondary structures of proteins.

PubMed

Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

2016-01-01

Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

A complementation assay for in vivo protein structure/function analysis in Physcomitrella patens (Funariaceae)

DOE PAGES

Scavuzzo-Duggan, Tess R.; Chaves, Arielle M.; Roberts, Alison W.

2015-07-14

Here, a method for rapid in vivo functional analysis of engineered proteins was developed using Physcomitrella patens. A complementation assay was designed for testing structure/function relationships in cellulose synthase (CESA) proteins. The components of the assay include (1) construction of test vectors that drive expression of epitope-tagged PpCESA5 carrying engineered mutations, (2) transformation of a ppcesa5 knockout line that fails to produce gametophores with test and control vectors, (3) scoring the stable transformants for gametophore production, (4) statistical analysis comparing complementation rates for test vectors to positive and negative control vectors, and (5) analysis of transgenic protein expression by Westernmore » blotting. The assay distinguished mutations that generate fully functional, nonfunctional, and partially functional proteins. In conclusion, compared with existing methods for in vivo testing of protein function, this complementation assay provides a rapid method for investigating protein structure/function relationships in plants.« less

Collaborative Modelling of the Vascular System--Designing and Evaluating a New Learning Method for Secondary Students

ERIC Educational Resources Information Center

Haugwitz, Marion; Sandmann, Angela

2010-01-01

Understanding biological structures and functions is often difficult because of their complexity and micro-structure. For example, the vascular system is a complex and only partly visible system. Constructing models to better understand biological functions is seen as a suitable learning method. Models function as simplified versions of real…

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

PubMed Central

Du, Yushen; Wu, Nicholas C.; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting

2016-01-01

ABSTRACT Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. PMID:27803181

Structures of Xishan village landslide in Li County, Sichuan, China, inferred from high-frequency receiver functions of local earthquakes

NASA Astrophysics Data System (ADS)

Wei, Z.; Chu, R.

2017-12-01

Teleseismic receiver function methods are widely used to study the deep structural information beneath the seismic station. However, teleseismic waveforms are difficult to extract the high-frequency receiver function, which are insufficient to constrain the shallow structure because of the inelastic attenuation effect of the earth. In this study, using the local earthquake waveforms collected from 3 broadband stations deployed on the Xishan village landslide in Li County in Sichuan Province, we used the high-frequency receiver function method to study the shallow structure beneath the landslide. We developed the Vp-k (Vp/Vs) staking method of receiver functions, and combined with the H-k stacking and waveform inversion methods of receiver functions to invert the landslide's thickness, S-wave velocity and average Vp/Vs ratio beneath these stations, and compared the thickness with the borehole results. Our results show small-scale lateral variety of velocity structure, a 78-143m/s lower S-wave velocity in the bottom layer and 2.4-3.1 Vp/Vs ratio in the landslide. The observed high Vp/Vs ratio and low S-wave velocity in the bottom layer of the landslide are consistent with low electrical resistivity and water-rich in the bottom layer, suggesting a weak shear strength and potential danger zone in landslide h1. Our study suggest that the local earthquake receiver function can obtain the shallow velocity structural information and supply some seismic constrains for the landslide catastrophe mitigation.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method.

PubMed

Molloy, Kevin; Shehu, Amarda

2013-01-01

Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space. We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers. Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.

Predicting nucleic acid binding interfaces from structural models of proteins.

PubMed

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

NASA Astrophysics Data System (ADS)

Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

2017-04-01

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

Effect of drying methods on the structure, thermo and functional properties of fenugreek (Trigonella foenum graecum) protein isolate.

PubMed

Feyzi, Samira; Varidi, Mehdi; Zare, Fatemeh; Varidi, Mohammad Javad

2018-03-01

Different drying methods due to protein denaturation could alter the functional properties of proteins, as well as their structure. So, this study focused on the effect of different drying methods on amino acid content, thermo and functional properties, and protein structure of fenugreek protein isolate. Freeze and spray drying methods resulted in comparable protein solubility, dynamic surface and interfacial tensions, foaming and emulsifying properties except for emulsion stability. Vacuum oven drying promoted emulsion stability, surface hydrophobicity and viscosity of fenugreek protein isolate at the expanse of its protein solubility. Vacuum oven process caused a higher level of Maillard reaction followed by the spray drying process, which was confirmed by the lower amount of lysine content and less lightness, also more browning intensity. ΔH of fenugreek protein isolates was higher than soy protein isolate, which confirmed the presence of more ordered structures. Also, the bands which are attributed to the α-helix structures in the FTIR spectrum were in the shorter wave number region for freeze and spray dried fenugreek protein isolates that show more possibility of such structures. This research suggests that any drying method must be conducted in its gentle state in order to sustain native structure of proteins and promote their functionalities. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

Method for protein structure alignment

DOEpatents

Blankenbecler, Richard; Ohlsson, Mattias; Peterson, Carsten; Ringner, Markus

2005-02-22

This invention provides a method for protein structure alignment. More particularly, the present invention provides a method for identification, classification and prediction of protein structures. The present invention involves two key ingredients. First, an energy or cost function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. Second, a minimization of the energy or cost function by an iterative method, where in each iteration (1) a mean field method is employed for the assignment variables and (2) exact rotation and/or translation of atomic coordinates is performed, weighted with the corresponding assignment variables.

Functional annotation by sequence-weighted structure alignments: statistical analysis and case studies from the Protein 3000 structural genomics project in Japan.

PubMed

Standley, Daron M; Toh, Hiroyuki; Nakamura, Haruki

2008-09-01

A method to functionally annotate structural genomics targets, based on a novel structural alignment scoring function, is proposed. In the proposed score, position-specific scoring matrices are used to weight structurally aligned residue pairs to highlight evolutionarily conserved motifs. The functional form of the score is first optimized for discriminating domains belonging to the same Pfam family from domains belonging to different families but the same CATH or SCOP superfamily. In the optimization stage, we consider four standard weighting functions as well as our own, the "maximum substitution probability," and combinations of these functions. The optimized score achieves an area of 0.87 under the receiver-operating characteristic curve with respect to identifying Pfam families within a sequence-unique benchmark set of domain pairs. Confidence measures are then derived from the benchmark distribution of true-positive scores. The alignment method is next applied to the task of functionally annotating 230 query proteins released to the public as part of the Protein 3000 structural genomics project in Japan. Of these queries, 78 were found to align to templates with the same Pfam family as the query or had sequence identities > or = 30%. Another 49 queries were found to match more distantly related templates. Within this group, the template predicted by our method to be the closest functional relative was often not the most structurally similar. Several nontrivial cases are discussed in detail. Finally, 103 queries matched templates at the fold level, but not the family or superfamily level, and remain functionally uncharacterized. 2008 Wiley-Liss, Inc.

Dual-Level Method for Estimating Multistructural Partition Functions with Torsional Anharmonicity.

PubMed

Bao, Junwei Lucas; Xing, Lili; Truhlar, Donald G

2017-06-13

For molecules with multiple torsions, an accurate evaluation of the molecular partition function requires consideration of multiple structures and their torsional-potential anharmonicity. We previously developed a method called MS-T for this problem, and it requires an exhaustive conformational search with frequency calculations for all the distinguishable conformers; this can become expensive for molecules with a large number of torsions (and hence a large number of structures) if it is carried out with high-level methods. In the present work, we propose a cost-effective method to approximate the MS-T partition function when there are a large number of structures, and we test it on a transition state that has eight torsions. This new method is a dual-level method that combines an exhaustive conformer search carried out by a low-level electronic structure method (for instance, AM1, which is very inexpensive) and selected calculations with a higher-level electronic structure method (for example, density functional theory with a functional that is suitable for conformational analysis and thermochemistry). To provide a severe test of the new method, we consider a transition state structure that has 8 torsional degrees of freedom; this transition state structure is formed along one of the reaction pathways of the hydrogen abstraction reaction (at carbon-1) of ketohydroperoxide (KHP; its IUPAC name is 4-hydroperoxy-2-pentanone) by OH radical. We find that our proposed dual-level method is able to significantly reduce the computational cost for computing MS-T partition functions for this test case with a large number of torsions and with a large number of conformers because we carry out high-level calculations for only a fraction of the distinguishable conformers found by the low-level method. In the example studied here, the dual-level method with 40 high-level optimizations (1.8% of the number of optimizations in a coarse-grained full search and 0.13% of the number of optimizations in a fine-grained full search) reproduces the full calculation of the high-level partition function within a factor of 1.0 to 2.0 from 200 to 1000 K. The error in the dual-level method can be further reduced to factors of 0.6 to 1.1 over the whole temperature interval from 200 to 2400 K by optimizing 128 structures (5.9% of the number of optimizations in a fine-grained full search and 0.41% of the number of optimizations in a fine-grained full search). These factor-of-two or better errors are small compared to errors up to a factor of 1.0 × 10 3 if one neglects multistructural effects for the case under study.

Crystal structure prediction supported by incomplete experimental data

NASA Astrophysics Data System (ADS)

Tsujimoto, Naoto; Adachi, Daiki; Akashi, Ryosuke; Todo, Synge; Tsuneyuki, Shinji

2018-05-01

We propose an efficient theoretical scheme for structure prediction on the basis of the idea of combining methods, which optimize theoretical calculation and experimental data simultaneously. In this scheme, we formulate a cost function based on a weighted sum of interatomic potential energies and a penalty function which is defined with partial experimental data totally insufficient for conventional structure analysis. In particular, we define the cost function using "crystallinity" formulated with only peak positions within the small range of the x-ray-diffraction pattern. We apply this method to well-known polymorphs of SiO2 and C with up to 108 atoms in the simulation cell and show that it reproduces the correct structures efficiently with very limited information of diffraction peaks. This scheme opens a new avenue for determining and predicting structures that are difficult to determine by conventional methods.

Structural reliability calculation method based on the dual neural network and direct integration method.

PubMed

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method

PubMed Central

2013-01-01

Background Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space. Methods We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers. Results and conclusions Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers. PMID:24565158

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Consolidating Orientation of Pedagogic Functions of University Teachers in International Students Training

ERIC Educational Resources Information Center

Dzhamalova, Bika B.; Timonin, Andrey I.; Kolesov, Vladimir I.; Pavlov, Vladimir V.; Evstegneeva, Anastasiia A.

2016-01-01

This article is focused on the development of the structure and content of consolidating orientation of pedagogical functions of university teachers in international students' training. The leading method of research is the modeling method that allows producing of the established structure's and content's justification of consolidating orientation…

[Immunochemistry of eukaryotic ribosomes].

PubMed

Lopaczyński, W; Gałasiński, W

1990-01-01

Immunochemical investigations of ribosomes should correlate with basic knowledge of the function, structure and activity of organelles in the cell processes. Our paper presents data of immunochemical methods used to determine the structure, function and differences of ribosomes. We present the usefulness of immunochemical methods to test human ribosomes, diagnosis and therapy of many diseases.

A statistical approach for inferring the 3D structure of the genome.

PubMed

Varoquaux, Nelle; Ay, Ferhat; Noble, William Stafford; Vert, Jean-Philippe

2014-06-15

Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate 3D models of how chromosomes fold and fit into the nucleus. Many existing inference methods rely on multidimensional scaling (MDS), in which the pairwise distances of the inferred model are optimized to resemble pairwise distances derived directly from the contact counts. These approaches, however, often optimize a heuristic objective function and require strong assumptions about the biophysics of DNA to transform interaction frequencies to spatial distance, and thereby may lead to incorrect structure reconstruction. We propose a novel approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data. We compare two variants of our Poisson method, with or without optimization of the transfer function, to four different MDS-based algorithms-two metric MDS methods using different stress functions, a non-metric version of MDS and ChromSDE, a recently described, advanced MDS method-on a wide range of simulated datasets. We demonstrate that the Poisson models reconstruct better structures than all MDS-based methods, particularly at low coverage and high resolution, and we highlight the importance of optimizing the transfer function. On publicly available Hi-C data from mouse embryonic stem cells, we show that the Poisson methods lead to more reproducible structures than MDS-based methods when we use data generated using different restriction enzymes, and when we reconstruct structures at different resolutions. A Python implementation of the proposed method is available at http://cbio.ensmp.fr/pastis. © The Author 2014. Published by Oxford University Press.

A network function-based definition of communities in complex networks.

PubMed

Chauhan, Sanjeev; Girvan, Michelle; Ott, Edward

2012-09-01

We consider an alternate definition of community structure that is functionally motivated. We define network community structure based on the function the network system is intended to perform. In particular, as a specific example of this approach, we consider communities whose function is enhanced by the ability to synchronize and/or by resilience to node failures. Previous work has shown that, in many cases, the largest eigenvalue of the network's adjacency matrix controls the onset of both synchronization and percolation processes. Thus, for networks whose functional performance is dependent on these processes, we propose a method that divides a given network into communities based on maximizing a function of the largest eigenvalues of the adjacency matrices of the resulting communities. We also explore the differences between the partitions obtained by our method and the modularity approach (which is based solely on consideration of network structure). We do this for several different classes of networks. We find that, in many cases, modularity-based partitions do almost as well as our function-based method in finding functional communities, even though modularity does not specifically incorporate consideration of function.

The Researches on Damage Detection Method for Truss Structures

NASA Astrophysics Data System (ADS)

Wang, Meng Hong; Cao, Xiao Nan

2018-06-01

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Single Cell Spectroscopy: Noninvasive Measures of Small-Scale Structure and Function

PubMed Central

Mousoulis, Charilaos; Xu, Xin; Reiter, David A.; Neu, Corey P.

2013-01-01

The advancement of spectroscopy methods attained through increases in sensitivity, and often with the coupling of complementary techniques, has enabled real-time structure and function measurements of single cells. The purpose of this review is to illustrate, in light of advances, the strengths and the weaknesses of these methods. Included also is an assessment of the impact of the experimental setup and conditions of each method on cellular function and integrity. A particular emphasis is placed on noninvasive and nondestructive techniques for achieving single cell detection, including nuclear magnetic resonance, in addition to physical, optical, and vibrational methods. PMID:23886910

Using block pulse functions for seismic vibration semi-active control of structures with MR dampers

NASA Astrophysics Data System (ADS)

Rahimi Gendeshmin, Saeed; Davarnia, Daniel

2018-03-01

This article applied the idea of block pulse functions in the semi-active control of structures. The BP functions give effective tools to approximate complex problems. The applied control algorithm has a major effect on the performance of the controlled system and the requirements of the control devices. In control problems, it is important to devise an accurate analytical technique with less computational cost. It is proved that the BP functions are fundamental tools in approximation problems which have been applied in disparate areas in last decades. This study focuses on the employment of BP functions in control algorithm concerning reduction the computational cost. Magneto-rheological (MR) dampers are one of the well-known semi-active tools that can be used to control the response of civil Structures during earthquake. For validation purposes, numerical simulations of a 5-story shear building frame with MR dampers are presented. The results of suggested method were compared with results obtained by controlling the frame by the optimal control method based on linear quadratic regulator theory. It can be seen from simulation results that the suggested method can be helpful in reducing seismic structural responses. Besides, this method has acceptable accuracy and is in agreement with optimal control method with less computational costs.

Residues with similar hexagon neighborhoods share similar side-chain conformations.

PubMed

Li, Shuai Cheng; Bu, Dongbo; Li, Ming

2012-01-01

We present in this study a new approach to code protein side-chain conformations into hexagon substructures. Classical side-chain packing methods consist of two steps: first, side-chain conformations, known as rotamers, are extracted from known protein structures as candidates for each residue; second, a searching method along with an energy function is used to resolve conflicts among residues and to optimize the combinations of side chain conformations for all residues. These methods benefit from the fact that the number of possible side-chain conformations is limited, and the rotamer candidates are readily extracted; however, these methods also suffer from the inaccuracy of energy functions. Inspired by threading and Ab Initio approaches to protein structure prediction, we propose to use hexagon substructures to implicitly capture subtle issues of energy functions. Our initial results indicate that even without guidance from an energy function, hexagon structures alone can capture side-chain conformations at an accuracy of 83.8 percent, higher than 82.6 percent by the state-of-art side-chain packing methods.

Structural and Functional Evaluations for the Early Detection of Glaucoma.

PubMed

Lucy, Katie A; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection.

Structural and Functional Evaluations for the Early Detection of Glaucoma

PubMed Central

Lucy, Katie A.; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection. PMID:28603546

Release strategies for making transferable semiconductor structures, devices and device components

DOEpatents

Rogers, John A; Nuzzo, Ralph G; Meitl, Matthew; Ko, Heung Cho; Yoon, Jongseung; Menard, Etienne; Baca, Alfred J

2014-11-25

Provided are methods for making a device or device component by providing a multilayer structure having a plurality of functional layers and a plurality of release layers and releasing the functional layers from the multilayer structure by separating one or more of the release layers to generate a plurality of transferable structures. The transferable structures are printed onto a device substrate or device component supported by a device substrate. The methods and systems provide means for making high-quality and low-cost photovoltaic devices, transferable semiconductor structures, (opto-)electronic devices and device components.

Release strategies for making transferable semiconductor structures, devices and device components

DOEpatents

Rogers, John A [Champaign, IL; Nuzzo, Ralph G [Champaign, IL; Meitl, Matthew [Raleigh, NC; Ko, Heung Cho [Urbana, IL; Yoon, Jongseung [Urbana, IL; Menard, Etienne [Durham, NC; Baca, Alfred J [Urbana, IL

2011-04-26

Provided are methods for making a device or device component by providing a multilayer structure having a plurality of functional layers and a plurality of release layers and releasing the functional layers from the multilayer structure by separating one or more of the release layers to generate a plurality of transferable structures. The transferable structures are printed onto a device substrate or device component supported by a device substrate. The methods and systems provide means for making high-quality and low-cost photovoltaic devices, transferable semiconductor structures, (opto-)electronic devices and device components.

Release strategies for making transferable semiconductor structures, devices and device components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rogers, John A.; Nuzzo, Ralph G.; Meitl, Matthew

2016-05-24

Provided are methods for making a device or device component by providing a multi layer structure having a plurality of functional layers and a plurality of release layers and releasing the functional layers from the multilayer structure by separating one or more of the release layers to generate a plurality of transferable structures. The transferable structures are printed onto a device substrate or device component supported by a device substrate. The methods and systems provide means for making high-quality and low-cost photovoltaic devices, transferable semiconductor structures, (opto-)electronic devices and device components.

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Text Mining Improves Prediction of Protein Functional Sites

PubMed Central

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Methods to assess Drosophila heart development, function and aging

PubMed Central

Ocorr, Karen; Vogler, Georg; Bodmer, Rolf

2014-01-01

In recent years the Drosophila heart has become an established model of many different aspects of human cardiac disease. This model has allowed identification of disease-causing mechanisms underlying congenital heart disease and cardiomyopathies and has permitted the study underlying genetic, metabolic and age-related contributions to heart function. In this review we discuss methods currently employed in the analysis of the Drosophila heart structure and function, such as optical methods to infer heart function and performance, electrophysiological and mechanical approaches to characterize cardiac tissue properties, and conclude with histological techniques used in the study of heart development and adult structure. PMID:24727147

Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

NASA Astrophysics Data System (ADS)

Xu, Jun; Dang, Chao; Kong, Fan

2017-10-01

This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.

Simplified DFT methods for consistent structures and energies of large systems

NASA Astrophysics Data System (ADS)

Caldeweyher, Eike; Gerit Brandenburg, Jan

2018-05-01

Kohn–Sham density functional theory (DFT) is routinely used for the fast electronic structure computation of large systems and will most likely continue to be the method of choice for the generation of reliable geometries in the foreseeable future. Here, we present a hierarchy of simplified DFT methods designed for consistent structures and non-covalent interactions of large systems with particular focus on molecular crystals. The covered methods are a minimal basis set Hartree–Fock (HF-3c), a small basis set screened exchange hybrid functional (HSE-3c), and a generalized gradient approximated functional evaluated in a medium-sized basis set (B97-3c), all augmented with semi-classical correction potentials. We give an overview on the methods design, a comprehensive evaluation on established benchmark sets for geometries and lattice energies of molecular crystals, and highlight some realistic applications on large organic crystals with several hundreds of atoms in the primitive unit cell.

Potential function of element measurement for form-finding of wide sense tensegrity

NASA Astrophysics Data System (ADS)

Soe, C. K.; Obiya, H.; Koga, D.; Nizam, Z. M.; Ijima, K.

2018-04-01

Tensegrity is a unique morphological structure in which disconnected compression members and connected tension members make the whole structure in self-equilibrium. Many researches have been done on tensegrity structure because of its mysteriousness in form-finding analysis. This study is proposed to investigate the trends and to group into some patterns of the shape that a tensegrity structure can have under the same connectivity and support condition. In this study, tangent stiffness method adopts two different functions, namely power function and logarithm function to element measurement. Numerical examples are based on a simplex initial shape with statically determinate support condition to examine the pure effectiveness of two proposed methods. The tangent stiffness method that can evaluate strict rigid body displacement of elements has a superiority to define various measure potentials and to allow the use of virtual element stiffness freely. From the results of numerical examples, the finding of the dominant trends and patterns of the equilibrium solutions is achieved although it has many related solutions under the same circumstances.

General method of solving the Schroedinger equation of atoms and molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakatsuji, Hiroshi

2005-12-15

We propose a general method of solving the Schroedinger equation of atoms and molecules. We first construct the wave function having the exact structure, using the ICI (iterative configuration or complement interaction) method and then optimize the variables involved by the variational principle. Based on the scaled Schroedinger equation and related principles, we can avoid the singularity problem of atoms and molecules and formulate a general method of calculating the exact wave functions in an analytical expansion form. We choose initial function {psi}{sub 0} and scaling g function, and then the ICI method automatically generates the wave function that hasmore » the exact structure by using the Hamiltonian of the system. The Hamiltonian contains all the information of the system. The free ICI method provides a flexible and variationally favorable procedure of constructing the exact wave function. We explain the computational procedure of the analytical ICI method routinely performed in our laboratory. Simple examples are given using hydrogen atom for the nuclear singularity case, the Hooke's atom for the electron singularity case, and the helium atom for both cases.« less

Orbital dependent functionals: An atom projector augmented wave method implementation

NASA Astrophysics Data System (ADS)

Xu, Xiao

This thesis explores the formulation and numerical implementation of orbital dependent exchange-correlation functionals within electronic structure calculations. These orbital-dependent exchange-correlation functionals have recently received renewed attention as a means to improve the physical representation of electron interactions within electronic structure calculations. In particular, electron self-interaction terms can be avoided. In this thesis, an orbital-dependent functional is considered in the context of Hartree-Fock (HF) theory as well as the Optimized Effective Potential (OEP) method and the approximate OEP method developed by Krieger, Li, and Iafrate, known as the KLI approximation. In this thesis, the Fock exchange term is used as a simple well-defined example of an orbital-dependent functional. The Projected Augmented Wave (PAW) method developed by P. E. Blochl has proven to be accurate and efficient for electronic structure calculations for local and semi-local functions because of its accurate evaluation of interaction integrals by controlling multiple moments. We have extended the PAW method to treat orbital-dependent functionals in Hartree-Fock theory and the Optimized Effective Potential method, particularly in the KLI approximation. In the course of study we develop a frozen-core orbital approximation that accurately treats the core electron contributions for above three methods. The main part of the thesis focuses on the treatment of spherical atoms. We have investigated the behavior of PAW-Hartree Fock and PAW-KLI basis, projector, and pseudopotential functions for several elements throughout the periodic table. We have also extended the formalism to the treatment of solids in a plane wave basis and implemented PWPAW-KLI code, which will appear in future publications.

GalaxyGPCRloop: Template-Based and Ab Initio Structure Sampling of the Extracellular Loops of G-Protein-Coupled Receptors.

PubMed

Won, Jonghun; Lee, Gyu Rie; Park, Hahnbeom; Seok, Chaok

2018-06-07

The second extracellular loops (ECL2s) of G-protein-coupled receptors (GPCRs) are often involved in GPCR functions, and their structures have important implications in drug discovery. However, structure prediction of ECL2 is difficult because of its long length and the structural diversity among different GPCRs. In this study, a new ECL2 conformational sampling method involving both template-based and ab initio sampling was developed. Inspired by the observation of similar ECL2 structures of closely related GPCRs, a template-based sampling method employing loop structure templates selected from the structure database was developed. A new metric for evaluating similarity of the target loop to templates was introduced for template selection. An ab initio loop sampling method was also developed to treat cases without highly similar templates. The ab initio method is based on the previously developed fragment assembly and loop closure method. A new sampling component that takes advantage of secondary structure prediction was added. In addition, a conserved disulfide bridge restraining ECL2 conformation was predicted and analytically incorporated into sampling, reducing the effective dimension of the conformational search space. The sampling method was combined with an existing energy function for comparison with previously reported loop structure prediction methods, and the benchmark test demonstrated outstanding performance.

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Using Variable-Length Aligned Fragment Pairs and an Improved Transition Function for Flexible Protein Structure Alignment.

PubMed

Cao, Hu; Lu, Yonggang

2017-01-01

With the rapid growth of known protein 3D structures in number, how to efficiently compare protein structures becomes an essential and challenging problem in computational structural biology. At present, many protein structure alignment methods have been developed. Among all these methods, flexible structure alignment methods are shown to be superior to rigid structure alignment methods in identifying structure similarities between proteins, which have gone through conformational changes. It is also found that the methods based on aligned fragment pairs (AFPs) have a special advantage over other approaches in balancing global structure similarities and local structure similarities. Accordingly, we propose a new flexible protein structure alignment method based on variable-length AFPs. Compared with other methods, the proposed method possesses three main advantages. First, it is based on variable-length AFPs. The length of each AFP is separately determined to maximally represent a local similar structure fragment, which reduces the number of AFPs. Second, it uses local coordinate systems, which simplify the computation at each step of the expansion of AFPs during the AFP identification. Third, it decreases the number of twists by rewarding the situation where nonconsecutive AFPs share the same transformation in the alignment, which is realized by dynamic programming with an improved transition function. The experimental data show that compared with FlexProt, FATCAT, and FlexSnap, the proposed method can achieve comparable results by introducing fewer twists. Meanwhile, it can generate results similar to those of the FATCAT method in much less running time due to the reduced number of AFPs.

From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

PubMed Central

Forman-Kay, Julie D.; Mittag, Tanja

2015-01-01

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

From sequence and forces to structure, function, and evolution of intrinsically disordered proteins.

PubMed

Forman-Kay, Julie D; Mittag, Tanja

2013-09-03

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics, and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales, and compactness are shaping a unified understanding of structure-dynamics-disorder/function relationships. In the 20(th) anniversary of Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional, and evolutionary properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ballistic Puncture Self-Healing Polymeric Materials

NASA Technical Reports Server (NTRS)

Gordon, Keith L.; Siochi, Emilie J.; Yost, William T.; Bogert, Phil B.; Howell, Patricia A.; Cramer, K. Elliott; Burke, Eric R.

2017-01-01

Space exploration launch costs on the order of $10,000 per pound provide an incentive to seek ways to reduce structural mass while maintaining structural function to assure safety and reliability. Damage-tolerant structural systems provide a route to avoiding weight penalty while enhancing vehicle safety and reliability. Self-healing polymers capable of spontaneous puncture repair show promise to mitigate potentially catastrophic damage from events such as micrometeoroid penetration. Effective self-repair requires these materials to quickly heal following projectile penetration while retaining some structural function during the healing processes. Although there are materials known to possess this capability, they are typically not considered for structural applications. Current efforts use inexpensive experimental methods to inflict damage, after which analytical procedures are identified to verify that function is restored. Two candidate self-healing polymer materials for structural engineering systems are used to test these experimental methods.

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

PubMed

Kuhn, Alexandre; Ong, Yao Min; Quake, Stephen R; Burkholder, William F

2015-07-08

Like other structural variants, transposable element insertions can be highly polymorphic across individuals. Their functional impact, however, remains poorly understood. Current genome-wide approaches for genotyping insertion-site polymorphisms based on targeted or whole-genome sequencing remain very expensive and can lack accuracy, hence new large-scale genotyping methods are needed. We describe a high-throughput method for genotyping transposable element insertions and other types of structural variants that can be assayed by breakpoint PCR. The method relies on next-generation sequencing of multiplex, site-specific PCR amplification products and read count-based genotype calls. We show that this method is flexible, efficient (it does not require rounds of optimization), cost-effective and highly accurate. This method can benefit a wide range of applications from the routine genotyping of animal and plant populations to the functional study of structural variants in humans.

Modified Displacement Transfer Functions for Deformed Shape Predictions of Slender Curved Structures with Varying Curvatives

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2014-01-01

To eliminate the need to use finite-element modeling for structure shape predictions, a new method was invented. This method is to use the Displacement Transfer Functions to transform the measured surface strains into deflections for mapping out overall structural deformed shapes. The Displacement Transfer Functions are expressed in terms of rectilinearly distributed surface strains, and contain no material properties. This report is to apply the patented method to the shape predictions of non-symmetrically loaded slender curved structures with different curvatures up to a full circle. Because the measured surface strains are not available, finite-element analysis had to be used to analytically generate the surface strains. Previously formulated straight-beam Displacement Transfer Functions were modified by introducing the curvature-effect correction terms. Through single-point or dual-point collocations with finite-elementgenerated deflection curves, functional forms of the curvature-effect correction terms were empirically established. The resulting modified Displacement Transfer Functions can then provide quite accurate shape predictions. Also, the uniform straight-beam Displacement Transfer Function was applied to the shape predictions of a section-cut of a generic capsule (GC) outer curved sandwich wall. The resulting GC shape predictions are quite accurate in partial regions where the radius of curvature does not change sharply.

Clustering and visualizing similarity networks of membrane proteins.

PubMed

Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

2015-08-01

We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

Structure and Stability of Molecular Crystals with Many-Body Dispersion-Inclusive Density Functional Tight Binding.

PubMed

Mortazavi, Majid; Brandenburg, Jan Gerit; Maurer, Reinhard J; Tkatchenko, Alexandre

2018-01-18

Accurate prediction of structure and stability of molecular crystals is crucial in materials science and requires reliable modeling of long-range dispersion interactions. Semiempirical electronic structure methods are computationally more efficient than their ab initio counterparts, allowing structure sampling with significant speedups. We combine the Tkatchenko-Scheffler van der Waals method (TS) and the many-body dispersion method (MBD) with third-order density functional tight-binding (DFTB3) via a charge population-based method. We find an overall good performance for the X23 benchmark database of molecular crystals, despite an underestimation of crystal volume that can be traced to the DFTB parametrization. We achieve accurate lattice energy predictions with DFT+MBD energetics on top of vdW-inclusive DFTB3 structures, resulting in a speedup of up to 3000 times compared with a full DFT treatment. This suggests that vdW-inclusive DFTB3 can serve as a viable structural prescreening tool in crystal structure prediction.

From Structure to Function: A Comprehensive Compendium of Tools to Unveil Protein Domains and Understand Their Role in Cytokinesis.

PubMed

Rincon, Sergio A; Paoletti, Anne

2016-01-01

Unveiling the function of a novel protein is a challenging task that requires careful experimental design. Yeast cytokinesis is a conserved process that involves modular structural and regulatory proteins. For such proteins, an important step is to identify their domains and structural organization. Here we briefly discuss a collection of methods commonly used for sequence alignment and prediction of protein structure that represent powerful tools for the identification homologous domains and design of structure-function approaches to test experimentally the function of multi-domain proteins such as those implicated in yeast cytokinesis.

Estimation of the auto frequency response function at unexcited points using dummy masses

NASA Astrophysics Data System (ADS)

Hosoya, Naoki; Yaginuma, Shinji; Onodera, Hiroshi; Yoshimura, Takuya

2015-02-01

If structures with complex shapes have space limitations, vibration tests using an exciter or impact hammer for the excitation are difficult. Although measuring the auto frequency response function at an unexcited point may not be practical via a vibration test, it can be obtained by assuming that the inertia acting on a dummy mass is an external force on the target structure upon exciting a different excitation point. We propose a method to estimate the auto frequency response functions at unexcited points by attaching a small mass (dummy mass), which is comparable to the accelerometer mass. The validity of the proposed method is demonstrated by comparing the auto frequency response functions estimated at unexcited points in a beam structure to those obtained from numerical simulations. We also consider random measurement errors by finite element analysis and vibration tests, but not bias errors. Additionally, the applicability of the proposed method is demonstrated by applying it to estimate the auto frequency response function of the lower arm in a car suspension.

Exponential Family Functional data analysis via a low-rank model.

PubMed

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

Understand protein functions by comparing the similarity of local structural environments.

PubMed

Chen, Jiawen; Xie, Zhong-Ru; Wu, Yinghao

2017-02-01

The three-dimensional structures of proteins play an essential role in regulating binding between proteins and their partners, offering a direct relationship between structures and functions of proteins. It is widely accepted that the function of a protein can be determined if its structure is similar to other proteins whose functions are known. However, it is also observed that proteins with similar global structures do not necessarily correspond to the same function, while proteins with very different folds can share similar functions. This indicates that function similarity is originated from the local structural information of proteins instead of their global shapes. We assume that proteins with similar local environments prefer binding to similar types of molecular targets. In order to testify this assumption, we designed a new structural indicator to define the similarity of local environment between residues in different proteins. This indicator was further used to calculate the probability that a given residue binds to a specific type of structural neighbors, including DNA, RNA, small molecules and proteins. After applying the method to a large-scale non-redundant database of proteins, we show that the positive signal of binding probability calculated from the local structural indicator is statistically meaningful. In summary, our studies suggested that the local environment of residues in a protein is a good indicator to recognize specific binding partners of the protein. The new method could be a potential addition to a suite of existing template-based approaches for protein function prediction. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistically generated weighted curve fit of residual functions for modal analysis of structures

NASA Technical Reports Server (NTRS)

Bookout, P. S.

1995-01-01

A statistically generated weighting function for a second-order polynomial curve fit of residual functions has been developed. The residual flexibility test method, from which a residual function is generated, is a procedure for modal testing large structures in an external constraint-free environment to measure the effects of higher order modes and interface stiffness. This test method is applicable to structures with distinct degree-of-freedom interfaces to other system components. A theoretical residual function in the displacement/force domain has the characteristics of a relatively flat line in the lower frequencies and a slight upward curvature in the higher frequency range. In the test residual function, the above-mentioned characteristics can be seen in the data, but due to the present limitations in the modal parameter evaluation (natural frequencies and mode shapes) of test data, the residual function has regions of ragged data. A second order polynomial curve fit is required to obtain the residual flexibility term. A weighting function of the data is generated by examining the variances between neighboring data points. From a weighted second-order polynomial curve fit, an accurate residual flexibility value can be obtained. The residual flexibility value and free-free modes from testing are used to improve a mathematical model of the structure. The residual flexibility modal test method is applied to a straight beam with a trunnion appendage and a space shuttle payload pallet simulator.

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level. http://genome.gbf.de/bioinformatics/

Highly efficient model updating for structural condition assessment of large-scale bridges.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

Time-domain representation of frequency-dependent foundation impedance functions

USGS Publications Warehouse

Safak, E.

2006-01-01

Foundation impedance functions provide a simple means to account for soil-structure interaction (SSI) when studying seismic response of structures. Impedance functions represent the dynamic stiffness of the soil media surrounding the foundation. The fact that impedance functions are frequency dependent makes it difficult to incorporate SSI in standard time-history analysis software. This paper introduces a simple method to convert frequency-dependent impedance functions into time-domain filters. The method is based on the least-squares approximation of impedance functions by ratios of two complex polynomials. Such ratios are equivalent, in the time-domain, to discrete-time recursive filters, which are simple finite-difference equations giving the relationship between foundation forces and displacements. These filters can easily be incorporated into standard time-history analysis programs. Three examples are presented to show the applications of the method.

Propagation of eigenmodes and transfer functions in waveguide WDM structures

NASA Astrophysics Data System (ADS)

Mashkov, Vladimir A.; Francoeur, S.; Geuss, U.; Neiser, K.; Temkin, Henryk

1998-02-01

A method of propagation functions and transfer amplitudes suitable for the design of integrated optical circuits is presented. The method is based on vectorial formulation of electrodynamics: the distributions and propagation of electromagnetic fields in optical circuits is described by equivalent surface sources. This approach permits a division of complex optical waveguide structures into sets of primitive blocks and to separately calculate the transfer function and the transfer amplitude for each block. The transfer amplitude of the entire optical system is represented by a convolution of transfer amplitudes of its primitive blocks. The eigenvalues and eigenfunctions of arbitrary waveguide structure are obtained in the WKB approximation and compared with other methods. The general approach is illustrated with the transfer amplitude calculations for Dragone's star coupler and router.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Mathematical methods for protein science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.; Istrail, S.; Atkins, J.

1997-12-31

Understanding the structure and function of proteins is a fundamental endeavor in molecular biology. Currently, over 100,000 protein sequences have been determined by experimental methods. The three dimensional structure of the protein determines its function, but there are currently less than 4,000 structures known to atomic resolution. Accordingly, techniques to predict protein structure from sequence have an important role in aiding the understanding of the Genome and the effects of mutations in genetic disease. The authors describe current efforts at Sandia to better understand the structure of proteins through rigorous mathematical analyses of simple lattice models. The efforts have focusedmore » on two aspects of protein science: mathematical structure prediction, and inverse protein folding.« less

Computational modeling of RNA 3D structures, with the aid of experimental restraints

PubMed Central

Magnus, Marcin; Matelska, Dorota; Łach, Grzegorz; Chojnowski, Grzegorz; Boniecki, Michal J; Purta, Elzbieta; Dawson, Wayne; Dunin-Horkawicz, Stanislaw; Bujnicki, Janusz M

2014-01-01

In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation (“Greek science” approach) or utilize information derived from known structures of other RNA molecules (“Babylonian science” approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately. PMID:24785264

A survey of kernel-type estimators for copula and their applications

NASA Astrophysics Data System (ADS)

Sumarjaya, I. W.

2017-10-01

Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

Frequency response function-based explicit framework for dynamic identification in human-structure systems

NASA Astrophysics Data System (ADS)

Wei, Xiaojun; Živanović, Stana

2018-05-01

The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.

The proteome: structure, function and evolution

PubMed Central

Fleming, Keiran; Kelley, Lawrence A; Islam, Suhail A; MacCallum, Robert M; Muller, Arne; Pazos, Florencio; Sternberg, Michael J.E

2006-01-01

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family. PMID:16524832

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

An active structure preservation method for developing functional graphitic carbon dots as an effective antibacterial agent and a sensitive pH and Al(iii) nanosensor.

PubMed

Hou, Peng; Yang, Tong; Liu, Hui; Li, Yuan Fang; Huang, Cheng Zhi

2017-11-16

Functional engineering is a crucial prerequisite for specific and wide applications of optical probes. In this study, we proposed a facile active structure preservation (ASP) method to directly develop new self-functional graphitic carbon dots (g-CDs) through a hydrothermal synthesis route by taking ciprofloxacin hydrochloride, an antibiotic belonging to a group of fluoroquinolone drugs, as an example. To retain the functional structures of the starting materials, the reaction temperature is intentionally controlled below the decomposition temperature of the reactants that hold the functional groups. As a proof of concept, we successfully prepared g-CDs with ciprofloxacin-like structures on its surface, as identified by mass spectrometric (MS) analysis. The as-prepared g-CDs not only exhibit effective antibacterial activity towards the bacteria Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative), but can also optically sense pH in the range from 5.02 to 9.91. Furthermore, the g-CDs can coordinate with aluminum ions to show a chelation-enhanced photoluminescence (CHEP) effect. These results indicate that the ASP method can be promising for engineering CDs with various properties.

Structure-function insights of membrane and soluble proteins revealed by electron crystallography.

PubMed

Dreaden, Tina M; Devarajan, Bharanidharan; Barry, Bridgette A; Schmidt-Krey, Ingeborg

2013-01-01

Electron crystallography is emerging as an important method in solving protein structures. While it has found extensive applications in the understanding of membrane protein structure and function at a wide range of resolutions, from revealing oligomeric arrangements to atomic models, electron crystallography has also provided invaluable information on the soluble α/β-tubulin which could not be obtained by any other method to date. Examples of critical insights from selected structures of membrane proteins as well as α/β-tubulin are described here, demonstrating the vast potential of electron crystallography that is first beginning to unfold.

Controllable assembly and disassembly of nanoparticle systems via protein and DNA agents

DOEpatents

Lee, Soo-Kwan; Gang, Oleg; van der Lelie, Daniel

2014-05-20

The invention relates to the use of peptides, proteins, and other oligomers to provide a means by which normally quenched nanoparticle fluorescence may be recovered upon detection of a target molecule. Further, the inventive technology provides a structure and method to carry out detection of target molecules without the need to label the target molecules before detection. In another aspect, a method for forming arbitrarily shaped two- and three-dimensional protein-mediated nanoparticle structures and the resulting structures are described. Proteins mediating structure formation may themselves be functionalized with a variety of useful moieties, including catalytic functional groups.

Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

PubMed

Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

2014-01-01

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

Computational methods for structural load and resistance modeling

NASA Technical Reports Server (NTRS)

Thacker, B. H.; Millwater, H. R.; Harren, S. V.

1991-01-01

An automated capability for computing structural reliability considering uncertainties in both load and resistance variables is presented. The computations are carried out using an automated Advanced Mean Value iteration algorithm (AMV +) with performance functions involving load and resistance variables obtained by both explicit and implicit methods. A complete description of the procedures used is given as well as several illustrative examples, verified by Monte Carlo Analysis. In particular, the computational methods described in the paper are shown to be quite accurate and efficient for a material nonlinear structure considering material damage as a function of several primitive random variables. The results show clearly the effectiveness of the algorithms for computing the reliability of large-scale structural systems with a maximum number of resolutions.

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Synthesis and optimization of four bar mechanism with six design parameters

NASA Astrophysics Data System (ADS)

Jaiswal, Ankur; Jawale, H. P.

2018-04-01

Function generation is synthesis of mechanism for specific task, involves complexity for specially synthesis above five precision of coupler points. Thus pertains to large structural error. The methodology for arriving to better precision solution is to use the optimization technique. Work presented herein considers methods of optimization of structural error in closed kinematic chain with single degree of freedom, for generating functions like log(x), ex, tan(x), sin(x) with five precision points. The equation in Freudenstein-Chebyshev method is used to develop five point synthesis of mechanism. The extended formulation is proposed and results are obtained to verify existing results in literature. Optimization of structural error is carried out using least square approach. Comparative structural error analysis is presented on optimized error through least square method and extended Freudenstein-Chebyshev method.

HIV-1 Protease Function and Structure Studies with the Simplicial Neighborhood Analysis of Protein Packing (SNAPP) Method

PubMed Central

Zhang, Shuxing; Kaplan, Andrew H.; Tropsha, Alexander

2009-01-01

The Simplicial Neighborhood Analysis of Protein Packing (SNAPP) method was used to predict the effect of mutagenesis on the enzymatic activity of the HIV-1 protease (HIVP). SNAPP relies on a four-body statistical scoring function derived from the analysis of spatially nearest neighbor residue compositional preferences in a diverse and representative subset of protein structures from the Protein Data Bank. The method was applied to the analysis of HIVP mutants with residue substitutions in the hydrophobic core as well as at the interface between the two protease monomers. Both wild type and tethered structures were employed in the calculations. We obtained a strong correlation, with R2 as high as 0.96, between ΔSNAPP score (i.e., the difference in SNAPP scores between wild type and mutant proteins) and the protease catalytic activity for tethered structures. A weaker but significant correlation was also obtained for non-tethered structures as well. Our analysis identified residues both in the hydrophobic core and at the dimeric interface (DI) that are very important for the protease function. This study demonstrates a potential utility of the SNAPP method for rational design of mutagenesis studies and protein engineering. PMID:18498108

Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

PubMed

Smith, Colin A; Kortemme, Tanja

2011-01-01

Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

Phonon dispersions, band structures, and dielectric functions of BeO and BeS polymorphs

NASA Astrophysics Data System (ADS)

Wang, Ke-Long; Gao, Shang-Peng

2018-07-01

Structures, phonon dispersions, electronic structures, and dielectric functions of beryllium oxide (BeO) and beryllium sulfide (BeS) polymorphs are investigated by density functional theory and many-body perturbation theory. Phonon calculations indicate that both wurtzite (w-) and zincblende (zb-) structures are dynamically stable for BeO and BeS, whereas rocksalt (rs-) structures for both BeO and BeS have imaginary phonon frequencies and thus are dynamically unstable at zero pressure. Band structures for the 4 dynamically stable phases show that only w-BeO has a direct band gap. Both the one-shot G0W0 and quasiparticle self-consistent GW methods are used to correct band energies at high symmetry k-points. Bethe-Salpeter equation (BSE), which considers Coulomb correlated electron-hole pairs, is employed to deal with the computation of macroscopic dielectric functions. It is shown that BSE calculation, employing scissors operator derived by self-consistent GW method, can give dielectric functions agreeing very well with experimental measurement of w-BeO. Weak anisotropic characters can be observed for w-BeO and w-BeS. Both zb-BeS and w-BeS show high optical transition probabilities within a narrow ultraviolet energy range.

A scoring function based on solvation thermodynamics for protein structure prediction

PubMed Central

Du, Shiqiao; Harano, Yuichi; Kinoshita, Masahiro; Sakurai, Minoru

2012-01-01

We predict protein structure using our recently developed free energy function for describing protein stability, which is focused on solvation thermodynamics. The function is combined with the current most reliable sampling methods, i.e., fragment assembly (FA) and comparative modeling (CM). The prediction is tested using 11 small proteins for which high-resolution crystal structures are available. For 8 of these proteins, sequence similarities are found in the database, and the prediction is performed with CM. Fairly accurate models with average Cα root mean square deviation (RMSD) ∼ 2.0 Å are successfully obtained for all cases. For the rest of the target proteins, we perform the prediction following FA protocols. For 2 cases, we obtain predicted models with an RMSD ∼ 3.0 Å as the best-scored structures. For the other case, the RMSD remains larger than 7 Å. For all the 11 target proteins, our scoring function identifies the experimentally determined native structure as the best structure. Starting from the predicted structure, replica exchange molecular dynamics is performed to further refine the structures. However, we are unable to improve its RMSD toward the experimental structure. The exhaustive sampling by coarse-grained normal mode analysis around the native structures reveals that our function has a linear correlation with RMSDs < 3.0 Å. These results suggest that the function is quite reliable for the protein structure prediction while the sampling method remains one of the major limiting factors in it. The aspects through which the methodology could further be improved are discussed. PMID:27493529

Undefined freeform surfaces having deterministic structure: issues of their characterization for functionality and manufacture

NASA Astrophysics Data System (ADS)

Whitehouse, David J.

2016-09-01

There is an increasing use of surfaces which have structure, an increase in the use of freeform surfaces, and most importantly an increase in the number of surfaces having both characteristics. These can be called multi-function surfaces, where more than one function is helped by the geometrical features: the structure can help one, the freeform another. Alternatively, they can be complementary to optimize a single function, but in all cases both geometries are involved. This paper examines some of the problems posed by having such disparate geometries on one surface; in particular, the methods of characterization needed to help understand the functionality and also to some extent their manufacture. This involves investigating ways of expressing how local and global geometric features of undefined freeform surfaces might influence function and how surface structure on top of or in series with the freeform affects the nature of the characterization. Some methods have been found of identifying possible strategies for tackling the characterization problem, based in part on the principles of least action and on the way that nature has solved the marriage of flexible freeform geometry and structure on surfaces.

Sensitivity analysis of discrete structural systems: A survey

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.

1984-01-01

Methods for calculating sensitivity derivatives for discrete structural systems are surveyed, primarily covering literature published during the past two decades. Methods are described for calculating derivatives of static displacements and stresses, eigenvalues and eigenvectors, transient structural response, and derivatives of optimum structural designs with respect to problem parameters. The survey is focused on publications addressed to structural analysis, but also includes a number of methods developed in nonstructural fields such as electronics, controls, and physical chemistry which are directly applicable to structural problems. Most notable among the nonstructural-based methods are the adjoint variable technique from control theory, and the Green's function and FAST methods from physical chemistry.

Classification of protein quaternary structure by functional domain composition

PubMed Central

Yu, Xiaojing; Wang, Chuan; Li, Yixue

2006-01-01

Background The number and the arrangement of subunits that form a protein are referred to as quaternary structure. Quaternary structure is an important protein attribute that is closely related to its function. Proteins with quaternary structure are called oligomeric proteins. Oligomeric proteins are involved in various biological processes, such as metabolism, signal transduction, and chromosome replication. Thus, it is highly desirable to develop some computational methods to automatically classify the quaternary structure of proteins from their sequences. Results To explore this problem, we adopted an approach based on the functional domain composition of proteins. Every protein was represented by a vector calculated from the domains in the PFAM database. The nearest neighbor algorithm (NNA) was used for classifying the quaternary structure of proteins from this information. The jackknife cross-validation test was performed on the non-redundant protein dataset in which the sequence identity was less than 25%. The overall success rate obtained is 75.17%. Additionally, to demonstrate the effectiveness of this method, we predicted the proteins in an independent dataset and achieved an overall success rate of 84.11% Conclusion Compared with the amino acid composition method and Blast, the results indicate that the domain composition approach may be a more effective and promising high-throughput method in dealing with this complicated problem in bioinformatics. PMID:16584572

Modeling, estimation and identification methods for static shape determination of flexible structures. [for large space structure design

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling

PubMed Central

MacDonald, James T.; Kelley, Lawrence A.; Freemont, Paul S.

2013-01-01

Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using -carbon positions only and sampling conformations with a Monte Carlo simulated annealing based protocol. Backbone atoms were added using a method previously described and then gradient minimised in the Rosetta force field. Despite the CG potential energy function being sequence-independent, the method performed similarly to methods that explicitly use either fragments of known protein backbones with similar sequences or residue-specific /-maps to restrict the search space. The method was also able to predict with sub-Angstrom accuracy two out of seven loops from recently solved crystal structures of proteins with low sequence and structure similarity to previously deposited structures in the PDB. The ability to sample realistic loop conformations directly from a potential energy function enables the incorporation of additional geometric restraints and the use of more advanced sampling methods in a way that is not possible to do easily with fragment replacement methods and also enable multi-scale simulations for protein design and protein structure prediction. These restraints could be derived from experimental data or could be design restraints in the case of computational protein design. C++ source code is available for download from http://www.sbg.bio.ic.ac.uk/phyre2/PD2/. PMID:23824634

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

A Method to Predict the Structure and Stability of RNA/RNA Complexes.

PubMed

Xu, Xiaojun; Chen, Shi-Jie

2016-01-01

RNA/RNA interactions are essential for genomic RNA dimerization and regulation of gene expression. Intermolecular loop-loop base pairing is a widespread and functionally important tertiary structure motif in RNA machinery. However, computational prediction of intermolecular loop-loop base pairing is challenged by the entropy and free energy calculation due to the conformational constraint and the intermolecular interactions. In this chapter, we describe a recently developed statistical mechanics-based method for the prediction of RNA/RNA complex structures and stabilities. The method is based on the virtual bond RNA folding model (Vfold). The main emphasis in the method is placed on the evaluation of the entropy and free energy for the loops, especially tertiary kissing loops. The method also uses recursive partition function calculations and two-step screening algorithm for large, complicated structures of RNA/RNA complexes. As case studies, we use the HIV-1 Mal dimer and the siRNA/HIV-1 mutant (T4) to illustrate the method.

Characterizing Bonding Patterns in Diradicals and Triradicals by Density-Based Wave Function Analysis: A Uniform Approach.

PubMed

Orms, Natalie; Rehn, Dirk R; Dreuw, Andreas; Krylov, Anna I

2018-02-13

Density-based wave function analysis enables unambiguous comparisons of the electronic structure computed by different methods and removes ambiguity of orbital choices. We use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high- and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of the bonding pattern.

Structural optimization of large structural systems by optimality criteria methods

NASA Technical Reports Server (NTRS)

Berke, Laszlo

1992-01-01

The fundamental concepts of the optimality criteria method of structural optimization are presented. The effect of the separability properties of the objective and constraint functions on the optimality criteria expressions is emphasized. The single constraint case is treated first, followed by the multiple constraint case with a more complex evaluation of the Lagrange multipliers. Examples illustrate the efficiency of the method.

Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.

PubMed

Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino

2017-01-10

In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

PubMed Central

NagaSundaram, N; Priya Doss, C George

2011-01-01

Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype. PMID:22190868

Mobility power flow analysis of an L-shaped plate structure subjected to distributed loading

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.; Cimmerman, B.

1990-01-01

An analytical investigation based in the Mobility Power Flow (MPF) method is presented for the determination of the vibrational response and power flow for two coupled flat plate structures in an L-shaped configuration, subjected to distributed excitation. The principle of the MPF method consists of dividing the global structure into a series of subsystems coupled together using mobility functions. Each separate subsystem is analyzed independently to determine the structural mobility functions for the junction and excitation locations. The mobility functions, together with the characteristics of the junction between the subsystems, are then used to determine the response of the global structure and the MPF. In the considered coupled plate structure, MPF expressions are derived for distributed mechanical excitation which is independent of the structure response. However using a similar approach with some modifications excitation by an acoustic plane wave can be considered. Some modifications are required to deal with the latter case are necessary because the forces (acoustic pressure) acting on the structure are dependent on the response of the structure due to the presence of the scattered pressure.

Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

PubMed

Hsieh, Jui-Hua; Yin, Shuangye; Wang, Xiang S; Liu, Shubin; Dokholyan, Nikolay V; Tropsha, Alexander

2012-01-23

Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening (VS), which is most frequently manifested in the scoring functions' inability to discriminate between true ligands vs known nonbinders (therefore designated as binding decoys). This deficiency leads to a large number of false positive hits resulting from VS. We have hypothesized that filtering out or penalizing docking poses recognized as non-native (i.e., pose decoys) should improve the performance of VS in terms of improved identification of true binders. Using several concepts from the field of cheminformatics, we have developed a novel approach to identifying pose decoys from an ensemble of poses generated by computational docking procedures. We demonstrate that the use of target-specific pose (scoring) filter in combination with a physical force field-based scoring function (MedusaScore) leads to significant improvement of hit rates in VS studies for 12 of the 13 benchmark sets from the clustered version of the Database of Useful Decoys (DUD). This new hybrid scoring function outperforms several conventional structure-based scoring functions, including XSCORE::HMSCORE, ChemScore, PLP, and Chemgauss3, in 6 out of 13 data sets at early stage of VS (up 1% decoys of the screening database). We compare our hybrid method with several novel VS methods that were recently reported to have good performances on the same DUD data sets. We find that the retrieved ligands using our method are chemically more diverse in comparison with two ligand-based methods (FieldScreen and FLAP::LBX). We also compare our method with FLAP::RBLB, a high-performance VS method that also utilizes both the receptor and the cognate ligand structures. Interestingly, we find that the top ligands retrieved using our method are highly complementary to those retrieved using FLAP::RBLB, hinting effective directions for best VS applications. We suggest that this integrative VS approach combining cheminformatics and molecular mechanics methodologies may be applied to a broad variety of protein targets to improve the outcome of structure-based drug discovery studies.

Biocuration in the structure-function linkage database: the anatomy of a superfamily.

PubMed

Holliday, Gemma L; Brown, Shoshana D; Akiva, Eyal; Mischel, David; Hicks, Michael A; Morris, John H; Huang, Conrad C; Meng, Elaine C; Pegg, Scott C-H; Ferrin, Thomas E; Babbitt, Patricia C

2017-01-01

With ever-increasing amounts of sequence data available in both the primary literature and sequence repositories, there is a bottleneck in annotating molecular function to a sequence. This article describes the biocuration process and methods used in the structure-function linkage database (SFLD) to help address some of the challenges. We discuss how the hierarchy within the SFLD allows us to infer detailed functional properties for functionally diverse enzyme superfamilies in which all members are homologous, conserve an aspect of their chemical function and have associated conserved structural features that enable the chemistry. Also presented is the Enzyme Structure-Function Ontology (ESFO), which has been designed to capture the relationships between enzyme sequence, structure and function that underlie the SFLD and is used to guide the biocuration processes within the SFLD. http://sfld.rbvi.ucsf.edu/. © The Author 2017. Published by Oxford University Press.

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming.

PubMed

Gültas, Mehmet; Düzgün, Güncel; Herzog, Sebastian; Jäger, Sven Joachim; Meckbach, Cornelia; Wingender, Edgar; Waack, Stephan

2014-04-03

The identification of functionally or structurally important non-conserved residue sites in protein MSAs is an important challenge for understanding the structural basis and molecular mechanism of protein functions. Despite the rich literature on compensatory mutations as well as sequence conservation analysis for the detection of those important residues, previous methods often rely on classical information-theoretic measures. However, these measures usually do not take into account dis/similarities of amino acids which are likely to be crucial for those residues. In this study, we present a new method, the Quantum Coupled Mutation Finder (QCMF) that incorporates significant dis/similar amino acid pair signals in the prediction of functionally or structurally important sites. The result of this study is twofold. First, using the essential sites of two human proteins, namely epidermal growth factor receptor (EGFR) and glucokinase (GCK), we tested the QCMF-method. The QCMF includes two metrics based on quantum Jensen-Shannon divergence to measure both sequence conservation and compensatory mutations. We found that the QCMF reaches an improved performance in identifying essential sites from MSAs of both proteins with a significantly higher Matthews correlation coefficient (MCC) value in comparison to previous methods. Second, using a data set of 153 proteins, we made a pairwise comparison between QCMF and three conventional methods. This comparison study strongly suggests that QCMF complements the conventional methods for the identification of correlated mutations in MSAs. QCMF utilizes the notion of entanglement, which is a major resource of quantum information, to model significant dissimilar and similar amino acid pair signals in the detection of functionally or structurally important sites. Our results suggest that on the one hand QCMF significantly outperforms the previous method, which mainly focuses on dissimilar amino acid signals, to detect essential sites in proteins. On the other hand, it is complementary to the existing methods for the identification of correlated mutations. The method of QCMF is computationally intensive. To ensure a feasible computation time of the QCMF's algorithm, we leveraged Compute Unified Device Architecture (CUDA).The QCMF server is freely accessible at http://qcmf.informatik.uni-goettingen.de/.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach.

PubMed

Nagasundaram, N; Priya Doss, C George

2011-01-01

Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

The heritability of the functional connectome is robust to common nonlinear registration methods

NASA Astrophysics Data System (ADS)

Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.

2016-03-01

Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.

Ab Initio Structural Modeling of and Experimental Validation for Chlamydia trachomatis Protein CT296 Reveal Structural Similarity to Fe(II) 2-Oxoglutarate-Dependent Enzymes▿

PubMed Central

Kemege, Kyle E.; Hickey, John M.; Lovell, Scott; Battaile, Kevin P.; Zhang, Yang; Hefty, P. Scott

2011-01-01

Chlamydia trachomatis is a medically important pathogen that encodes a relatively high percentage of proteins with unknown function. The three-dimensional structure of a protein can be very informative regarding the protein's functional characteristics; however, determining protein structures experimentally can be very challenging. Computational methods that model protein structures with sufficient accuracy to facilitate functional studies have had notable successes. To evaluate the accuracy and potential impact of computational protein structure modeling of hypothetical proteins encoded by Chlamydia, a successful computational method termed I-TASSER was utilized to model the three-dimensional structure of a hypothetical protein encoded by open reading frame (ORF) CT296. CT296 has been reported to exhibit functional properties of a divalent cation transcription repressor (DcrA), with similarity to the Escherichia coli iron-responsive transcriptional repressor, Fur. Unexpectedly, the I-TASSER model of CT296 exhibited no structural similarity to any DNA-interacting proteins or motifs. To validate the I-TASSER-generated model, the structure of CT296 was solved experimentally using X-ray crystallography. Impressively, the ab initio I-TASSER-generated model closely matched (2.72-Å Cα root mean square deviation [RMSD]) the high-resolution (1.8-Å) crystal structure of CT296. Modeled and experimentally determined structures of CT296 share structural characteristics of non-heme Fe(II) 2-oxoglutarate-dependent enzymes, although key enzymatic residues are not conserved, suggesting a unique biochemical process is likely associated with CT296 function. Additionally, functional analyses did not support prior reports that CT296 has properties shared with divalent cation repressors such as Fur. PMID:21965559

Ab initio structural modeling of and experimental validation for Chlamydia trachomatis protein CT296 reveal structural similarity to Fe(II) 2-oxoglutarate-dependent enzymes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kemege, Kyle E.; Hickey, John M.; Lovell, Scott

2012-02-13

Chlamydia trachomatis is a medically important pathogen that encodes a relatively high percentage of proteins with unknown function. The three-dimensional structure of a protein can be very informative regarding the protein's functional characteristics; however, determining protein structures experimentally can be very challenging. Computational methods that model protein structures with sufficient accuracy to facilitate functional studies have had notable successes. To evaluate the accuracy and potential impact of computational protein structure modeling of hypothetical proteins encoded by Chlamydia, a successful computational method termed I-TASSER was utilized to model the three-dimensional structure of a hypothetical protein encoded by open reading frame (ORF)more » CT296. CT296 has been reported to exhibit functional properties of a divalent cation transcription repressor (DcrA), with similarity to the Escherichia coli iron-responsive transcriptional repressor, Fur. Unexpectedly, the I-TASSER model of CT296 exhibited no structural similarity to any DNA-interacting proteins or motifs. To validate the I-TASSER-generated model, the structure of CT296 was solved experimentally using X-ray crystallography. Impressively, the ab initio I-TASSER-generated model closely matched (2.72-{angstrom} C{alpha} root mean square deviation [RMSD]) the high-resolution (1.8-{angstrom}) crystal structure of CT296. Modeled and experimentally determined structures of CT296 share structural characteristics of non-heme Fe(II) 2-oxoglutarate-dependent enzymes, although key enzymatic residues are not conserved, suggesting a unique biochemical process is likely associated with CT296 function. Additionally, functional analyses did not support prior reports that CT296 has properties shared with divalent cation repressors such as Fur.« less

New strategy for surface functionalization of periodic mesoporous silica based on meso-HSiO1.5.

PubMed

Xie, Zhuoying; Bai, Ling; Huang, Suwen; Zhu, Cun; Zhao, Yuanjin; Gu, Zhong-Ze

2014-01-29

Organic functionalization of periodic mesoporous silicas (PMSs) offers a way to improve their excellent properties and wide applications owing to their structural superiority. In this study, a new strategy for organic functionalization of PMSs is demonstrated by hydrosilylation of the recently discovered "impossible" periodic mesoporous hydridosilica, meso-HSiO1.5. This method overcomes the disadvantages of present pathways for organic functionalization of PMSs with organosilica. Moreover, compared to the traditional functionalization on the surface of porous silicon by hydrosilylation, the template-synthesized meso-HSiO1.5 is more flexible to access functional-groups-loaded PMSs with adjustable microstructures. The new method and materials will have wider applications based on both the structure and surface superiorities.

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

PubMed

Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Structure function monitor

DOEpatents

McGraw, John T [Placitas, NM; Zimmer, Peter C [Albuquerque, NM; Ackermann, Mark R [Albuquerque, NM

2012-01-24

Methods and apparatus for a structure function monitor provide for generation of parameters characterizing a refractive medium. In an embodiment, a structure function monitor acquires images of a pupil plane and an image plane and, from these images, retrieves the phase over an aperture, unwraps the retrieved phase, and analyzes the unwrapped retrieved phase. In an embodiment, analysis yields atmospheric parameters measured at spatial scales from zero to the diameter of a telescope used to collect light from a source.

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

PubMed

Jeong, Chan-Seok; Kim, Dongsup

2016-02-24

Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

Liquid li structure and dynamics: A comparison between OFDFT and second nearest-neighbor embedded-atom method

DOE PAGES

Chen, Mohan; Vella, Joseph R.; Panagiotopoulos, Athanassios Z.; ...

2015-04-08

The structure and dynamics of liquid lithium are studied using two simulation methods: orbital-free (OF) first-principles molecular dynamics (MD), which employs OF density functional theory (DFT), and classical MD utilizing a second nearest-neighbor embedded-atom method potential. The properties we studied include the dynamic structure factor, the self-diffusion coefficient, the dispersion relation, the viscosity, and the bond angle distribution function. Our simulation results were compared to available experimental data when possible. Each method has distinct advantages and disadvantages. For example, OFDFT gives better agreement with experimental dynamic structure factors, yet is more computationally demanding than classical simulations. Classical simulations can accessmore » a broader temperature range and longer time scales. The combination of first-principles and classical simulations is a powerful tool for studying properties of liquid lithium.« less

Accelerating large scale Kohn-Sham density functional theory calculations with semi-local functionals and hybrid functionals

NASA Astrophysics Data System (ADS)

Lin, Lin

The computational cost of standard Kohn-Sham density functional theory (KSDFT) calculations scale cubically with respect to the system size, which limits its use in large scale applications. In recent years, we have developed an alternative procedure called the pole expansion and selected inversion (PEXSI) method. The PEXSI method solves KSDFT without solving any eigenvalue and eigenvector, and directly evaluates physical quantities including electron density, energy, atomic force, density of states, and local density of states. The overall algorithm scales as at most quadratically for all materials including insulators, semiconductors and the difficult metallic systems. The PEXSI method can be efficiently parallelized over 10,000 - 100,000 processors on high performance machines. The PEXSI method has been integrated into a number of community electronic structure software packages such as ATK, BigDFT, CP2K, DGDFT, FHI-aims and SIESTA, and has been used in a number of applications with 2D materials beyond 10,000 atoms. The PEXSI method works for LDA, GGA and meta-GGA functionals. The mathematical structure for hybrid functional KSDFT calculations is significantly different. I will also discuss recent progress on using adaptive compressed exchange method for accelerating hybrid functional calculations. DOE SciDAC Program, DOE CAMERA Program, LBNL LDRD, Sloan Fellowship.

Protein Bricks: 2D and 3D Bio-Nanostructures with Shape and Function on Demand.

PubMed

Jiang, Jianjuan; Zhang, Shaoqing; Qian, Zhigang; Qin, Nan; Song, Wenwen; Sun, Long; Zhou, Zhitao; Shi, Zhifeng; Chen, Liang; Li, Xinxin; Mao, Ying; Kaplan, David L; Gilbert Corder, Stephanie N; Chen, Xinzhong; Liu, Mengkun; Omenetto, Fiorenzo G; Xia, Xiaoxia; Tao, Tiger H

2018-05-01

Precise patterning of polymer-based biomaterials for functional bio-nanostructures has extensive applications including biosensing, tissue engineering, and regenerative medicine. Remarkable progress is made in both top-down (based on lithographic methods) and bottom-up (via self-assembly) approaches with natural and synthetic biopolymers. However, most methods only yield 2D and pseudo-3D structures with restricted geometries and functionalities. Here, it is reported that precise nanostructuring on genetically engineered spider silk by accurately directing ion and electron beam interactions with the protein's matrix at the nanoscale to create well-defined 2D bionanopatterns and further assemble 3D bionanoarchitectures with shape and function on demand, termed "Protein Bricks." The added control over protein sequence and molecular weight of recombinant spider silk via genetic engineering provides unprecedented lithographic resolution (approaching the molecular limit), sharpness, and biological functions compared to natural proteins. This approach provides a facile method for patterning and immobilizing functional molecules within nanoscopic, hierarchical protein structures, which sheds light on a wide range of biomedical applications such as structure-enhanced fluorescence and biomimetic microenvironments for controlling cell fate. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Local atomic structure of Fe/Cr multilayers: Depth-resolved method

NASA Astrophysics Data System (ADS)

Babanov, Yu. A.; Ponomarev, D. A.; Devyaterikov, D. I.; Salamatov, Yu. A.; Romashev, L. N.; Ustinov, V. V.; Vasin, V. V.; Ageev, A. L.

2017-10-01

A depth-resolved method for the investigation of the local atomic structure by combining data of X-ray reflectivity and angle-resolved EXAFS is proposed. The solution of the problem can be divided into three stages: 1) determination of the element concentration profile with the depth z from X-ray reflectivity data, 2) determination of the X-ray fluorescence emission spectrum of the element i absorption coefficient μia (z,E) as a function of depth and photon energy E using the angle-resolved EXAFS data Iif (E , ϑl) , 3) determination of partial correlation functions gij (z , r) as a function of depth from μi (z , E) . All stages of the proposed method are demonstrated on a model example of a multilayer nanoheterostructure Cr/Fe/Cr/Al2O3. Three partial pair correlation functions are obtained. A modified Levenberg-Marquardt algorithm and a regularization method are applied.

Binding ligand prediction for proteins using partial matching of local surface patches.

PubMed

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

PubMed Central

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group. PMID:21614188

Mobility power flow analysis of an L-shaped plate structure subjected to acoustic excitation

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1989-01-01

An analytical investigation based on the Mobility Power Flow method is presented for the determination of the vibrational response and power flow for two coupled flat plate structures in an L-shaped configuration, subjected to acoustical excitation. The principle of the mobility power flow method consists of dividing the global structure into a series of subsystems coupled together using mobility functions. Each separate subsystem is analyzed independently to determine the structural mobility functions for the junction and excitation locations. The mobility functions, together with the characteristics of the junction between the subsystems, are then used to determine the response of the global structure and the power flow. In the coupled plate structure considered here, mobility power flow expressions are derived for excitation by an incident acoustic plane wave. In this case, the forces (acoustic pressures) acting on the structure are dependent on the response of the structure because of the scattered pressure component. The interaction between the structure and the fluid leads to the derivation of a corrected mode shape for the plates' normal surface velocity and also for the structure mobility functions. The determination of the scattered pressure components in the expressions for the power flow represents an additional component in the power flow balance for the source plate and the receiver plate. This component represents the radiated acoustical power from the plate structure.

Altered osteoblast structure and function in parabolic flight

NASA Astrophysics Data System (ADS)

Zhong-Quan, Dai; Ying-Hui, Li; Fen, Yang; Bai, Ding; Ying-Jun, Tan

Introduction Bone loss has a significant impact on astronauts during spaceflight being one of the main obstacles preventing interplanetary missions However the exact mechanism is not well understood In the present study we investigated the effects of acute gravitational changes generated by parabolic flight on the structure and function of osteoblasts ROS17 2 8 carried by airbus A300 Methods The alteration of microfilament cytoskeleton was observed by the Texas red conjugated Phalloidin and Alexa Fluor 488 conjugated DNase I immunofluorescence stain ALP activity and expression COL1A1 expression osteocalcin secrete which presenting the osteoblast function were detected by modified calcium and cobalt method RT-PCR and radioimmunity methods respectively Results The changed gravity induced the reorganization of microfilament cytoskeleton of osteoblast After 3 hours parabolic flight F-actin of osteoblast cytoskeleton became more thickness and directivity whereas G-actin reduced and relatively concentrated at the edge of nucleus observed by confocal fluorescence microscopy This phenomenon is identical with structure alternation observed in hypergravity but the osteoblast function decrease The excretion of osteocalcin the activity and mRNA expression of ALP decrease but the COL1A1 expression has no changes These results were similar to the changes in simulated or real microgravity Conclusion Above results suggest that short time gravity alternative change induce osteoblast structure and function

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

A Novel Method of Extraction of Blend Component Structure from SANS Measurements of Homopolymer Bimodal Blends.

PubMed

Smerdova, Olga; Graham, Richard S; Gasser, Urs; Hutchings, Lian R; De Focatiis, Davide S A

2014-05-01

A new method is presented for the extraction of single-chain form factors and interchain interference functions from a range of small-angle neutron scattering (SANS) experiments on bimodal homopolymer blends. The method requires a minimum of three blends, made up of hydrogenated and deuterated components with matched degree of polymerization at two different chain lengths, but with carefully varying deuteration levels. The method is validated through an experimental study on polystyrene homopolymer bimodal blends with [Formula: see text]. By fitting Debye functions to the structure factors, it is shown that there is good agreement between the molar mass of the components obtained from SANS and from chromatography. The extraction method also enables, for the first time, interchain scattering functions to be produced for scattering between chains of different lengths. [Formula: see text].

Dawn of the in vivo RNA structurome and interactome.

PubMed

Kwok, Chun Kit

2016-10-15

RNA is one of the most fascinating biomolecules in living systems given its structural versatility to fold into elaborate architectures for important biological functions such as gene regulation, catalysis, and information storage. Knowledge of RNA structures and interactions can provide deep insights into their functional roles in vivo For decades, RNA structural studies have been conducted on a transcript-by-transcript basis. The advent of next-generation sequencing (NGS) has enabled the development of transcriptome-wide structural probing methods to profile the global landscape of RNA structures and interactions, also known as the RNA structurome and interactome, which transformed our understanding of the RNA structure-function relationship on a transcriptomic scale. In this review, molecular tools and NGS methods used for RNA structure probing are presented, novel insights uncovered by RNA structurome and interactome studies are highlighted, and perspectives on current challenges and potential future directions are discussed. A more complete understanding of the RNA structures and interactions in vivo will help illuminate the novel roles of RNA in gene regulation, development, and diseases. © 2016 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Multiphase Interface Tracking with Fast Semi-Lagrangian Contouring.

PubMed

Li, Xiaosheng; He, Xiaowei; Liu, Xuehui; Zhang, Jian J; Liu, Baoquan; Wu, Enhua

2016-08-01

We propose a semi-Lagrangian method for multiphase interface tracking. In contrast to previous methods, our method maintains an explicit polygonal mesh, which is reconstructed from an unsigned distance function and an indicator function, to track the interface of arbitrary number of phases. The surface mesh is reconstructed at each step using an efficient multiphase polygonization procedure with precomputed stencils while the distance and indicator function are updated with an accurate semi-Lagrangian path tracing from the meshes of the last step. Furthermore, we provide an adaptive data structure, multiphase distance tree, to accelerate the updating of both the distance function and the indicator function. In addition, the adaptive structure also enables us to contour the distance tree accurately with simple bisection techniques. The major advantage of our method is that it can easily handle topological changes without ambiguities and preserve both the sharp features and the volume well. We will evaluate its efficiency, accuracy and robustness in the results part with several examples.

A simplified method of evaluating the stress wave environment of internal equipment

NASA Technical Reports Server (NTRS)

Colton, J. D.; Desmond, T. P.

1979-01-01

A simplified method called the transfer function technique (TFT) was devised for evaluating the stress wave environment in a structure containing internal equipment. The TFT consists of following the initial in-plane stress wave that propagates through a structure subjected to a dynamic load and characterizing how the wave is altered as it is transmitted through intersections of structural members. As a basis for evaluating the TFT, impact experiments and detailed stress wave analyses were performed for structures with two or three, or more members. Transfer functions that relate the wave transmitted through an intersection to the incident wave were deduced from the predicted wave response. By sequentially applying these transfer functions to a structure with several intersections, it was found that the environment produced by the initial stress wave propagating through the structure can be approximated well. The TFT can be used as a design tool or as an analytical tool to determine whether a more detailed wave analysis is warranted.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

Improving Glaucoma Detection Using Spatially Correspondent Clusters of Damage and by Combining Standard Automated Perimetry and Optical Coherence Tomography

PubMed Central

Raza, Ali S.; Zhang, Xian; De Moraes, Carlos G. V.; Reisman, Charles A.; Liebmann, Jeffrey M.; Ritch, Robert; Hood, Donald C.

2014-01-01

Purpose. To improve the detection of glaucoma, techniques for assessing local patterns of damage and for combining structure and function were developed. Methods. Standard automated perimetry (SAP) and frequency-domain optical coherence tomography (fdOCT) data, consisting of macular retinal ganglion cell plus inner plexiform layer (mRGCPL) as well as macular and optic disc retinal nerve fiber layer (mRNFL and dRNFL) thicknesses, were collected from 52 eyes of 52 healthy controls and 156 eyes of 96 glaucoma suspects and patients. In addition to generating simple global metrics, SAP and fdOCT data were searched for contiguous clusters of abnormal points and converted to a continuous metric (pcc). The pcc metric, along with simpler methods, was used to combine the information from the SAP and fdOCT. The performance of different methods was assessed using the area under receiver operator characteristic curves (AROC scores). Results. The pcc metric performed better than simple global measures for both the fdOCT and SAP. The best combined structure-function metric (mRGCPL&SAP pcc, AROC = 0.868 ± 0.032) was better (statistically significant) than the best metrics for independent measures of structure and function. When SAP was used as part of the inclusion and exclusion criteria, AROC scores increased for all metrics, including the best combined structure-function metric (AROC = 0.975 ± 0.014). Conclusions. A combined structure-function metric improved the detection of glaucomatous eyes. Overall, the primary sources of value-added for glaucoma detection stem from the continuous cluster search (the pcc), the mRGCPL data, and the combination of structure and function. PMID:24408977

A guide to large-scale RNA sample preparation.

PubMed

Baronti, Lorenzo; Karlsson, Hampus; Marušič, Maja; Petzold, Katja

2018-05-01

RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods. Graphical abstract In this review we present different methods for large-scale production and purification of RNAs for structural and biophysical studies.

The FLAME-slab method for electromagnetic wave scattering in aperiodic slabs

NASA Astrophysics Data System (ADS)

Mansha, Shampy; Tsukerman, Igor; Chong, Y. D.

2017-12-01

The proposed numerical method, "FLAME-slab," solves electromagnetic wave scattering problems for aperiodic slab structures by exploiting short-range regularities in these structures. The computational procedure involves special difference schemes with high accuracy even on coarse grids. These schemes are based on Trefftz approximations, utilizing functions that locally satisfy the governing differential equations, as is done in the Flexible Local Approximation Method (FLAME). Radiation boundary conditions are implemented via Fourier expansions in the air surrounding the slab. When applied to ensembles of slab structures with identical short-range features, such as amorphous or quasicrystalline lattices, the method is significantly more efficient, both in runtime and in memory consumption, than traditional approaches. This efficiency is due to the fact that the Trefftz functions need to be computed only once for the whole ensemble.

Tools to evaluate the conformation of protein products.

PubMed

Manta, Bruno; Obal, Gonzalo; Ricciardi, Alejandro; Pritsch, Otto; Denicola, Ana

2011-06-01

Production of recombinant proteins is a process intensively used in the research laboratory. In addition, the main biotechnology market products are recombinant proteins and monoclonal antibodies. The biological (and clinical) properties of the protein product strongly depend on the conformation of the polypeptide. Therefore, assessment of the correct conformation of the produced protein is crucial. There is no single method to assess every aspect of protein structure or function. Depending on the protein, the methods of choice vary. There are general methods to evaluate not only mass and primary sequence of the protein, but also higher-order structure. This review outlines the principal techniques for determining the conformation of a protein from structural (biophysical methods) to functional (in vitro binding assays) analyses. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

PubMed

Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

2015-12-15

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Challenges in NMR-based structural genomics

NASA Astrophysics Data System (ADS)

Sue, Shih-Che; Chang, Chi-Fon; Huang, Yao-Te; Chou, Ching-Yu; Huang, Tai-huang

2005-05-01

Understanding the functions of the vast number of proteins encoded in many genomes that have been completely sequenced recently is the main challenge for biologists in the post-genomics era. Since the function of a protein is determined by its exact three-dimensional structure it is paramount to determine the 3D structures of all proteins. This need has driven structural biologists to undertake the structural genomics project aimed at determining the structures of all known proteins. Several centers for structural genomics studies have been established throughout the world. Nuclear magnetic resonance (NMR) spectroscopy has played a major role in determining protein structures in atomic details and in a physiologically relevant solution state. Since the number of new genes being discovered daily far exceeds the number of structures determined by both NMR and X-ray crystallography, a high-throughput method for speeding up the process of protein structure determination is essential for the success of the structural genomics effort. In this article we will describe NMR methods currently being employed for protein structure determination. We will also describe methods under development which may drastically increase the throughput, as well as point out areas where opportunities exist for biophysicists to make significant contribution in this important field.

Towards Long-Range RNA Structure Prediction in Eukaryotic Genes.

PubMed

Pervouchine, Dmitri D

2018-06-15

The ability to form an intramolecular structure plays a fundamental role in eukaryotic RNA biogenesis. Proximate regions in the primary transcripts fold into a local secondary structure, which is then hierarchically assembled into a tertiary structure that is stabilized by RNA-binding proteins and long-range intramolecular base pairings. While the local RNA structure can be predicted reasonably well for short sequences, long-range structure at the scale of eukaryotic genes remains problematic from the computational standpoint. The aim of this review is to list functional examples of long-range RNA structures, to summarize current comparative methods of structure prediction, and to highlight their advances and limitations in the context of long-range RNA structures. Most comparative methods implement the “first-align-then-fold” principle, i.e., they operate on multiple sequence alignments, while functional RNA structures often reside in non-conserved parts of the primary transcripts. The opposite “first-fold-then-align” approach is currently explored to a much lesser extent. Developing novel methods in both directions will improve the performance of comparative RNA structure analysis and help discover novel long-range structures, their higher-order organization, and RNA⁻RNA interactions across the transcriptome.

Band structures in coupled-cluster singles-and-doubles Green's function (GFCCSD)

NASA Astrophysics Data System (ADS)

Furukawa, Yoritaka; Kosugi, Taichi; Nishi, Hirofumi; Matsushita, Yu-ichiro

2018-05-01

We demonstrate that the coupled-cluster singles-and-doubles Green's function (GFCCSD) method is a powerful and prominent tool drawing the electronic band structures and the total energies, which many theoretical techniques struggle to reproduce. We have calculated single-electron energy spectra via the GFCCSD method for various kinds of systems, ranging from ionic to covalent and van der Waals, for the first time: the one-dimensional LiH chain, one-dimensional C chain, and one-dimensional Be chain. We have found that the bandgap becomes narrower than in HF due to the correlation effect. We also show that the band structures obtained from the GFCCSD method include both quasiparticle and satellite peaks successfully. Besides, taking one-dimensional LiH as an example, we discuss the validity of restricting the active space to suppress the computational cost of the GFCCSD method. We show that the calculated results without bands that do not contribute to the chemical bonds are in good agreement with full-band calculations. With the GFCCSD method, we can calculate the total energies and spectral functions for periodic systems in an explicitly correlated manner.

Advances in Fabrication Materials of Honeycomb Structure Films by the Breath-Figure Method

PubMed Central

Heng, Liping; Wang, Bin; Li, Muchen; Zhang, Yuqi; Jiang, Lei

2013-01-01

Creatures in nature possess almost perfect structures and properties, and exhibit harmonization and unification between structure and function. Biomimetics, mimicking nature for engineering solutions, provides a model for the development of functional surfaces with special properties. Recently, honeycomb structure materials have attracted wide attention for both fundamental research and practical applications and have become an increasingly hot research topic. Though progress in the field of breath-figure formation has been reviewed, the advance in the fabrication materials of bio-inspired honeycomb structure films has not been discussed. Here we review the recent progress of honeycomb structure fabrication materials which were prepared by the breath-figure method. The application of breath figures for the generation of all kinds of honeycomb is discussed. PMID:28809319

Electronic Structure Calculation of Permanent Magnets using the KKR Green's Function Method

NASA Astrophysics Data System (ADS)

Doi, Shotaro; Akai, Hisazumi

2014-03-01

Electronic structure and magnetic properties of permanent magnetic materials, especially Nd2Fe14B, are investigated theoretically using the KKR Green's function method. Important physical quantities in magnetism, such as magnetic moment, Curie temperature, and anisotropy constant, which are obtained from electronics structure calculations in both cases of atomic-sphere-approximation and full-potential treatment, are compared with past band structure calculations and experiments. The site preference of heavy rare-earth impurities are also evaluated through the calculation of formation energy with the use of coherent potential approximations. Further, the development of electronic structure calculation code using the screened KKR for large super-cells, which is aimed at studying the electronic structure of realistic microstructures (e.g. grain boundary phase), is introduced with some test calculations.

The Protein Structure Initiative Structural Biology Knowledgebase Technology Portal: a structural biology web resource.

PubMed

Gifford, Lida K; Carter, Lester G; Gabanyi, Margaret J; Berman, Helen M; Adams, Paul D

2012-06-01

The Technology Portal of the Protein Structure Initiative Structural Biology Knowledgebase (PSI SBKB; http://technology.sbkb.org/portal/ ) is a web resource providing information about methods and tools that can be used to relieve bottlenecks in many areas of protein production and structural biology research. Several useful features are available on the web site, including multiple ways to search the database of over 250 technological advances, a link to videos of methods on YouTube, and access to a technology forum where scientists can connect, ask questions, get news, and develop collaborations. The Technology Portal is a component of the PSI SBKB ( http://sbkb.org ), which presents integrated genomic, structural, and functional information for all protein sequence targets selected by the Protein Structure Initiative. Created in collaboration with the Nature Publishing Group, the SBKB offers an array of resources for structural biologists, such as a research library, editorials about new research advances, a featured biological system each month, and a functional sleuth for searching protein structures of unknown function. An overview of the various features and examples of user searches highlight the information, tools, and avenues for scientific interaction available through the Technology Portal.

Relationship between global structural parameters and Enzyme Commission hierarchy: implications for function prediction.

PubMed

Boareto, Marcelo; Yamagishi, Michel E B; Caticha, Nestor; Leite, Vitor B P

2012-10-01

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. Copyright © 2012 Elsevier Ltd. All rights reserved.

High-Aspect-Ratio Ridge Structures Induced by Plastic Deformation as a Novel Microfabrication Technique.

PubMed

Takei, Atsushi; Jin, Lihua; Fujita, Hiroyuki; Takei, A; Fujita, H; Jin, Lihua

2016-09-14

Wrinkles on thin film/elastomer bilayer systems provide functional surfaces. The aspect ratio of these wrinkles is critical to their functionality. Much effort has been dedicated to creating high-aspect-ratio structures on the surface of bilayer systems. A highly prestretched elastomer attached to a thin film has recently been shown to form a high-aspect-ratio structure, called a ridge structure, due to a large strain induced in the elastomer. However, the prestretch requirements of the elastomer during thin film attachment are not compatible with conventional thin film deposition methods, such as spin coating, dip coating, and chemical vapor deposition (CVD). Thus, the fabrication method is complex, and ridge structure formation is limited to planar surfaces. This paper presents a new and simple method for constructing ridge structures on a nonplanar surface using a plastic thin film/elastomer bilayer system. A plastic thin film is attached to a stress-free elastomer, and the resulting bilayer system is highly stretched one- or two-dimensionally. Upon the release of the stretch load, the deformation of the elastomer is reversible, while the plastically deformed thin film stays elongated. The combination of the length mismatch and the large strain induced in the elastomer generates ridge structures. The morphology of the plastic thin film/elastomer bilayer system is experimentally studied by varying the physical parameters, and the functionality and the applicability to a nonplanar surface are demonstrated. Finally, we simulate the effect of plasticity on morphology. This study presents a new technique for generating microscale high-aspect-ratio structures and its potential for functional surfaces.

Introduction to the Wetland Book 1: Wetland structure and function, management, and nethods

USGS Publications Warehouse

Davidson, Nick C.; Middleton, Beth A.; McInnes, Robert J.; Everard, Mark; Irvine, Kenneth; Van Dam, Anne A.; Finlayson, C. Max; Finlayson, C. Max; Everard, Mark; Irvine, Kenneth; McInnes, Robert J.; Middleton, Beth A.; Van Dam, Anne A.; Davidson, Nick C.

2016-01-01

The Wetland Book 1 is designed as a ‘first port-of-call’ reference work for information on the structure and functions of wetlands, current approaches to wetland management, and methods for researching and understanding wetlands. Contributions by experts summarize key concepts, orient the reader to the major issues, and support further research on such issues by individuals and multidisciplinary teams. The Wetland Book 1 is organized in three parts - Wetland structure and function; Wetland management; and Wetland methods - each of which is divided into a number of thematic Sections. Each Section starts with one or more overview chapters, supported by chapters providing further information and case studies on different aspects of the theme.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Defining functional distance using manifold embeddings of gene ontology annotations

PubMed Central

Lerman, Gilad; Shakhnovich, Boris E.

2007-01-01

Although rigorous measures of similarity for sequence and structure are now well established, the problem of defining functional relationships has been particularly daunting. Here, we present several manifold embedding techniques to compute distances between Gene Ontology (GO) functional annotations and consequently estimate functional distances between protein domains. To evaluate accuracy, we correlate the functional distance to the well established measures of sequence, structural, and phylogenetic similarities. Finally, we show that manual classification of structures into folds and superfamilies is mirrored by proximity in the newly defined function space. We show how functional distances place structure–function relationships in biological context resulting in insight into divergent and convergent evolution. The methods and results in this paper can be readily generalized and applied to a wide array of biologically relevant investigations, such as accuracy of annotation transference, the relationship between sequence, structure, and function, or coherence of expression modules. PMID:17595300

A simulator for evaluating methods for the detection of lesion-deficit associations

NASA Technical Reports Server (NTRS)

Megalooikonomou, V.; Davatzikos, C.; Herskovits, E. H.

2000-01-01

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

Thermodynamics of RNA structures by Wang–Landau sampling

PubMed Central

Lou, Feng; Clote, Peter

2010-01-01

Motivation: Thermodynamics-based dynamic programming RNA secondary structure algorithms have been of immense importance in molecular biology, where applications range from the detection of novel selenoproteins using expressed sequence tag (EST) data, to the determination of microRNA genes and their targets. Dynamic programming algorithms have been developed to compute the minimum free energy secondary structure and partition function of a given RNA sequence, the minimum free-energy and partition function for the hybridization of two RNA molecules, etc. However, the applicability of dynamic programming methods depends on disallowing certain types of interactions (pseudoknots, zig-zags, etc.), as their inclusion renders structure prediction an nondeterministic polynomial time (NP)-complete problem. Nevertheless, such interactions have been observed in X-ray structures. Results: A non-Boltzmannian Monte Carlo algorithm was designed by Wang and Landau to estimate the density of states for complex systems, such as the Ising model, that exhibit a phase transition. In this article, we apply the Wang-Landau (WL) method to compute the density of states for secondary structures of a given RNA sequence, and for hybridizations of two RNA sequences. Our method is shown to be much faster than existent software, such as RNAsubopt. From density of states, we compute the partition function over all secondary structures and over all pseudoknot-free hybridizations. The advantage of the WL method is that by adding a function to evaluate the free energy of arbitary pseudoknotted structures and of arbitrary hybridizations, we can estimate thermodynamic parameters for situations known to be NP-complete. This extension to pseudoknots will be made in the sequel to this article; in contrast, the current article describes the WL algorithm applied to pseudoknot-free secondary structures and hybridizations. Availability: The WL RNA hybridization web server is under construction at http://bioinformatics.bc.edu/clotelab/. Contact: clote@bc.edu PMID:20529917

Numerical simulation of intelligent compaction technology for construction quality control.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

Structural system reliability calculation using a probabilistic fault tree analysis method

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.; Millwater, H. R.

1992-01-01

The development of a new probabilistic fault tree analysis (PFTA) method for calculating structural system reliability is summarized. The proposed PFTA procedure includes: developing a fault tree to represent the complex structural system, constructing an approximation function for each bottom event, determining a dominant sampling sequence for all bottom events, and calculating the system reliability using an adaptive importance sampling method. PFTA is suitable for complicated structural problems that require computer-intensive computer calculations. A computer program has been developed to implement the PFTA.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method.

PubMed

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-05-16

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

PubMed Central

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-01-01

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions.

PubMed

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Structural and Functional Assessment of APOBEC3G Macromolecular Complexes

PubMed Central

Polevoda, Bogdan; McDougall, William M.; Bennett, Ryan P.; Salter, Jason D.; Smith, Harold C.

2016-01-01

There are eleven members in the human APOBEC family of proteins that are evolutionarily related through their zinc-dependent cytidine deaminase domains. The human APOBEC gene clusters arose on chromosome 6 and 22 through gene duplication and divergence to where current day APOBEC proteins are functionally diverse and broadly expressed in tissues. APOBEC serve enzymatic and non enzymatic functions in cells. In both cases, formation of higher-order structures driven by APOBEC protein-protein interactions and binding to RNA and/or single stranded DNA are integral to their function. In some circumstances, these interactions are regulatory and modulate APOBEC activities. We are just beginning to understand how macromolecular interactions drive processes such as APOBEC subcellular compartmentalization, formation of holoenzyme complexes, gene targeting, foreign DNA restriction, anti-retroviral activity, formation of ribonucleoprotein particles and APOBEC degradation. Protein-protein and protein-nucleic acid cross-linking methods coupled with mass spectrometry, electrophoretic mobility shift assays, glycerol gradient sedimentation, fluorescence anisotropy and APOBEC deaminase assays are enabling mapping of interacting surfaces that are essential for these functions. The goal of this methods review is through example of our research on APOBEC3G, describe the application of cross-linking methods to characterize and quantify macromolecular interactions and their functional implications. Given the homology in structure and function, it is proposed that these methods will be generally applicable to the discovery process for other APOBEC and RNA and DNA editing and modifying proteins. PMID:26988126

Spectral analysis of structure functions and their scaling exponents in forced isotropic turbulence

NASA Astrophysics Data System (ADS)

Linkmann, Moritz; McComb, W. David; Yoffe, Samuel; Berera, Arjun

2014-11-01

The pseudospectral method, in conjunction with a new technique for obtaining scaling exponents ζn from the structure functions Sn (r) , is presented as an alternative to the extended self-similarity (ESS) method and the use of generalized structure functions. We propose plotting the ratio | Sn (r) /S3 (r) | against the separation r in accordance with a standard technique for analysing experimental data. This method differs from the ESS technique, which plots the generalized structure functions Gn (r) against G3 (r) , where G3 (r) ~ r . Using our method for the particular case of S2 (r) we obtain the new result that the exponent ζ2 decreases as the Taylor-Reynolds number increases, with ζ2 --> 0 . 679 +/- 0 . 013 as Rλ --> ∞ . This supports the idea of finite-viscosity corrections to the K41 prediction for S2, and is the opposite of the result obtained by ESS. The pseudospectral method permits the forcing to be taken into account exactly through the calculation of the energy input in real space from the work spectrum of the stirring forces. The combination of the viscous and the forcing corrections as calculated by the pseudospectral method is shown to account for the deviation of S3 from Kolmogorov's ``four-fifths''-law at all scales. This work has made use of the resources provided by the UK supercomputing service HECToR, made available through the Edinburgh Compute and Data Facility (ECDF). A. B. is supported by STFC, S. R. Y. and M. F. L. are funded by EPSRC.

General Retarded Contact Self-energies in and beyond the Non-equilibrium Green's Functions Method

NASA Astrophysics Data System (ADS)

Kubis, Tillmann; He, Yu; Andrawis, Robert; Klimeck, Gerhard

2016-03-01

Retarded contact self-energies in the framework of nonequilibrium Green's functions allow to model the impact of lead structures on the device without explicitly including the leads in the actual device calculation. Most of the contact self-energy algorithms are limited to homogeneous or periodic, semi-infinite lead structures. In this work, the complex absorbing potential method is extended to solve retarded contact self-energies for arbitrary lead structures, including irregular and randomly disordered leads. This method is verified for regular leads against common approaches and on physically equivalent, but numerically different irregular leads. Transmission results on randomly alloyed In0.5Ga0.5As structures show the importance of disorder in the leads. The concept of retarded contact self-energies is expanded to model passivation of atomically resolved surfaces without explicitly increasing the device's Hamiltonian.

Structural reliability analysis under evidence theory using the active learning kriging model

NASA Astrophysics Data System (ADS)

Yang, Xufeng; Liu, Yongshou; Ma, Panke

2017-11-01

Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.

De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.

PubMed

Lee, Juyong; Lee, Jinhyuk; Sasaki, Takeshi N; Sasai, Masaki; Seok, Chaok; Lee, Jooyoung

2011-08-01

Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods. Copyright © 2011 Wiley-Liss, Inc.

PASCAL vs BASIC

ERIC Educational Resources Information Center

Mundie, David A.

1978-01-01

A comparison between PASCAL and BASIC as general purpose microprocessor languages rates PASCAL above BASIC in such points as program structure, data types, structuring methods, control structures, procedures and functions, and ease in learning. (CMV)

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

DOE PAGES

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas; ...

2017-12-21

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Local and average structure of Mn- and La-substituted BiFeO3

NASA Astrophysics Data System (ADS)

Jiang, Bo; Selbach, Sverre M.

2017-06-01

The local and average structure of solid solutions of the multiferroic perovskite BiFeO3 is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space group symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO3. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions.

Local and average structure of Mn- and La-substituted BiFeO 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Bo; Selbach, Sverre M.

2017-06-01

The local and average structure of solid solutions of the multiferroic perovskite BiFeO 3 is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space groupmore » symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO 3. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions.« less

The invariant of the stiffness filter function with the weight filter function of the power function form

NASA Astrophysics Data System (ADS)

Shang, Zhen; Sui, Yun-Kang

2012-12-01

Based on the independent, continuous and mapping (ICM) method and homogenization method, a research model is constructed to propose and deduce a theorem and corollary from the invariant between the weight filter function and the corresponding stiffness filter function of the form of power function. The efficiency in searching for optimum solution will be raised via the choice of rational filter functions, so the above mentioned results are very important to the further study of structural topology optimization.

Detection of functionally important regions in "hypothetical proteins" of known structure.

PubMed

Nimrod, Guy; Schushan, Maya; Steinberg, David M; Ben-Tal, Nir

2008-12-10

Structural genomics initiatives provide ample structures of "hypothetical proteins" (i.e., proteins of unknown function) at an ever increasing rate. However, without function annotation, this structural goldmine is of little use to biologists who are interested in particular molecular systems. To this end, we used (an improved version of) the PatchFinder algorithm for the detection of functional regions on the protein surface, which could mediate its interactions with, e.g., substrates, ligands, and other proteins. Examination, using a data set of annotated proteins, showed that PatchFinder outperforms similar methods. We collected 757 structures of hypothetical proteins and their predicted functional regions in the N-Func database. Inspection of several of these regions demonstrated that they are useful for function prediction. For example, we suggested an interprotein interface and a putative nucleotide-binding site. A web-server implementation of PatchFinder and the N-Func database are available at http://patchfinder.tau.ac.il/.

R-chie: a web server and R package for visualizing RNA secondary structures

PubMed Central

Lai, Daniel; Proctor, Jeff R.; Zhu, Jing Yun A.; Meyer, Irmtraud M.

2012-01-01

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-chie as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems. PMID:22434875

Assignment of functional activations to probabilistic cytoarchitectonic areas revisited.

PubMed

Eickhoff, Simon B; Paus, Tomas; Caspers, Svenja; Grosbras, Marie-Helene; Evans, Alan C; Zilles, Karl; Amunts, Katrin

2007-07-01

Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure-function relationships in the human brain. While these microstructurally defined maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure-function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure-function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the "central tendency" of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.

Elastic Green’s Function in Anisotropic Bimaterials Considering Interfacial Elasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Juan, Pierre -Alexandre; Dingreville, Remi

Here, the two-dimensional elastic Green’s function is calculated for a general anisotropic elastic bimaterial containing a line dislocation and a concentrated force while accounting for the interfacial structure by means of a generalized interfacial elasticity paradigm. The introduction of the interface elasticity model gives rise to boundary conditions that are effectively equivalent to those of a weakly bounded interface. The equations of elastic equilibrium are solved by complex variable techniques and the method of analytical continuation. The solution is decomposed into the sum of the Green’s function corresponding to the perfectly bonded interface and a perturbation term corresponding to themore » complex coupling nature between the interface structure and a line dislocation/concentrated force. Such construct can be implemented into the boundary integral equations and the boundary element method for analysis of nano-layered structures and epitaxial systems where the interface structure plays an important role.« less

Structure determination and characterization of two rare-earth molybdenum borate compounds: LnMoBO(6) (Ln = La, Ce).

PubMed

Zhao, Dan; Cheng, Wen-Dan; Zhang, Hao; Hang, Shu-Ping; Fang, Ming

2008-07-28

The structural, optical, and electronic properties of two rare-earth molybdenum borate compounds, LnMoBO(6) (Ln = La, Ce), have been investigated by means of single-crystal X-ray diffraction, elemental analyses, and spectral measurements, as well as calculations of energy band structures, density of states, and optical response functions by the density functional method. The title compounds, which crystallize in monoclinic space group P2(1)/c, possess a similar network of interconnected [Ce(2)(MoO(4))(2)](2+) chains and [BO(2)](-) wavy chains. Novel 1D molybdenum oxide chains are contained in their three-dimensional (3D) networks. The calculated results of crystal energy band structure by the density functional theory (DFT) method show that the solid-state compound LaMoBO(6) is a semiconductor with indirect band gaps.

Elastic Green’s Function in Anisotropic Bimaterials Considering Interfacial Elasticity

DOE PAGES

Juan, Pierre -Alexandre; Dingreville, Remi

2017-09-13

Here, the two-dimensional elastic Green’s function is calculated for a general anisotropic elastic bimaterial containing a line dislocation and a concentrated force while accounting for the interfacial structure by means of a generalized interfacial elasticity paradigm. The introduction of the interface elasticity model gives rise to boundary conditions that are effectively equivalent to those of a weakly bounded interface. The equations of elastic equilibrium are solved by complex variable techniques and the method of analytical continuation. The solution is decomposed into the sum of the Green’s function corresponding to the perfectly bonded interface and a perturbation term corresponding to themore » complex coupling nature between the interface structure and a line dislocation/concentrated force. Such construct can be implemented into the boundary integral equations and the boundary element method for analysis of nano-layered structures and epitaxial systems where the interface structure plays an important role.« less

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

PubMed

Robinson, Lucy F; Atlas, Lauren Y; Wager, Tor D

2015-03-01

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Local structure analysis on (La,Ba)(Ga,Mg)O3-δ by the pair distribution function method using a neutron source and density functional theory calculations

NASA Astrophysics Data System (ADS)

Kitamura, Naoto; Vogel, Sven C.; Idemoto, Yasushi

2013-06-01

In this work, we focused on La0.95Ba0.05Ga0.8Mg0.2O3-δ with the perovskite structure, and investigated the local structure around the oxygen vacancy by pair distribution function (PDF) method and density functional theory (DFT) calculation. By comparing the G(r) simulated based on the DFT calculation and the experimentally-observed G(r), it was suggested that the oxygen vacancy was trapped by Ba2+ at the La3+ site at least at room temperature. Such a defect association may be one of the reasons why the La0.95Ba0.05Ga0.8Mg0.2O3-δ showed lower oxide-ion conductivity than (La,Sr)(Ga,Mg)O3-δ which was widely-used as an electrolyte of the solid oxide fuel cell.

Antibody Epitope Analysis to Investigate Folded Structure, Allosteric Conformation, and Evolutionary Lineage of Proteins.

PubMed

Wong, Sienna; Jin, J-P

2017-01-01

Study of folded structure of proteins provides insights into their biological functions, conformational dynamics and molecular evolution. Current methods of elucidating folded structure of proteins are laborious, low-throughput, and constrained by various limitations. Arising from these methods is the need for a sensitive, quantitative, rapid and high-throughput method not only analysing the folded structure of proteins, but also to monitor dynamic changes under physiological or experimental conditions. In this focused review, we outline the foundation and limitations of current protein structure-determination methods prior to discussing the advantages of an emerging antibody epitope analysis for applications in structural, conformational and evolutionary studies of proteins. We discuss the application of this method using representative examples in monitoring allosteric conformation of regulatory proteins and the determination of the evolutionary lineage of related proteins and protein isoforms. The versatility of the method described herein is validated by the ability to modulate a variety of assay parameters to meet the needs of the user in order to monitor protein conformation. Furthermore, the assay has been used to clarify the lineage of troponin isoforms beyond what has been depicted by sequence homology alone, demonstrating the nonlinear evolutionary relationship between primary structure and tertiary structure of proteins. The antibody epitope analysis method is a highly adaptable technique of protein conformation elucidation, which can be easily applied without the need for specialized equipment or technical expertise. When applied in a systematic and strategic manner, this method has the potential to reveal novel and biomedically meaningful information for structure-function relationship and evolutionary lineage of proteins. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Layered Searchable Encryption Scheme with Functional Components Independent of Encryption Methods

PubMed Central

Luo, Guangchun; Qin, Ke

2014-01-01

Searchable encryption technique enables the users to securely store and search their documents over the remote semitrusted server, which is especially suitable for protecting sensitive data in the cloud. However, various settings (based on symmetric or asymmetric encryption) and functionalities (ranked keyword query, range query, phrase query, etc.) are often realized by different methods with different searchable structures that are generally not compatible with each other, which limits the scope of application and hinders the functional extensions. We prove that asymmetric searchable structure could be converted to symmetric structure, and functions could be modeled separately apart from the core searchable structure. Based on this observation, we propose a layered searchable encryption (LSE) scheme, which provides compatibility, flexibility, and security for various settings and functionalities. In this scheme, the outputs of the core searchable component based on either symmetric or asymmetric setting are converted to some uniform mappings, which are then transmitted to loosely coupled functional components to further filter the results. In such a way, all functional components could directly support both symmetric and asymmetric settings. Based on LSE, we propose two representative and novel constructions for ranked keyword query (previously only available in symmetric scheme) and range query (previously only available in asymmetric scheme). PMID:24719565

QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information.

PubMed

Benkert, Pascal; Schwede, Torsten; Tosatto, Silvio Ce

2009-05-20

The selection of the most accurate protein model from a set of alternatives is a crucial step in protein structure prediction both in template-based and ab initio approaches. Scoring functions have been developed which can either return a quality estimate for a single model or derive a score from the information contained in the ensemble of models for a given sequence. Local structural features occurring more frequently in the ensemble have a greater probability of being correct. Within the context of the CASP experiment, these so called consensus methods have been shown to perform considerably better in selecting good candidate models, but tend to fail if the best models are far from the dominant structural cluster. In this paper we show that model selection can be improved if both approaches are combined by pre-filtering the models used during the calculation of the structural consensus. Our recently published QMEAN composite scoring function has been improved by including an all-atom interaction potential term. The preliminary model ranking based on the new QMEAN score is used to select a subset of reliable models against which the structural consensus score is calculated. This scoring function called QMEANclust achieves a correlation coefficient of predicted quality score and GDT_TS of 0.9 averaged over the 98 CASP7 targets and perform significantly better in selecting good models from the ensemble of server models than any other groups participating in the quality estimation category of CASP7. Both scoring functions are also benchmarked on the MOULDER test set consisting of 20 target proteins each with 300 alternatives models generated by MODELLER. QMEAN outperforms all other tested scoring functions operating on individual models, while the consensus method QMEANclust only works properly on decoy sets containing a certain fraction of near-native conformations. We also present a local version of QMEAN for the per-residue estimation of model quality (QMEANlocal) and compare it to a new local consensus-based approach. Improved model selection is obtained by using a composite scoring function operating on single models in order to enrich higher quality models which are subsequently used to calculate the structural consensus. The performance of consensus-based methods such as QMEANclust highly depends on the composition and quality of the model ensemble to be analysed. Therefore, performance estimates for consensus methods based on large meta-datasets (e.g. CASP) might overrate their applicability in more realistic modelling situations with smaller sets of models based on individual methods.

Efficient High-Fidelity, Geometrically Exact, Multiphysics Structural Models

DTIC Science & Technology

2011-10-14

fuctionally graded core. International Journal for Numerical Methods in Engineering, 68:940– 966, 2006. 7F. Shang, Z. Wang, and Z. Li. Analysis of...normal deformable plate theory and MLPG method with radial basis fuctions . Composite Structures, 80:539– 552, 2007. 17W. Zhen and W. Chen. A higher-order...functionally graded plates by using higher-order shear and normal deformable plate theory and MLPG method with radial basis fuctions . Composite Structures, 80

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase.

PubMed

Venko, Katja; Roy Choudhury, A; Novič, Marjana

2017-01-01

The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helix-helix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.

Structural assurance testing for post-shipping satellite inspection

NASA Astrophysics Data System (ADS)

Reynolds, Whitney D.; Doyle, Derek; Arritt, Brandon

2012-04-01

Current satellite transportation sensors can provide a binary indication of the acceleration or shock that a satellite has experienced during the shipping process but do little to identify if significant structural change has occurred in the satellite and where it may be located. When a sensor indicates that the satellite has experienced shock during transit, an extensive testing process begins to evaluate the satellite functionality. If errors occur during the functional checkout, extensive physical inspection of the structure follows. In this work an alternate method for inspecting satellites for structural defects after shipping is presented. Electro- Mechanical Impedance measurements are used as an indication of the structural state. In partnership with the Air Force Research Laboratory University Nanosatellite Program, Cornell's CUSat mass model was instrumented with piezoelectric transducers and tested under several structural damage scenarios. A method for detecting and locating changes in the structure using EMI data is presented.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

A Multi-Resolution Data Structure for Two-Dimensional Morse Functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bremer, P-T; Edelsbrunner, H; Hamann, B

2003-07-30

The efficient construction of simplified models is a central problem in the field of visualization. We combine topological and geometric methods to construct a multi-resolution data structure for functions over two-dimensional domains. Starting with the Morse-Smale complex we build a hierarchy by progressively canceling critical points in pairs. The data structure supports mesh traversal operations similar to traditional multi-resolution representations.

Method for analyzing soil structure according to the size of structural elements

NASA Astrophysics Data System (ADS)

Wieland, Ralf; Rogasik, Helmut

2015-02-01

The soil structure in situ is the result of cropping history and soil development over time. It can be assessed by the size distribution of soil structural elements such as air-filled macro-pores, aggregates and stones, which are responsible for important water and solute transport processes, gas exchange, and the stability of the soil against compacting and shearing forces exerted by agricultural machinery. A method was developed to detect structural elements of the soil in selected horizontal slices of soil core samples with different soil structures in order for them to be implemented accordingly. In the second step, a fitting tool (Eureqa) based on artificial programming was used to find a general function to describe ordered sets of detected structural elements. It was shown that all the samples obey a hyperbolic function: Y(k) = A /(B + k) , k ∈ { 0 , 1 , 2 , … }. This general behavior can be used to develop a classification method based on parameters {A and B}. An open source software program in Python was developed, which can be downloaded together with a selection of soil samples.

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

An RNA Origami Octahedron with Intrinsic siRNAs for Potent Gene Knockdown.

PubMed

Høiberg, Hans Christian; Sparvath, Steffen M; Andersen, Veronica L; Kjems, Jørgen; Andersen, Ebbe S

2018-05-26

The fields of DNA and RNA nanotechnology have established nucleic acids as valuable building blocks for functional nanodevices with applications in nanomedicine. Here, a simple method for designing and assembling a 3D scaffolded RNA origami wireframe structure with intrinsic functioning small interfering RNAs (siRNAs) embedded is introduced. Uniquely, the method uses an mRNA fragment as scaffold strand, which is folded by sequence-complementarity of nine shorter synthetic strands. High-yield production of the intended 3D structure is verified by transmission electron microscopy (TEM). Production of functional siRNAs is facilitated by incorporating recognition sites for Dicer at selected locations in the structure, and efficient silencing of a target reporter gene is demonstrated. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A level set-based topology optimization method for simultaneous design of elastic structure and coupled acoustic cavity using a two-phase material model

NASA Astrophysics Data System (ADS)

Noguchi, Yuki; Yamamoto, Takashi; Yamada, Takayuki; Izui, Kazuhiro; Nishiwaki, Shinji

2017-09-01

This papers proposes a level set-based topology optimization method for the simultaneous design of acoustic and structural material distributions. In this study, we develop a two-phase material model that is a mixture of an elastic material and acoustic medium, to represent an elastic structure and an acoustic cavity by controlling a volume fraction parameter. In the proposed model, boundary conditions at the two-phase material boundaries are satisfied naturally, avoiding the need to express these boundaries explicitly. We formulate a topology optimization problem to minimize the sound pressure level using this two-phase material model and a level set-based method that obtains topologies free from grayscales. The topological derivative of the objective functional is approximately derived using a variational approach and the adjoint variable method and is utilized to update the level set function via a time evolutionary reaction-diffusion equation. Several numerical examples present optimal acoustic and structural topologies that minimize the sound pressure generated from a vibrating elastic structure.

FuncPatch: a web server for the fast Bayesian inference of conserved functional patches in protein 3D structures.

PubMed

Huang, Yi-Fei; Golding, G Brian

2015-02-15

A number of statistical phylogenetic methods have been developed to infer conserved functional sites or regions in proteins. Many methods, e.g. Rate4Site, apply the standard phylogenetic models to infer site-specific substitution rates and totally ignore the spatial correlation of substitution rates in protein tertiary structures, which may reduce their power to identify conserved functional patches in protein tertiary structures when the sequences used in the analysis are highly similar. The 3D sliding window method has been proposed to infer conserved functional patches in protein tertiary structures, but the window size, which reflects the strength of the spatial correlation, must be predefined and is not inferred from data. We recently developed GP4Rate to solve these problems under the Bayesian framework. Unfortunately, GP4Rate is computationally slow. Here, we present an intuitive web server, FuncPatch, to perform a fast approximate Bayesian inference of conserved functional patches in protein tertiary structures. Both simulations and four case studies based on empirical data suggest that FuncPatch is a good approximation to GP4Rate. However, FuncPatch is orders of magnitudes faster than GP4Rate. In addition, simulations suggest that FuncPatch is potentially a useful tool complementary to Rate4Site, but the 3D sliding window method is less powerful than FuncPatch and Rate4Site. The functional patches predicted by FuncPatch in the four case studies are supported by experimental evidence, which corroborates the usefulness of FuncPatch. The software FuncPatch is freely available at the web site, http://info.mcmaster.ca/yifei/FuncPatch golding@mcmaster.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

[Structural analysis of the functional status of the brain as affected by bemethyl using pattern recognition theory].

PubMed

Bobkov, Iu G; Machula, A I; Morozov, Iu I; Dvalishvili, E G

1987-11-01

Evoked visual potentials in associated, parietal and second somatosensory zones of the neocortex were analysed in trained cats using implanted electrodes. The influence of bemethyl on the structure of behavioral reactions was analysed using theoretical methods of perceptual images, particularly the method of cluster analysis. Bemethyl was shown to increase the level of interaction between the functional elements of the system, leading to a more stable resolution of problems facing the system, as compared to the initial state.

General software design for multisensor data fusion

NASA Astrophysics Data System (ADS)

Zhang, Junliang; Zhao, Yuming

1999-03-01

In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programing and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

Dynamic condensation of non-classically damped structures using the method of Maclaurin expansion of the frequency response function in Laplace domain

NASA Astrophysics Data System (ADS)

Esmaeilzad, Armin; Khanlari, Karen

2018-07-01

As the number of degrees of freedom (DOFs) in structural dynamic problems becomes larger, the analyzing complexity and CPU usage of computers increase drastically. Condensation (or reduction) method is an efficient technique to reduce the size of the full model or the dimension of the structural matrices by eliminating the unimportant DOFs. After the first presentation of condensation method by Guyan in 1965 for undamped structures, which ignores the dynamic effects of the mass term, various forms of dynamic condensation methods were presented to overcome this issue. Moreover, researchers have tried to expand the dynamic condensation method to non-classically damped structures. Dynamic reduction of such systems is far more complicated than undamped systems. The proposed non-iterative method in this paper is introduced as 'Maclaurin Expansion of the frequency response function in Laplace Domain' (MELD) applied for dynamic reduction of non-classically damped structures. The present approach is implemented in four numerical examples of 2D bending-shear-axial frames with various numbers of stories and spans and also a floating raft isolation system. The results of natural frequencies and dynamic responses of models are compared with each other before and after the dynamic reduction. It is shown that the result accuracy has acceptable convergence in both cases. In addition, it is indicated that the result of the proposed method is more accurate than the results of some other existing condensation methods.

Structural imaging of mild traumatic brain injury may not be enough: overview of functional and metabolic imaging of mild traumatic brain injury.

PubMed

Shin, Samuel S; Bales, James W; Edward Dixon, C; Hwang, Misun

2017-04-01

A majority of patients with traumatic brain injury (TBI) present as mild injury with no findings on conventional clinical imaging methods. Due to this difficulty of imaging assessment on mild TBI patients, there has been much emphasis on the development of diffusion imaging modalities such as diffusion tensor imaging (DTI). However, basic science research in TBI shows that many of the functional and metabolic abnormalities in TBI may be present even in the absence of structural damage. Moreover, structural damage may be present at a microscopic and molecular level that is not detectable by structural imaging modality. The use of functional and metabolic imaging modalities can provide information on pathological changes in mild TBI patients that may not be detected by structural imaging. Although there are various differences in protocols of positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) methods, these may be important modalities to be used in conjunction with structural imaging in the future in order to detect and understand the pathophysiology of mild TBI. In this review, studies of mild TBI patients using these modalities that detect functional and metabolic state of the brain are discussed. Each modality's advantages and disadvantages are compared, and potential future applications of using combined modalities are explored.

Efficient conformational space exploration in ab initio protein folding simulation.

PubMed

Ullah, Ahammed; Ahmed, Nasif; Pappu, Subrata Dey; Shatabda, Swakkhar; Ullah, A Z M Dayem; Rahman, M Sohel

2015-08-01

Ab initio protein folding simulation largely depends on knowledge-based energy functions that are derived from known protein structures using statistical methods. These knowledge-based energy functions provide us with a good approximation of real protein energetics. However, these energy functions are not very informative for search algorithms and fail to distinguish the types of amino acid interactions that contribute largely to the energy function from those that do not. As a result, search algorithms frequently get trapped into the local minima. On the other hand, the hydrophobic-polar (HP) model considers hydrophobic interactions only. The simplified nature of HP energy function makes it limited only to a low-resolution model. In this paper, we present a strategy to derive a non-uniform scaled version of the real 20×20 pairwise energy function. The non-uniform scaling helps tackle the difficulty faced by a real energy function, whereas the integration of 20×20 pairwise information overcomes the limitations faced by the HP energy function. Here, we have applied a derived energy function with a genetic algorithm on discrete lattices. On a standard set of benchmark protein sequences, our approach significantly outperforms the state-of-the-art methods for similar models. Our approach has been able to explore regions of the conformational space which all the previous methods have failed to explore. Effectiveness of the derived energy function is presented by showing qualitative differences and similarities of the sampled structures to the native structures. Number of objective function evaluation in a single run of the algorithm is used as a comparison metric to demonstrate efficiency.

Development of new maskless manufacturing method for anti-reflection structure and application to large-area lens with curved surface

NASA Astrophysics Data System (ADS)

Yamamoto, Kazuya; Takaoka, Toshimitsu; Fukui, Hidetoshi; Haruta, Yasuyuki; Yamashita, Tomoya; Kitagawa, Seiichiro

2016-03-01

In general, thin-film coating process is widely applied on optical lens surface as anti-reflection function. In normal production process, at first lens is manufactured by molding, then anti-reflection is added by thin-film coating. In recent years, instead of thin-film coating, sub-wavelength structures adding on surface of molding die are widely studied and development to keep anti-reflection performance. As merits, applying sub-wavelength structure, coating process becomes unnecessary and it is possible to reduce man-hour costs. In addition to cost merit, these are some technical advantages on this study. Adhesion of coating depends on material of plastic, and it is impossible to apply anti-reflection function on arbitrary surface. Sub-wavelength structure can solve both problems. Manufacturing method of anti-reflection structure can be divided into two types mainly. One method is with the resist patterning, and the other is mask-less method that does not require patterning. What we have developed is new mask-less method which is no need for resist patterning and possible to impart an anti-reflection structure to large area and curved lens surface, and can be expected to apply to various market segments. We report developed technique and characteristics of production lens.

An Immersed Boundary method with divergence-free velocity interpolation and force spreading

NASA Astrophysics Data System (ADS)

Bao, Yuanxun; Donev, Aleksandar; Griffith, Boyce E.; McQueen, David M.; Peskin, Charles S.

2017-10-01

The Immersed Boundary (IB) method is a mathematical framework for constructing robust numerical methods to study fluid-structure interaction in problems involving an elastic structure immersed in a viscous fluid. The IB formulation uses an Eulerian representation of the fluid and a Lagrangian representation of the structure. The Lagrangian and Eulerian frames are coupled by integral transforms with delta function kernels. The discretized IB equations use approximations to these transforms with regularized delta function kernels to interpolate the fluid velocity to the structure, and to spread structural forces to the fluid. It is well-known that the conventional IB method can suffer from poor volume conservation since the interpolated Lagrangian velocity field is not generally divergence-free, and so this can cause spurious volume changes. In practice, the lack of volume conservation is especially pronounced for cases where there are large pressure differences across thin structural boundaries. The aim of this paper is to greatly reduce the volume error of the IB method by introducing velocity-interpolation and force-spreading schemes with the properties that the interpolated velocity field in which the structure moves is at least C1 and satisfies a continuous divergence-free condition, and that the force-spreading operator is the adjoint of the velocity-interpolation operator. We confirm through numerical experiments in two and three spatial dimensions that this new IB method is able to achieve substantial improvement in volume conservation compared to other existing IB methods, at the expense of a modest increase in the computational cost. Further, the new method provides smoother Lagrangian forces (tractions) than traditional IB methods. The method presented here is restricted to periodic computational domains. Its generalization to non-periodic domains is important future work.

Structural and functional neural correlates of music perception.

PubMed

Limb, Charles J

2006-04-01

This review article highlights state-of-the-art functional neuroimaging studies and demonstrates the novel use of music as a tool for the study of human auditory brain structure and function. Music is a unique auditory stimulus with properties that make it a compelling tool with which to study both human behavior and, more specifically, the neural elements involved in the processing of sound. Functional neuroimaging techniques represent a modern and powerful method of investigation into neural structure and functional correlates in the living organism. These methods have demonstrated a close relationship between the neural processing of music and language, both syntactically and semantically. Greater neural activity and increased volume of gray matter in Heschl's gyrus has been associated with musical aptitude. Activation of Broca's area, a region traditionally considered to subserve language, is important in interpreting whether a note is on or off key. The planum temporale shows asymmetries that are associated with the phenomenon of perfect pitch. Functional imaging studies have also demonstrated activation of primitive emotional centers such as ventral striatum, midbrain, amygdala, orbitofrontal cortex, and ventral medial prefrontal cortex in listeners of moving musical passages. In addition, studies of melody and rhythm perception have elucidated mechanisms of hemispheric specialization. These studies show the power of music and functional neuroimaging to provide singularly useful tools for the study of brain structure and function.

Dynamic GSCA (Generalized Structured Component Analysis) with Applications to the Analysis of Effective Connectivity in Functional Neuroimaging Data

ERIC Educational Resources Information Center

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S.

2012-01-01

We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also…

Applications of matched field processing to damage detection in composite wind turbine blades

NASA Astrophysics Data System (ADS)

Tippmann, Jeffery D.; Lanza di Scalea, Francesco

2015-03-01

There are many structures serving vital infrastructure, energy, and national security purposes. Inspecting the components and areas of the structure most prone to failure during maintenance operations by using non- destructive evaluation methods has been essential in avoiding costly, but preventable, catastrophic failures. In many cases, the inspections are performed by introducing acoustic, ultrasonic, or even thermographic waves into the structure and then evaluating the response. Sometimes the structure, or a component, is not accessible for active inspection methods. Because of this, there is a growing interest to use passive methods, such as using ambient noise, or sources of opportunity, to produce a passive impulse response function similar to the active approach. Several matched field processing techniques most notably used in oceanography and seismology applications are examined in more detail. While sparse array imaging in structures has been studied for years, all methods studied previously have used an active interrogation approach. Here, structural damage detection is studied by use of the reconstructed impulse response functions in ambient noise within sparse array imaging techniques, such as matched-field processing. This has been studied in experiments on a 9-m wind turbine blade.

Electronic Structure and Transport in Solids from First Principles

NASA Astrophysics Data System (ADS)

Mustafa, Jamal Ibrahim

The focus of this dissertation is the determination of the electronic structure and trans- port properties of solids. We first review some of the theory and computational methodology used in the calculation of electronic structure and materials properties. Throughout the dissertation, we make extensive use of state-of-the-art software packages that implement density functional theory, density functional perturbation theory, and the GW approximation, in addition to specialized methods for interpolating matrix elements for extremely accurate results. The first application of the computational framework introduced is the determination of band offsets in semiconductor heterojunctions using a theory of quantum dipoles at the interface. This method is applied to the case of heterojunction formed between a new metastable phase of silicon, with a rhombohedral structure, and cubic silicon. Next, we introduce a novel method for the construction of localized Wannier functions, which we have named the optimized projection functions method (OPFM). We illustrate the method on a variety of systems and find that it can reliably construct localized Wannier functions with minimal user intervention. We further develop the OPFM to investigate a class of materials called topological insulators, which are insulating in the bulk but have conductive surface states. These properties are a result of a nontrivial topology in their band structure, which has interesting effects on the character of the Wannier functions. In the last sections of the main text, the noble metals are studied in great detail, including their electronic properties and carrier dynamics. In particular, we investigate, the Fermi surface properties of the noble metals, specifically electron-phonon scattering lifetimes, and subsequently the transport properties determined by carriers on the Fermi surface. To achieve this, a novel sampling technique is developed, with wide applicability to transport calculations. Additionally, the generation and transport of hot carriers is studied extensively. The distribution of hot carriers generated from the decay of plasmons is explored over a range of energy, and the transport properties, particularly the lifetimes and mean-free-paths, of the hot carriers are determined. Lastly, appendices detailing the implementation of the algorithms developed in the work is presented, along with a useful derivation of the electron-plasmon matrix elements.

Kinetics and mechanism of catalytic hydroprocessing of components of coal-derived liquids. Sixteenth quarterly report, February 16, 1983-May 15, 1983.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gates, B. C.; Olson, H. H.; Schuit, G. C.A.

1983-08-22

A new method of structural analysis is applied to a group of hydroliquefied coal samples. The method uses elemental analysis and NMR data to estimate the concentrations of functional groups in the samples. The samples include oil and asphaltene fractions obtained in a series of hydroliquefaction experiments, and a set of 9 fractions separated from a coal-derived oil. The structural characterization of these samples demonstrates that estimates of functional group concentrations can be used to provide detailed structural profiles of complex mixtures and to obtain limited information about reaction pathways. 11 references, 1 figure, 7 tables.

Decision support methodology to establish priorities on the inspection of structures

NASA Astrophysics Data System (ADS)

Cortes, V. Juliette; Sterlacchini, Simone; Bogaard, Thom; Frigerio, Simone; Schenato, Luca; Pasuto, Alessandro

2014-05-01

For hydro-meteorological hazards in mountain areas, the regular inspection of check dams and bridges is important due to the effect of their functional status on water-sediment processes. Moreover, the inspection of these structures is time consuming for organizations due to their extensive number in many regions. However, trained citizen-volunteers can support civil protection and technical services in the frequency, timeliness and coverage of monitoring the functional status of hydraulic structures. Technicians should evaluate and validate these reports to get an index for the status of the structure. Thus, preventive actions could initiate such as the cleaning of obstructions or to pre-screen potential problems for a second level inspection. This study proposes a decision support methodology that technicians can use to assess an index for three parameters representing the functional status of the structure: a) condition of the structure at the opening of the stream flow, b) level of obstruction at the structure and c) the level of erosion in the stream bank. The calculation of the index for each parameter is based upon fuzzy logic theory to handle ranges in precision of the reports and to convert the linguistic rating scales into numbers representing the structure's status. A weighting method and multi-criteria method (Analytic Hierarchy Process- AHP and TOPSIS), can be used by technicians to combine the different ratings according to the component elements of the structure and the completeness of the reports. Finally, technicians can set decision rules based on the worst rating and a threshold for the functional indexes. The methodology was implemented as a prototype web-based tool to be tested with technicians of the Civil Protection in the Fella basin, Northern Italy. Results at this stage comprise the design and implementation of the web-based tool with GIS interaction to evaluate available reports and to set priorities on the inspection of structures. Keywords Decision-making, Multi-criteria methods, Torrent control structures, Web-based tools.

Application of kernel functions for accurate similarity search in large chemical databases.

PubMed

Wang, Xiaohong; Huan, Jun; Smalter, Aaron; Lushington, Gerald H

2010-04-29

Similarity search in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions can not be applied to large chemical compound database due to the high computational complexity and the difficulties in indexing similarity search for large databases. To bridge graph kernel function and similarity search in chemical databases, we applied a novel kernel-based similarity measurement, developed in our team, to measure similarity of graph represented chemicals. In our method, we utilize a hash table to support new graph kernel function definition, efficient storage and fast search. We have applied our method, named G-hash, to large chemical databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Moreover, the similarity measurement and the index structure is scalable to large chemical databases with smaller indexing size, and faster query processing time as compared to state-of-the-art indexing methods such as Daylight fingerprints, C-tree and GraphGrep. Efficient similarity query processing method for large chemical databases is challenging since we need to balance running time efficiency and similarity search accuracy. Our previous similarity search method, G-hash, provides a new way to perform similarity search in chemical databases. Experimental study validates the utility of G-hash in chemical databases.

Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

PubMed Central

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-01-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC–vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder. PMID:28944772

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder.

PubMed

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-04-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.

Characterizing left-right gait balance using footstep-induced structural vibrations

NASA Astrophysics Data System (ADS)

Fagert, Jonathon; Mirshekari, Mostafa; Pan, Shijia; Zhang, Pei; Noh, Hae Young

2017-04-01

In this paper, we introduce a method for estimating human left/right walking gait balance using footstep-induced structural vibrations. Understanding human gait balance is an integral component of assessing gait, neurological and musculoskeletal conditions, overall health status, and risk of falls. Existing techniques utilize pressure- sensing mats, wearable devices, and human observation-based assessment by healthcare providers. These existing methods are collectively limited in their operation and deployment; often requiring dense sensor deployment or direct user interaction. To address these limitations, we utilize footstep-induced structural vibration responses. Based on the physical insight that the vibration energy is a function of the force exerted by a footstep, we calculate the vibration signal energy due to a footstep and use it to estimate the footstep force. By comparing the footstep forces while walking, we determine balance. This approach enables non-intrusive gait balance assessment using sparsely deployed sensors. The primary research challenge is that the floor vibration signal energy is also significantly affected by the distance between the footstep location and the vibration sensor; this function is unclear in real-world scenarios and is a mixed function of wave propagation and structure-dependent properties. We overcome this challenge through footstep localization and incorporating structural factors into an analytical force-energy-distance function. This function is estimated through a nonlinear least squares regression analysis. We evaluate the performance of our method with a real-world deployment in a campus building. Our approach estimates footstep forces with a RMSE of 61.0N (8% of participant's body weight), representing a 1.54X improvement over the baseline.

Can enzyme engineering benefit from the modulation of protein motions? Lessons learned from NMR relaxation dispersion experiments.

PubMed

Doucet, Nicolas

2011-04-01

Despite impressive progress in protein engineering and design, our ability to create new and efficient enzyme activities remains a laborious and time-consuming endeavor. In the past few years, intricate combinations of rational mutagenesis, directed evolution and computational methods have paved the way to exciting engineering examples and are now offering a new perspective on the structural requirements of enzyme activity. However, these structure-function analyses are usually guided by the time-averaged static models offered by enzyme crystal structures, which often fail to describe the functionally relevant 'invisible states' adopted by proteins in space and time. To alleviate such limitations, NMR relaxation dispersion experiments coupled to mutagenesis studies have recently been applied to the study of enzyme catalysis, effectively complementing 'structure-function' analyses with 'flexibility-function' investigations. In addition to offering quantitative, site-specific information to help characterize residue motion, these NMR methods are now being applied to enzyme engineering purposes, providing a powerful tool to help characterize the effects of controlling long-range networks of flexible residues affecting enzyme function. Recent advancements in this emerging field are presented here, with particular attention to mutagenesis reports highlighting the relevance of NMR relaxation dispersion tools in enzyme engineering.

Deforming black hole and cosmological solutions by quasiperiodic and/or pattern forming structures in modified and Einstein gravity

NASA Astrophysics Data System (ADS)

Bubuianu, Laurenţiu; Vacaru, Sergiu I.

2018-05-01

We elaborate on the anholonomic frame deformation method, AFDM, for constructing exact solutions with quasiperiodic structure in modified gravity theories, MGTs, and general relativity, GR. Such solutions are described by generic off-diagonal metrics, nonlinear and linear connections and (effective) matter sources with coefficients depending on all spacetime coordinates via corresponding classes of generation and integration functions and (effective) matter sources. There are studied effective free energy functionals and nonlinear evolution equations for generating off-diagonal quasiperiodic deformations of black hole and/or homogeneous cosmological metrics. The physical data for such functionals are stated by different values of constants and prescribed symmetries for defining quasiperiodic structures at cosmological scales, or astrophysical objects in nontrivial gravitational backgrounds some similar forms as in condensed matter physics. It is shown how quasiperiodic structures determined by general nonlinear, or additive, functionals for generating functions and (effective) sources may transform black hole like configurations into cosmological metrics and inversely. We speculate on possible implications of quasiperiodic solutions in dark energy and dark matter physics. Finally, it is concluded that geometric methods for constructing exact solutions consist an important alternative tool to numerical relativity for investigating nonlinear effects in astrophysics and cosmology.

Metal-ligand delocalization and spin density in the CuCl2 and [CuCl4](2-) molecules: Some insights from wave function theory.

PubMed

Giner, Emmanuel; Angeli, Celestino

2015-09-28

The aim of this paper is to unravel the physical phenomena involved in the calculation of the spin density of the CuCl2 and [CuCl4](2-) systems using wave function methods. Various types of wave functions are used here, both variational and perturbative, to analyse the effects impacting the spin density. It is found that the spin density on the chlorine ligands strongly depends on the mixing between two types of valence bond structures. It is demonstrated that the main difficulties found in most of the previous studies based on wave function methods come from the fact that each valence bond structure requires a different set of molecular orbitals and that using a unique set of molecular orbitals in a variational procedure leads to the removal of one of them from the wave function. Starting from these results, a method to compute the spin density at a reasonable computational cost is proposed.

Advances in structural and functional analysis of membrane proteins by electron crystallography

PubMed Central

Wisedchaisri, Goragot; Reichow, Steve L.; Gonen, Tamir

2011-01-01

Summary Electron crystallography is a powerful technique for the study of membrane protein structure and function in the lipid environment. When well-ordered two-dimensional crystals are obtained the structure of both protein and lipid can be determined and lipid-protein interactions analyzed. Protons and ionic charges can be visualized by electron crystallography and the protein of interest can be captured for structural analysis in a variety of physiologically distinct states. This review highlights the strengths of electron crystallography and the momentum that is building up in automation and the development of high throughput tools and methods for structural and functional analysis of membrane proteins by electron crystallography. PMID:22000511

Advances in structural and functional analysis of membrane proteins by electron crystallography.

PubMed

Wisedchaisri, Goragot; Reichow, Steve L; Gonen, Tamir

2011-10-12

Electron crystallography is a powerful technique for the study of membrane protein structure and function in the lipid environment. When well-ordered two-dimensional crystals are obtained the structure of both protein and lipid can be determined and lipid-protein interactions analyzed. Protons and ionic charges can be visualized by electron crystallography and the protein of interest can be captured for structural analysis in a variety of physiologically distinct states. This review highlights the strengths of electron crystallography and the momentum that is building up in automation and the development of high throughput tools and methods for structural and functional analysis of membrane proteins by electron crystallography. Copyright © 2011 Elsevier Ltd. All rights reserved.

Methods to enable the design of bioactive small molecules targeting RNA

PubMed Central

Disney, Matthew D.; Yildirim, Ilyas; Childs-Disney, Jessica L.

2014-01-01

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including Structure-Activity Relationships Through Sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome. PMID:24357181

Methods to enable the design of bioactive small molecules targeting RNA.

PubMed

Disney, Matthew D; Yildirim, Ilyas; Childs-Disney, Jessica L

2014-02-21

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including structure-activity relationships through sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome.

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

From protein structure to function via single crystal optical spectroscopy

PubMed Central

Ronda, Luca; Bruno, Stefano; Bettati, Stefano; Storici, Paola; Mozzarelli, Andrea

2015-01-01

The more than 100,000 protein structures determined by X-ray crystallography provide a wealth of information for the characterization of biological processes at the molecular level. However, several crystallographic “artifacts,” including conformational selection, crystallization conditions and radiation damages, may affect the quality and the interpretation of the electron density maps, thus limiting the relevance of structure determinations. Moreover, for most of these structures, no functional data have been obtained in the crystalline state, thus posing serious questions on their validity in infereing protein mechanisms. In order to solve these issues, spectroscopic methods have been applied for the determination of equilibrium and kinetic properties of proteins in the crystalline state. These methods are UV-vis spectrophotometry, spectrofluorimetry, IR, EPR, Raman, and resonance Raman spectroscopy. Some of these approaches have been implemented with on-line instruments at X-ray synchrotron beamlines. Here, we provide an overview of investigations predominantly carried out in our laboratory by single crystal polarized absorption UV-vis microspectrophotometry, the most applied technique for the functional characterization of proteins in the crystalline state. Studies on hemoglobins, pyridoxal 5′-phosphate dependent enzymes and green fluorescent protein in the crystalline state have addressed key biological issues, leading to either straightforward structure-function correlations or limitations to structure-based mechanisms. PMID:25988179

Mapping urban forest structure and function using hyperspectral imagery and lidar data

Treesearch

Michael Alonzo; Joseph P. McFadden; David J. Nowak; Dar A. Roberts

2016-01-01

Cities measure the structure and function of their urban forest resource to optimize forest managementand the provision of ecosystem services. Measurements made using plot sampling methods yield useful results including citywide or land-use level estimates of species counts, leaf area, biomass, and air pollution reduction. However, these quantities are statistical...

Generalized self-adjustment method for statistical mechanics of composite materials

NASA Astrophysics Data System (ADS)

Pan'kov, A. A.

1997-03-01

A new method is developed for the statistical mechanics of composite materials — the generalized selfadjustment method — which makes it possible to reduce the problem of predicting effective elastic properties of composites with random structures to the solution of two simpler "averaged" problems of an inclusion with transitional layers in a medium with the desired effective elastic properties. The inhomogeneous elastic properties and dimensions of the transitional layers take into account both the "approximate" order of mutual positioning, and also the variation in the dimensions and elastics properties of inclusions through appropriate special averaged indicator functions of the random structure of the composite. A numerical calculation of averaged indicator functions and effective elastic characteristics is performed by the generalized self-adjustment method for a unidirectional fiberglass on the basis of various models of actual random structures in the plane of isotropy.

Generalized self-consistent method for predicting the effective elastic properties of composites with random hybrid structures

NASA Astrophysics Data System (ADS)

Pan'kov, A. A.

1997-05-01

The feasibility of using a generalized self-consistent method for predicting the effective elastic properties of composites with random hybrid structures has been examined. Using this method, the problem is reduced to solution of simpler special averaged problems for composites with single inclusions and corresponding transition layers in the medium examined. The dimensions of the transition layers are defined by correlation radii of the composite random structure of the composite, while the heterogeneous elastic properties of the transition layers take account of the probabilities for variation of the size and configuration of the inclusions using averaged special indicator functions. Results are given for a numerical calculation of the averaged indicator functions and analysis of the effect of the micropores in the matrix-fiber interface region on the effective elastic properties of unidirectional fiberglass—epoxy using the generalized self-consistent method and compared with experimental data and reported solutions.

An Innovations-Based Noise Cancelling Technique on Inverse Kepstrum Whitening Filter and Adaptive FIR Filter in Beamforming Structure

PubMed Central

Jeong, Jinsoo

2011-01-01

This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure. PMID:22163987

Protein homology model refinement by large-scale energy optimization.

PubMed

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Towards solution and refinement of organic crystal structures by fitting to the atomic pair distribution function.

PubMed

Prill, Dragica; Juhás, Pavol; Billinge, Simon J L; Schmidt, Martin U

2016-01-01

A method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may be used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.

Automated method for relating regional pulmonary structure and function: integration of dynamic multislice CT and thin-slice high-resolution CT

NASA Astrophysics Data System (ADS)

Tajik, Jehangir K.; Kugelmass, Steven D.; Hoffman, Eric A.

1993-07-01

We have developed a method utilizing x-ray CT for relating pulmonary perfusion to global and regional anatomy, allowing for detailed study of structure to function relationships. A thick slice, high temporal resolution mode is used to follow a bolus contrast agent for blood flow evaluation and is fused with a high spatial resolution, thin slice mode to obtain structure- function detail. To aid analysis of blood flow, we have developed a software module, for our image analysis package (VIDA), to produce the combined structure-function image. Color coded images representing blood flow, mean transit time, regional tissue content, regional blood volume, regional air content, etc. are generated and imbedded in the high resolution volume image. A text file containing these values along with a voxel's 3-D coordinates is also generated. User input can be minimized to identifying the location of the pulmonary artery from which the input function to a blood flow model is derived. Any flow model utilizing one input and one output function can be easily added to a user selectable list. We present examples from our physiologic based research findings to demonstrate the strengths of combining dynamic CT and HRCT relative to other scanning modalities to uniquely characterize pulmonary normal and pathophysiology.

Algorithms for Efficient Computation of Transfer Functions for Large Order Flexible Systems

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Giesy, Daniel P.

1998-01-01

An efficient and robust computational scheme is given for the calculation of the frequency response function of a large order, flexible system implemented with a linear, time invariant control system. Advantage is taken of the highly structured sparsity of the system matrix of the plant based on a model of the structure using normal mode coordinates. The computational time per frequency point of the new computational scheme is a linear function of system size, a significant improvement over traditional, still-matrix techniques whose computational times per frequency point range from quadratic to cubic functions of system size. This permits the practical frequency domain analysis of systems of much larger order than by traditional, full-matrix techniques. Formulations are given for both open- and closed-loop systems. Numerical examples are presented showing the advantages of the present formulation over traditional approaches, both in speed and in accuracy. Using a model with 703 structural modes, the present method was up to two orders of magnitude faster than a traditional method. The present method generally showed good to excellent accuracy throughout the range of test frequencies, while traditional methods gave adequate accuracy for lower frequencies, but generally deteriorated in performance at higher frequencies with worst case errors being many orders of magnitude times the correct values.

Synthesis of hollow silica spheres with hierarchical shell structure by the dual action of liquid indium microbeads in vapor-liquid-solid growth.

PubMed

Wang, Jian-Tao; Wang, Hui; Ou, Xue-Mei; Lee, Chun-Sing; Zhang, Xiao-Hong

2011-07-05

Geometry-based adhesion arising from hierarchical surface structure enables microspheres to adhere to cells strongly, which is essential for inorganic microcapsules that function as drug delivery or diagnostic imaging agents. However, constructing a hierarchical structure on the outer shell of the products via the current microcapsule synthesis method is difficult. This work presents a novel approach to fabricating hollow microspheres with a hierarchical shell structure through the vapor-liquid-solid (VLS) process in which liquid indium droplets act as both templates for the formation of silica capsules and catalysts for the growth of hierarchical shell structure. This hierarchical shell structure offers the hollow microsphere an enhanced geometry-based adhesion. The results provide a facile method for fabricating hollow spheres and enriching their function through tailoring the geometry of their outer shells. © 2011 American Chemical Society

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

PubMed Central

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized. PMID:24688696

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Conformational sampling in template-free protein loop structure modeling: an overview.

PubMed

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

A new method to improve network topological similarity search: applied to fold recognition

PubMed Central

Lhota, John; Hauptman, Ruth; Hart, Thomas; Ng, Clara; Xie, Lei

2015-01-01

Motivation: Similarity search is the foundation of bioinformatics. It plays a key role in establishing structural, functional and evolutionary relationships between biological sequences. Although the power of the similarity search has increased steadily in recent years, a high percentage of sequences remain uncharacterized in the protein universe. Thus, new similarity search strategies are needed to efficiently and reliably infer the structure and function of new sequences. The existing paradigm for studying protein sequence, structure, function and evolution has been established based on the assumption that the protein universe is discrete and hierarchical. Cumulative evidence suggests that the protein universe is continuous. As a result, conventional sequence homology search methods may be not able to detect novel structural, functional and evolutionary relationships between proteins from weak and noisy sequence signals. To overcome the limitations in existing similarity search methods, we propose a new algorithmic framework—Enrichment of Network Topological Similarity (ENTS)—to improve the performance of large scale similarity searches in bioinformatics. Results: We apply ENTS to a challenging unsolved problem: protein fold recognition. Our rigorous benchmark studies demonstrate that ENTS considerably outperforms state-of-the-art methods. As the concept of ENTS can be applied to any similarity metric, it may provide a general framework for similarity search on any set of biological entities, given their representation as a network. Availability and implementation: Source code freely available upon request Contact: lxie@iscb.org PMID:25717198

Reusable glucose sensing using carbon nanotube-based self-assembly

NASA Astrophysics Data System (ADS)

Bhattacharyya, Tamoghna; Samaddar, Sarbani; Dasgupta, Anjan Kr.

2013-09-01

Lipid functionalized single walled carbon nanotube-based self assembly forms a super-micellar structure. This assemblage has been exploited to trap glucose oxidase in a molecular cargo for glucose sensing. The advantage of such a molecular trap is that all components of this unique structure (both the trapping shell and the entrapped enzyme) are reusable and rechargeable. The unique feature of this sensing method lies in the solid state functionalization of single walled carbon nanotubes that facilitates liquid state immobilization of the enzyme. The method can be used for soft-immobilization (a new paradigm in enzyme immobilization) of enzymes with better thermostability that is imparted by the strong hydrophobic environment provided through encapsulation by the nanotubes.Lipid functionalized single walled carbon nanotube-based self assembly forms a super-micellar structure. This assemblage has been exploited to trap glucose oxidase in a molecular cargo for glucose sensing. The advantage of such a molecular trap is that all components of this unique structure (both the trapping shell and the entrapped enzyme) are reusable and rechargeable. The unique feature of this sensing method lies in the solid state functionalization of single walled carbon nanotubes that facilitates liquid state immobilization of the enzyme. The method can be used for soft-immobilization (a new paradigm in enzyme immobilization) of enzymes with better thermostability that is imparted by the strong hydrophobic environment provided through encapsulation by the nanotubes. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr02609d

Consistent global structures of complex RNA states through multidimensional chemical mapping

PubMed Central

Cheng, Clarence Yu; Chou, Fang-Chieh; Kladwang, Wipapat; Tian, Siqi; Cordero, Pablo; Das, Rhiju

2015-01-01

Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis. Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions. We report that integrating a new method called MOHCA-seq (Multiplexed •OH Cleavage Analysis with paired-end sequencing) with mutate-and-map secondary structure inference guides Rosetta 3D modeling to consistent 1-nm accuracy for intricately folded ncRNAs with lengths up to 188 nucleotides, including a blind RNA-puzzle challenge, the lariat-capping ribozyme. This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon. MCM offers a sequencing-based route to uncovering ncRNA 3D structure, applicable to functionally important but potentially heterogeneous states. DOI: http://dx.doi.org/10.7554/eLife.07600.001 PMID:26035425

Structured Illumination Microscopy for the Investigation of Synaptic Structure and Function.

PubMed

Hong, Soyon; Wilton, Daniel K; Stevens, Beth; Richardson, Douglas S

2017-01-01

The neuronal synapse is a primary building block of the nervous system to which alterations in structure or function can result in numerous pathologies. Studying its formation and elimination is the key to understanding how brains are wired during development, maintained throughout adulthood plasticity, and disrupted during disease. However, due to its diffraction-limited size, investigations of the synaptic junction at the structural level have primarily relied on labor-intensive electron microscopy or ultra-thin section array tomography. Recent advances in the field of super-resolution light microscopy now allow researchers to image synapses and associated molecules with high-spatial resolution, while taking advantage of the key characteristics of light microscopy, such as easy sample preparation and the ability to detect multiple targets with molecular specificity. One such super-resolution technique, Structured Illumination Microscopy (SIM), has emerged as an attractive method to examine synapse structure and function. SIM requires little change in standard light microscopy sample preparation steps, but results in a twofold improvement in both lateral and axial resolutions compared to widefield microscopy. The following protocol outlines a method for imaging synaptic structures at resolutions capable of resolving the intricacies of these neuronal connections.

Understanding the General Packing Rearrangements Required for Successful Template Based Modeling of Protein Structure from a CASP Experiment

PubMed Central

Day, Ryan; Joo, Hyun; Chavan, Archana; Lennox, Kristin P.; Chen, Ann; Dahl, David B.; Vannucci, Marina; Tsai, Jerry W.

2012-01-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. PMID:23266765

Understanding the general packing rearrangements required for successful template based modeling of protein structure from a CASP experiment.

PubMed

Day, Ryan; Joo, Hyun; Chavan, Archana C; Lennox, Kristin P; Chen, Y Ann; Dahl, David B; Vannucci, Marina; Tsai, Jerry W

2013-02-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. Copyright © 2012 Elsevier Ltd. All rights reserved.

Approximate analytical solutions in the analysis of elastic structures of complex geometry

NASA Astrophysics Data System (ADS)

Goloskokov, Dmitriy P.; Matrosov, Alexander V.

2018-05-01

A method of analytical decomposition for analysis plane structures of a complex configuration is presented. For each part of the structure in the form of a rectangle all the components of the stress-strain state are constructed by the superposition method. The method is based on two solutions derived in the form of trigonometric series with unknown coefficients using the method of initial functions. The coefficients are determined from the system of linear algebraic equations obtained while satisfying the boundary conditions and the conditions for joining the structure parts. The components of the stress-strain state of a bent plate with holes are calculated using the analytical decomposition method.

Nanomanipulation of Single RNA Molecules by Optical Tweezers

PubMed Central

Stephenson, William; Wan, Gorby; Tenenbaum, Scott A.; Li, Pan T. X.

2014-01-01

A large portion of the human genome is transcribed but not translated. In this post genomic era, regulatory functions of RNA have been shown to be increasingly important. As RNA function often depends on its ability to adopt alternative structures, it is difficult to predict RNA three-dimensional structures directly from sequence. Single-molecule approaches show potentials to solve the problem of RNA structural polymorphism by monitoring molecular structures one molecule at a time. This work presents a method to precisely manipulate the folding and structure of single RNA molecules using optical tweezers. First, methods to synthesize molecules suitable for single-molecule mechanical work are described. Next, various calibration procedures to ensure the proper operations of the optical tweezers are discussed. Next, various experiments are explained. To demonstrate the utility of the technique, results of mechanically unfolding RNA hairpins and a single RNA kissing complex are used as evidence. In these examples, the nanomanipulation technique was used to study folding of each structural domain, including secondary and tertiary, independently. Lastly, the limitations and future applications of the method are discussed. PMID:25177917

Biomimetic cellular metals-using hierarchical structuring for energy absorption.

PubMed

Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

2016-07-19

Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form-structure-function relationship of the biological concept generators as well as the bio-inspired metal foams was achieved, on deeper hierarchical levels and overarching different levels.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Frequency response function (FRF) based updating of a laser spot welded structure

NASA Astrophysics Data System (ADS)

Zin, M. S. Mohd; Rani, M. N. Abdul; Yunus, M. A.; Sani, M. S. M.; Wan Iskandar Mirza, W. I. I.; Mat Isa, A. A.

2018-04-01

The objective of this paper is to present frequency response function (FRF) based updating as a method for matching the finite element (FE) model of a laser spot welded structure with a physical test structure. The FE model of the welded structure was developed using CQUAD4 and CWELD element connectors, and NASTRAN was used to calculate the natural frequencies, mode shapes and FRF. Minimization of the discrepancies between the finite element and experimental FRFs was carried out using the exceptional numerical capability of NASTRAN Sol 200. The experimental work was performed under free-free boundary conditions using LMS SCADAS. Avast improvement in the finite element FRF was achieved using the frequency response function (FRF) based updating with two different objective functions proposed.

ModeRNA: a tool for comparative modeling of RNA 3D structure

PubMed Central

Rother, Magdalena; Rother, Kristian; Puton, Tomasz; Bujnicki, Janusz M.

2011-01-01

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available. PMID:21300639

PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

PubMed

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

2014-01-01

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

Recent developments in structural proteomics for protein structure determination.

PubMed

Liu, Hsuan-Liang; Hsu, Jyh-Ping

2005-05-01

The major challenges in structural proteomics include identifying all the proteins on the genome-wide scale, determining their structure-function relationships, and outlining the precise three-dimensional structures of the proteins. Protein structures are typically determined by experimental approaches such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. However, the knowledge of three-dimensional space by these techniques is still limited. Thus, computational methods such as comparative and de novo approaches and molecular dynamic simulations are intensively used as alternative tools to predict the three-dimensional structures and dynamic behavior of proteins. This review summarizes recent developments in structural proteomics for protein structure determination; including instrumental methods such as X-ray crystallography and NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulations.

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

Harnessing glycomics technologies: integrating structure with function for glycan characterization

PubMed Central

Robinson, Luke N.; Artpradit, Charlermchai; Raman, Rahul; Shriver, Zachary H.; Ruchirawat, Mathuros; Sasisekharan, Ram

2013-01-01

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecules which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships. PMID:22522536

An improved design method for EPC middleware

NASA Astrophysics Data System (ADS)

Lou, Guohuan; Xu, Ran; Yang, Chunming

2014-04-01

For currently existed problems and difficulties during the small and medium enterprises use EPC (Electronic Product Code) ALE (Application Level Events) specification to achieved middleware, based on the analysis of principle of EPC Middleware, an improved design method for EPC middleware is presented. This method combines the powerful function of MySQL database, uses database to connect reader-writer with upper application system, instead of development of ALE application program interface to achieve a middleware with general function. This structure is simple and easy to implement and maintain. Under this structure, different types of reader-writers added can be configured conveniently and the expandability of the system is improved.

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Impact of graphene-based nanomaterials (GBNMs) on the structural and functional conformations of hepcidin peptide

NASA Astrophysics Data System (ADS)

Singh, Krishna P.; Baweja, Lokesh; Wolkenhauer, Olaf; Rahman, Qamar; Gupta, Shailendra K.

2018-03-01

Graphene-based nanomaterials (GBNMs) are widely used in various industrial and biomedical applications. GBNMs of different compositions, size and shapes are being introduced without thorough toxicity evaluation due to the unavailability of regulatory guidelines. Computational toxicity prediction methods are used by regulatory bodies to quickly assess health hazards caused by newer materials. Due to increasing demand of GBNMs in various size and functional groups in industrial and consumer based applications, rapid and reliable computational toxicity assessment methods are urgently needed. In the present work, we investigate the impact of graphene and graphene oxide nanomaterials on the structural conformations of small hepcidin peptide and compare the materials for their structural and conformational changes. Our molecular dynamics simulation studies revealed conformational changes in hepcidin due to its interaction with GBMNs, which results in a loss of its functional properties. Our results indicate that hepcidin peptide undergo severe structural deformations when superimposed on the graphene sheet in comparison to graphene oxide sheet. These observations suggest that graphene is more toxic than a graphene oxide nanosheet of similar area. Overall, this study indicates that computational methods based on structural deformation, using molecular dynamics (MD) simulations, can be used for the early evaluation of toxicity potential of novel nanomaterials.

Biofouling-resistant ceragenin-modified materials and structures for water treatment

DOEpatents

Hibbs, Michael; Altman, Susan J.; Jones, Howland D. T.; Savage, Paul B.

2013-09-10

This invention relates to methods for chemically grafting and attaching ceragenin molecules to polymer substrates; methods for synthesizing ceragenin-containing copolymers; methods for making ceragenin-modified water treatment membranes and spacers; and methods of treating contaminated water using ceragenin-modified treatment membranes and spacers. Ceragenins are synthetically produced antimicrobial peptide mimics that display broad-spectrum bactericidal activity. Alkene-functionalized ceragenins (e.g., acrylamide-functionalized ceragenins) can be attached to polyamide reverse osmosis membranes using amine-linking, amide-linking, UV-grafting, or silane-coating methods. In addition, silane-functionalized ceragenins can be directly attached to polymer surfaces that have free hydroxyls.

Benchmarking Density Functional Theory Based Methods To Model NiOOH Material Properties: Hubbard and van der Waals Corrections vs Hybrid Functionals.

PubMed

Zaffran, Jeremie; Caspary Toroker, Maytal

2016-08-09

NiOOH has recently been used to catalyze water oxidation by way of electrochemical water splitting. Few experimental data are available to rationalize the successful catalytic capability of NiOOH. Thus, theory has a distinctive role for studying its properties. However, the unique layered structure of NiOOH is associated with the presence of essential dispersion forces within the lattice. Hence, the choice of an appropriate exchange-correlation functional within Density Functional Theory (DFT) is not straightforward. In this work, we will show that standard DFT is sufficient to evaluate the geometry, but DFT+U and hybrid functionals are required to calculate the oxidation states. Notably, the benefit of DFT with van der Waals correction is marginal. Furthermore, only hybrid functionals succeed in opening a bandgap, and such methods are necessary to study NiOOH electronic structure. In this work, we expect to give guidelines to theoreticians dealing with this material and to present a rational approach in the choice of the DFT method of calculation.

Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules

PubMed Central

Park, Hahnbeom; Bradley, Philip; Greisen, Per; Liu, Yuan; Mulligan, Vikram Khipple; Kim, David E.; Baker, David; DiMaio, Frank

2017-01-01

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking, have been parameterized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties. PMID:27766851

Atomistic full-quantum transport model for zigzag graphene nanoribbon-based structures: Complex energy-band method

NASA Astrophysics Data System (ADS)

Chen, Chun-Nan; Luo, Win-Jet; Shyu, Feng-Lin; Chung, Hsien-Ching; Lin, Chiun-Yan; Wu, Jhao-Ying

2018-01-01

Using a non-equilibrium Green’s function framework in combination with the complex energy-band method, an atomistic full-quantum model for solving quantum transport problems for a zigzag-edge graphene nanoribbon (zGNR) structure is proposed. For transport calculations, the mathematical expressions from the theory for zGNR-based device structures are derived in detail. The transport properties of zGNR-based devices are calculated and studied in detail using the proposed method.

SA-Mot: a web server for the identification of motifs of interest extracted from protein loops

PubMed Central

Regad, Leslie; Saladin, Adrien; Maupetit, Julien; Geneix, Colette; Camproux, Anne-Claude

2011-01-01

The detection of functional motifs is an important step for the determination of protein functions. We present here a new web server SA-Mot (Structural Alphabet Motif) for the extraction and location of structural motifs of interest from protein loops. Contrary to other methods, SA-Mot does not focus only on functional motifs, but it extracts recurrent and conserved structural motifs involved in structural redundancy of loops. SA-Mot uses the structural word notion to extract all structural motifs from uni-dimensional sequences corresponding to loop structures. Then, SA-Mot provides a description of these structural motifs using statistics computed in the loop data set and in SCOP superfamily, sequence and structural parameters. SA-Mot results correspond to an interactive table listing all structural motifs extracted from a target structure and their associated descriptors. Using this information, the users can easily locate loop regions that are important for the protein folding and function. The SA-Mot web server is available at http://sa-mot.mti.univ-paris-diderot.fr. PMID:21665924

SA-Mot: a web server for the identification of motifs of interest extracted from protein loops.

PubMed

Regad, Leslie; Saladin, Adrien; Maupetit, Julien; Geneix, Colette; Camproux, Anne-Claude

2011-07-01

The detection of functional motifs is an important step for the determination of protein functions. We present here a new web server SA-Mot (Structural Alphabet Motif) for the extraction and location of structural motifs of interest from protein loops. Contrary to other methods, SA-Mot does not focus only on functional motifs, but it extracts recurrent and conserved structural motifs involved in structural redundancy of loops. SA-Mot uses the structural word notion to extract all structural motifs from uni-dimensional sequences corresponding to loop structures. Then, SA-Mot provides a description of these structural motifs using statistics computed in the loop data set and in SCOP superfamily, sequence and structural parameters. SA-Mot results correspond to an interactive table listing all structural motifs extracted from a target structure and their associated descriptors. Using this information, the users can easily locate loop regions that are important for the protein folding and function. The SA-Mot web server is available at http://sa-mot.mti.univ-paris-diderot.fr.

Functional MRI registration with tissue-specific patch-based functional correlation tensors.

PubMed

Zhou, Yujia; Zhang, Han; Zhang, Lichi; Cao, Xiaohuan; Yang, Ru; Feng, Qianjin; Yap, Pew-Thian; Shen, Dinggang

2018-06-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods. © 2018 Wiley Periodicals, Inc.

Enhancing biological relevance of a weighted gene co-expression network for functional module identification.

PubMed

Prom-On, Santitham; Chanthaphan, Atthawut; Chan, Jonathan Hoyin; Meechai, Asawin

2011-02-01

Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

Improving predicted protein loop structure ranking using a Pareto-optimality consensus method.

PubMed

Li, Yaohang; Rata, Ionel; Chiu, See-wing; Jakobsson, Eric

2010-07-20

Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction. We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of approximately 20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD < 0.5A from the native) as top-ranked, and selecting at least one near-native model in the top-5-ranked models, respectively. Similar effectiveness of the POC method is also found in the decoy sets from membrane protein loops. Furthermore, the POC method outperforms the other popularly-used consensus strategies in model ranking, such as rank-by-number, rank-by-rank, rank-by-vote, and regression-based methods. By integrating multiple knowledge- and physics-based scoring functions based on Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set.

Improving predicted protein loop structure ranking using a Pareto-optimality consensus method

PubMed Central

2010-01-01

Background Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction. Results We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of ~20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD < 0.5A from the native) as top-ranked, and selecting at least one near-native model in the top-5-ranked models, respectively. Similar effectiveness of the POC method is also found in the decoy sets from membrane protein loops. Furthermore, the POC method outperforms the other popularly-used consensus strategies in model ranking, such as rank-by-number, rank-by-rank, rank-by-vote, and regression-based methods. Conclusions By integrating multiple knowledge- and physics-based scoring functions based on Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set. PMID:20642859

Environmental drivers of heterogeneity in the trophic-functional structure of protozoan communities during an annual cycle in a coastal ecosystem.

PubMed

Xu, Guangjian; Yang, Eun Jin; Xu, Henglong

2017-08-15

Trophic-functional groupings are an important biological trait to summarize community structure in functional space. The heterogeneity of the tropic-functional pattern of protozoan communities and its environmental drivers were studied in coastal waters of the Yellow Sea during a 1-year cycle. Samples were collected using the glass slide method at four stations within a water pollution gradient. A second-stage matrix-based analysis was used to summarize spatial variation in the annual pattern of the functional structure. A clustering analysis revealed significant variability in the trophic-functional pattern among the four stations during the 1-year cycle. The heterogeneity in the trophic-functional pattern of the communities was significantly related to changes in environmental variables, particularly ammonium-nitrogen and nitrates, alone or in combination with dissolved oxygen. These results suggest that the heterogeneity in annual patterns of protozoan trophic-functional structure may reflect water quality status in coastal ecosystems. Copyright © 2017. Published by Elsevier Ltd.

Multiscale study of metal nanoparticles

NASA Astrophysics Data System (ADS)

Lee, Byeongchan

Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum nanoparticles in the range of 2.4 nm to 3.1 nm: energetically favorable structures have been determined in terms of semi-continuum binding energy, and the reactivity of the selected nanoparticle has been investigated based on local density of states from first principles calculations. The calculation suggests that the reactivity landscape of particles is more complex than the simple reactivity of clean surfaces, and the reactivity towards a particular reactant can be predicted for a given structure.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase.

PubMed

Zemla, Adam T; Lang, Dorothy M; Kostova, Tanya; Andino, Raul; Ecale Zhou, Carol L

2011-06-02

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV (structure-alignment sequence variability), a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus, and we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Two-photon reduction: a cost-effective method for fabrication of functional metallic nanostructures

NASA Astrophysics Data System (ADS)

Tabrizi, Sahar; Cao, YaoYu; Lin, Han; Jia, BaoHua

2017-03-01

Metallic nanostructures have underpinned plasmonic-based advanced photonic devices in a broad range of research fields over the last decade including physics, engineering, material science and bioscience. The key to realizing functional plasmonic resonances that can manipulate light at the optical frequencies relies on the creation of conductive metallic structures at the nanoscale with low structural defects. Currently, most plasmonic nanostructures are fabricated either by electron beam lithography (EBL) or by focused ion beam (FIB) milling, which are expensive, complicated and time-consuming. In comparison, the direct laser writing (DLW) technique has demonstrated its high spatial resolution and cost-effectiveness in three-dimensional fabrication of micro/nanostructures. Furthermore, the recent breakthroughs in superresolution nanofabrication and parallel writing have significantly advanced the fabrication resolution and throughput of the DLW method and made it one of the promising future nanofabrication technologies with low-cost and scalability. In this review, we provide a comprehensive summary of the state-of-the-art DLW fabrication technology for nanometer scale metallic structures. The fabrication mechanisms, different material choices, fabrication capability, including resolution, conductivity and structure surface smoothness, as well as the characterization methods and achievable devices for different applications are presented. In particular, the development trends of the field and the perspectives for future opportunities and challenges are provided at the end of the review. It has been demonstrated that the quality of the metallic structures fabricated using the DLW method is excellent compared with other methods providing a new and enabling platform for functional nanophotonic device fabrication.

Computational methods for prediction of RNA interactions with metal ions and small organic ligands.

PubMed

Philips, Anna; Łach, Grzegorz; Bujnicki, Janusz M

2015-01-01

In the recent years, it has become clear that a wide range of regulatory functions in bacteria are performed by riboswitches--regions of mRNA that change their structure upon external stimuli. Riboswitches are therefore attractive targets for drug design, molecular engineering, and fundamental research on regulatory circuitry of living cells. Several mechanisms are known for riboswitches controlling gene expression, but most of them perform their roles by ligand binding. As with other macromolecules, knowledge of the 3D structure of riboswitches is crucial for the understanding of their function. The development of experimental methods allowed for investigation of RNA structure and its complexes with ligands (which are either riboswitches' substrates or inhibitors) and metal cations (which stabilize the structure and are also known to be riboswitches' inhibitors). The experimental probing of different states of riboswitches is however time consuming, costly, and difficult to resolve without theoretical support. The natural consequence is the use of computational methods at least for initial research, such as the prediction of putative binding sites of ligands or metal ions. Here, we present a review on such methods, with a special focus on knowledge-based methods developed in our laboratory: LigandRNA--a scoring function for the prediction of RNA-small molecule interactions and MetalionRNA--a predictor of metal ions-binding sites in RNA structures. Both programs are available free of charge as a Web servers, LigandRNA at http://ligandrna.genesilico.pl and MetalionRNA at http://metalionrna.genesilico.pl/. © 2015 Elsevier Inc. All rights reserved.

Protein structure based prediction of catalytic residues.

PubMed

Fajardo, J Eduardo; Fiser, Andras

2013-02-22

Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

Structural Analysis of PTM Hotspots (SAPH-ire) – A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families*

PubMed Central

Dewhurst, Henry M.; Choudhury, Shilpa; Torres, Matthew P.

2015-01-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. PMID:26070665

Modeling vibration response and damping of cables and cabled structures

NASA Astrophysics Data System (ADS)

Spak, Kaitlin S.; Agnes, Gregory S.; Inman, Daniel J.

2015-02-01

In an effort to model the vibration response of cabled structures, the distributed transfer function method is developed to model cables and a simple cabled structure. The model includes shear effects, tension, and hysteretic damping for modeling of helical stranded cables, and includes a method for modeling cable attachment points using both linear and rotational damping and stiffness. The damped cable model shows agreement with experimental data for four types of stranded cables, and the damped cabled beam model shows agreement with experimental data for the cables attached to a beam structure, as well as improvement over the distributed mass method for cabled structure modeling.

MSTor version 2013: A new version of the computer code for the multi-structural torsional anharmonicity, now with a coupled torsional potential

NASA Astrophysics Data System (ADS)

Zheng, Jingjing; Meana-Pañeda, Rubén; Truhlar, Donald G.

2013-08-01

We present an improved version of the MSTor program package, which calculates partition functions and thermodynamic functions of complex molecules involving multiple torsions; the method is based on either a coupled torsional potential or an uncoupled torsional potential. The program can also carry out calculations in the multiple-structure local harmonic approximation. The program package also includes seven utility codes that can be used as stand-alone programs to calculate reduced moment of inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes for torsional subdomains defined by Voronoi tessellation of the conformational subspace, to generate template input files for the MSTor calculation and Voronoi calculation, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Restrictions: There is no limit on the number of torsions that can be included in either the Voronoi calculation or the full MS-T calculation. In practice, the range of problems that can be addressed with the present method consists of all multitorsional problems for which one can afford to calculate all the conformational structures and their frequencies. Unusual features: The method can be applied to transition states as well as stable molecules. The program package also includes the hull program for the calculation of Voronoi volumes, the symmetry program for determining point group symmetry of a molecule, and seven utility codes that can be used as stand-alone programs to calculate reduced moment-of-inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes of the torsional subdomains defined by Voronoi tessellation of the conformational subspace, to generate template input files, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Additional comments: The program package includes a manual, installation script, and input and output files for a test suite. Running time: There are 26 test runs. The running time of the test runs on a single processor of the Itasca computer is less than 2 s. References: [1] MS-T(C) method: Quantum Thermochemistry: Multi-Structural Method with Torsional Anharmonicity Based on a Coupled Torsional Potential, J. Zheng and D.G. Truhlar, Journal of Chemical Theory and Computation 9 (2013) 1356-1367, DOI: http://dx.doi.org/10.1021/ct3010722. [2] MS-T(U) method: Practical Methods for Including Torsional Anharmonicity in Thermochemical Calculations of Complex Molecules: The Internal-Coordinate Multi-Structural Approximation, J. Zheng, T. Yu, E. Papajak, I, M. Alecu, S.L. Mielke, and D.G. Truhlar, Physical Chemistry Chemical Physics 13 (2011) 10885-10907.

CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences.

PubMed

Dawson, Natalie L; Sillitoe, Ian; Lees, Jonathan G; Lam, Su Datt; Orengo, Christine A

2017-01-01

This chapter describes the generation of the data in the CATH-Gene3D online resource and how it can be used to study protein domains and their evolutionary relationships. Methods will be presented for: comparing protein structures, recognizing homologs, predicting domain structures within protein sequences, and subclassifying superfamilies into functionally pure families, together with a guide on using the webpages.

Using polarized Raman spectroscopy and the pseudospectral method to characterize molecular structure and function

NASA Astrophysics Data System (ADS)

Weisman, Andrew L.

Electronic structure calculation is an essential approach for determining the structure and function of molecules and is therefore of critical interest to physics, chemistry, and materials science. Of the various algorithms for calculating electronic structure, the pseudospectral method is among the fastest. However, the trade-off for its speed is more up-front programming and testing, and as a result, applications using the pseudospectral method currently lag behind those using other methods. In Part I of this dissertation, we first advance the pseudospectral method by optimizing it for an important application, polarized Raman spectroscopy, which is a well-established tool used to characterize molecular properties. This is an application of particular importance because often the easiest and most economical way to obtain the polarized Raman spectrum of a material is to simulate it; thus, utilization of the pseudospectral method for this purpose will accelerate progress in the determination of molecular properties. We demonstrate that our implementation of Raman spectroscopy using the pseudospectral method results in spectra that are just as accurate as those calculated using the traditional analytic method, and in the process, we derive the most comprehensive formulation to date of polarized Raman intensity formulas, applicable to both crystalline and isotropic systems. Next, we apply our implementation to determine the orientations of crystalline oligothiophenes -- a class of materials important in the field of organic electronics -- achieving excellent agreement with experiment and demonstrating the general utility of polarized Raman spectroscopy for the determination of crystal orientation. In addition, we derive from first-principles a method for using polarized Raman spectra to establish unambiguously whether a uniform region of a material is crystalline or isotropic. Finally, we introduce free, open-source software that allows a user to determine any of a number of polarized Raman properties of a sample given common output from electronic structure calculations. In Part II, we apply the pseudospectral method to other areas of scientific importance requiring a deeper understanding of molecular structure and function. First, we use it to accurately determine the frequencies of vibrational tags on biomolecules that can be detected in real-time using stimulated Raman spectroscopy. Next, we evaluate the performance of the pseudospectral method for calculating excited-state energies and energy gradients of large molecules -- another new application of the pseudospectral method -- showing that the calculations run much more quickly than those using the analytic method. Finally, we use the pseudospectral method to simulate the bottleneck process of a solar cell used for water splitting, a promising technology for converting the sun's energy into hydrogen fuel. We apply the speed of the pseudospectral method by modeling the relevant part of the system as a large, explicitly passivated titanium dioxide nanoparticle and simulating it realistically using hybrid density functional theory with an implicit solvent model, yielding insight into the physical nature of the rate-limiting step of water splitting. These results further validate the particularly fast and accurate simulation methodologies used, opening the door to efficient and realistic cluster-based, fully quantum-mechanical simulations of the bottleneck process of a promising technology for clean solar energy conversion. Taken together, we show how both polarized Raman spectroscopy and the pseudospectral method are effective tools for analyzing the structure and function of important molecular systems.

Flow measuring structures

NASA Astrophysics Data System (ADS)

Boiten, W.

1993-11-01

The use of flow measuring structures is one of the various methods for the continuous measurement of discharges in open channels. In this report a brief summary of these methods is presented to get some insight in the selection of the most appropriate method. Then the distinct functions of water control structures are described. The flow measuring structures are classified according to international rules. The fields of application are dealt with and the definitions of weir flow are given. Much attention is paid to the aspects of how to select the most suitable flow measuring structure. The accuracy in the evaluation of the discharge has been related to the different error sources. A review of international standards on flow measuring structures concludes the report.

The Prediction of Botulinum Toxin Structure Based on in Silico and in Vitro Analysis

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2011-01-01

Many of biological system mediated through protein-protein interactions. Knowledge of protein-protein complex structure is required for understanding the function. The determination of huge size and flexible protein-protein complex structure by experimental studies remains difficult, costly and five-consuming, therefore computational prediction of protein structures by homolog modeling and docking studies is valuable method. In addition, MD simulation is also one of the most powerful methods allowing to see the real dynamics of proteins. Here, we predict protein-protein complex structure of botulinum toxin to analyze its property. These bioinformatics methods are useful to report the relation between the flexibility of backbone structure and the activity.

PHOENIX: a scoring function for affinity prediction derived using high-resolution crystal structures and calorimetry measurements.

PubMed

Tang, Yat T; Marshall, Garland R

2011-02-28

Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.

Transparent wood for functional and structural applications

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Fu, Qiliang; Yang, Xuan; Berglund, Lars

2017-12-01

Optically transparent wood combines mechanical performance with optical functionalities is an emerging candidate for applications in smart buildings and structural optics and photonics. The present review summarizes transparent wood preparation methods, optical and mechanical performance, and functionalization routes, and discusses potential applications. The various challenges are discussed for the purpose of improved performance, scaled-up production and realization of advanced applications. This article is part of a discussion meeting issue `New horizons for cellulose nanotechnology'.

Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

PubMed

Stein, Helge Sören; Jiao, Sally; Ludwig, Alfred

2017-01-09

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.

Looking at the Disordered Proteins through the Computational Microscope.

PubMed

Das, Payel; Matysiak, Silvina; Mittal, Jeetain

2018-05-23

Intrinsically disordered proteins (IDPs) have attracted wide interest over the past decade due to their surprising prevalence in the proteome and versatile roles in cell physiology and pathology. A large selection of IDPs has been identified as potential targets for therapeutic intervention. Characterizing the structure-function relationship of disordered proteins is therefore an essential but daunting task, as these proteins can adapt transient structure, necessitating a new paradigm for connecting structural disorder to function. Molecular simulation has emerged as a natural complement to experiments for atomic-level characterizations and mechanistic investigations of this intriguing class of proteins. The diverse range of length and time scales involved in IDP function requires performing simulations at multiple levels of resolution. In this Outlook, we focus on summarizing available simulation methods, along with a few interesting example applications. We also provide an outlook on how these simulation methods can be further improved in order to provide a more accurate description of IDP structure, binding, and assembly.

An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes

NASA Astrophysics Data System (ADS)

Li, Huilin; Nguyen, Hong Hanh; Ogorzalek Loo, Rachel R.; Campuzano, Iain D. G.; Loo, Joseph A.

2018-02-01

Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8 MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation.

Insights into Photosystem II from Isomorphous Difference Fourier Maps of Femtosecond X-ray Diffraction Data and Quantum Mechanics/Molecular Mechanics Structural Models.

PubMed

Wang, Jimin; Askerka, Mikhail; Brudvig, Gary W; Batista, Victor S

2017-02-10

Understanding structure-function relations in photosystem II (PSII) is important for the development of biomimetic photocatalytic systems. X-ray crystallography, computational modeling, and spectroscopy have played central roles in elucidating the structure and function of PSII. Recent breakthroughs in femtosecond X-ray crystallography offer the possibility of collecting diffraction data from the X-ray free electron laser (XFEL) before radiation damage of the sample, thereby overcoming the main challenge of conventional X-ray diffraction methods. However, the interpretation of XFEL data from PSII intermediates is challenging because of the issues regarding data-processing, uncertainty on the precise positions of light oxygen atoms next to heavy metal centers, and different kinetics of the S-state transition in microcrystals compared to solution. Here, we summarize recent advances and outstanding challenges in PSII structure-function determination with emphasis on the implementation of quantum mechanics/molecular mechanics techniques combined with isomorphous difference Fourier maps, direct methods, and high-resolution spectroscopy.

[Effect of pineal gland peptides on morphofunctional structure of the pancreas in ageing].

PubMed

Ryzhak, A P; Kostiuchek, I N; Kvetnoĭ, I M

2007-01-01

A study of pineal gland peptides effect on morphology and functions of the pancreas in the model of premature ageing in rats was performed with respect to the need in methods for premature ageing prevention. Structural, morphological and functional alterations in pancreas tissue, suggesting premature ageing of the gland, were identified by methods of immunohistochemistry and electronic microscopy. There was registered a geroprotective effect of the pineal gland peptides on pancreas tissue, manifested in the resistance of the latter to the impact of stress factors entailing premature ageing.

Pair potentials for liquid sodium near freezing from electron theory and from inversion of the measured structure factor

NASA Astrophysics Data System (ADS)

Perrot, F.; March, N. H.

An effective pair potential for liquid sodium near freezing has been calculated from electron theory using the density-functional method. The main features of the potential extracted by Reatto, Levesque, and Weis [phys. Rev. A 33, 3451 (1986)] by inverting the measured structure factor of Greenfield, Wellendorf, and Wiser [Phys. Rev. A 4, 1607 (1971)] are faithfully reflected by electron theory. To obtain precise agreement between the two methods will evidently require further progress in setting up nonlocal exchange and correlation functionals.

Free energy minimization to predict RNA secondary structures and computational RNA design.

PubMed

Churkin, Alexander; Weinbrand, Lina; Barash, Danny

2015-01-01

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Posttraumatic Stress Disorder Symptom Structure in Injured Children: Functional Impairment and Depression Symptoms in a Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Kassam-Adams, Nancy; Marsac, Meghan L.; Cirilli, Carla

2010-01-01

Objective: To examine the factor structure of posttraumatic stress disorder (PTSD) symptoms in children and adolescents who have experienced an acute single-incident trauma, associations between PTSD symptom clusters and functional impairment, and the specificity of PTSD symptoms in relation to depression and general distress. Method: Examined…

Regulation of T-cell receptor signalling by membrane microdomains

PubMed Central

Razzaq, Tahir M; Ozegbe, Patricia; Jury, Elizabeth C; Sembi, Phupinder; Blackwell, Nathan M; Kabouridis, Panagiotis S

2004-01-01

There is now considerable evidence suggesting that the plasma membrane of mammalian cells is compartmentalized by functional lipid raft microdomains. These structures are assemblies of specialized lipids and proteins and have been implicated in diverse biological functions. Analysis of their protein content using proteomics and other methods revealed enrichment of signalling proteins, suggesting a role for these domains in intracellular signalling. In T lymphocytes, structure/function experiments and complementary pharmacological studies have shown that raft microdomains control the localization and function of proteins which are components of signalling pathways regulated by the T-cell antigen receptor (TCR). Based on these studies, a model for TCR phosphorylation in lipid rafts is presented. However, despite substantial progress in the field, critical questions remain. For example, it is unclear if membrane rafts represent a homogeneous population and if their structure is modified upon TCR stimulation. In the future, proteomics and the parallel development of complementary analytical methods will undoubtedly contribute in further delineating the role of lipid rafts in signal transduction mechanisms. PMID:15554919

Structure and function of complex brain networks

PubMed Central

Sporns, Olaf

2013-01-01

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a “rich club,” centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed. PMID:24174898

Structural optimization: Status and promise

NASA Astrophysics Data System (ADS)

Kamat, Manohar P.

Chapters contained in this book include fundamental concepts of optimum design, mathematical programming methods for constrained optimization, function approximations, approximate reanalysis methods, dual mathematical programming methods for constrained optimization, a generalized optimality criteria method, and a tutorial and survey of multicriteria optimization in engineering. Also included are chapters on the compromise decision support problem and the adaptive linear programming algorithm, sensitivity analyses of discrete and distributed systems, the design sensitivity analysis of nonlinear structures, optimization by decomposition, mixed elements in shape sensitivity analysis of structures based on local criteria, and optimization of stiffened cylindrical shells subjected to destabilizing loads. Other chapters are on applications to fixed-wing aircraft and spacecraft, integrated optimum structural and control design, modeling concurrency in the design of composite structures, and tools for structural optimization. (No individual items are abstracted in this volume)

A structural-alphabet-based strategy for finding structural motifs across protein families

PubMed Central

Wu, Chih Yuan; Chen, Yao Chi; Lim, Carmay

2010-01-01

Proteins with insignificant sequence and overall structure similarity may still share locally conserved contiguous structural segments; i.e. structural/3D motifs. Most methods for finding 3D motifs require a known motif to search for other similar structures or functionally/structurally crucial residues. Here, without requiring a query motif or essential residues, a fully automated method for discovering 3D motifs of various sizes across protein families with different folds based on a 16-letter structural alphabet is presented. It was applied to structurally non-redundant proteins bound to DNA, RNA, obligate/non-obligate proteins as well as free DNA-binding proteins (DBPs) and proteins with known structures but unknown function. Its usefulness was illustrated by analyzing the 3D motifs found in DBPs. A non-specific motif was found with a ‘corner’ architecture that confers a stable scaffold and enables diverse interactions, making it suitable for binding not only DNA but also RNA and proteins. Furthermore, DNA-specific motifs present ‘only’ in DBPs were discovered. The motifs found can provide useful guidelines in detecting binding sites and computational protein redesign. PMID:20525797

Local and average structure of Mn- and La-substituted BiFeO{sub 3}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Bo; Selbach, Sverre M., E-mail: selbach@ntnu.no

2017-06-15

The local and average structure of solid solutions of the multiferroic perovskite BiFeO{sub 3} is investigated by synchrotron X-ray diffraction (XRD) and electron density functional theory (DFT) calculations. The average experimental structure is determined by Rietveld refinement and the local structure by total scattering data analyzed in real space with the pair distribution function (PDF) method. With equal concentrations of La on the Bi site or Mn on the Fe site, La causes larger structural distortions than Mn. Structural models based on DFT relaxed geometry give an improved fit to experimental PDFs compared to models constrained by the space groupmore » symmetry. Berry phase calculations predict a higher ferroelectric polarization than the experimental literature values, reflecting that structural disorder is not captured in either average structure space group models or DFT calculations with artificial long range order imposed by periodic boundary conditions. Only by including point defects in a supercell, here Bi vacancies, can DFT calculations reproduce the literature results on the structure and ferroelectric polarization of Mn-substituted BiFeO{sub 3}. The combination of local and average structure sensitive experimental methods with DFT calculations is useful for illuminating the structure-property-composition relationships in complex functional oxides with local structural distortions. - Graphical abstract: The experimental and simulated partial pair distribution functions (PDF) for BiFeO{sub 3}, BiFe{sub 0.875}Mn{sub 0.125}O{sub 3}, BiFe{sub 0.75}Mn{sub 0.25}O{sub 3} and Bi{sub 0.9}La{sub 0.1}FeO{sub 3}.« less

Electronic structure and electric polarity of edge-functionalized graphene nanoribbons

NASA Astrophysics Data System (ADS)

Taira, Remi; Yamanaka, Ayaka; Okada, Susumu

2017-08-01

On the basis of the density functional theory combined with the effective screening medium method, we studied the electronic structure of graphene nanoribbons with zigzag edges, which are terminated by functional groups. The work function of the nanoribbons is sensitive to the functional groups. The edge state inherent in the zigzag edges is robust against edge functionalization. OH termination causes the injection of electrons into the nearly free electron states situated alongside the nanoribbons, resulting in the formation of free electron channels outside the nanoribbons. We also demonstrated that the polarity of zigzag graphene nanoribbons is controllable by the asymmetrical functionalization of their edges.

Refinement of protein termini in template-based modeling using conformational space annealing.

PubMed

Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

2011-09-01

The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

PubMed

Zhang, Xianchang; Cheng, Hewei; Zuo, Zhentao; Zhou, Ke; Cong, Fei; Wang, Bo; Zhuo, Yan; Chen, Lin; Xue, Rong; Fan, Yong

2018-01-01

The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo . In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

Elastic wave field computation in multilayered nonplanar solid structures: a mesh-free semianalytical approach.

PubMed

Banerjee, Sourav; Kundu, Tribikram

2008-03-01

Multilayered solid structures made of isotropic, transversely isotropic, or general anisotropic materials are frequently used in aerospace, mechanical, and civil structures. Ultrasonic fields developed in such structures by finite size transducers simulating actual experiments in laboratories or in the field have not been rigorously studied. Several attempts to compute the ultrasonic field inside solid media have been made based on approximate paraxial methods like the classical ray tracing and multi-Gaussian beam models. These approximate methods have several limitations. A new semianalytical method is adopted in this article to model elastic wave field in multilayered solid structures with planar or nonplanar interfaces generated by finite size transducers. A general formulation good for both isotropic and anisotropic solids is presented in this article. A variety of conditions have been incorporated in the formulation including irregularities at the interfaces. The method presented here requires frequency domain displacement and stress Green's functions. Due to the presence of different materials in the problem geometry various elastodynamic Green's functions for different materials are used in the formulation. Expressions of displacement and stress Green's functions for isotropic and anisotropic solids as well as for the fluid media are presented. Computed results are verified by checking the stress and displacement continuity conditions across the interface of two different solids of a bimetal plate and investigating if the results for a corrugated plate with very small corrugation match with the flat plate results.

Structural predictions for Correlated Electron Materials Using the Functional Dynamical Mean Field Theory Approach

NASA Astrophysics Data System (ADS)

Haule, Kristjan

2018-04-01

The Dynamical Mean Field Theory (DMFT) in combination with the band structure methods has been able to address reach physics of correlated materials, such as the fluctuating local moments, spin and orbital fluctuations, atomic multiplet physics and band formation on equal footing. Recently it is getting increasingly recognized that more predictive ab-initio theory of correlated systems needs to also address the feedback effect of the correlated electronic structure on the ionic positions, as the metal-insulator transition is almost always accompanied with considerable structural distortions. We will review recently developed extension of merger between the Density Functional Theory (DFT) and DMFT method, dubbed DFT+ embedded DMFT (DFT+eDMFT), whichsuccessfully addresses this challenge. It is based on the stationary Luttinger-Ward functional to minimize the numerical error, it subtracts the exact double-counting of DFT and DMFT, and implements self-consistent forces on all atoms in the unit cell. In a few examples, we will also show how the method elucidated the important feedback effect of correlations on crystal structure in rare earth nickelates to explain the mechanism of the metal-insulator transition. The method showed that such feedback effect is also essential to understand the dynamic stability of the high-temperature body-centered cubic phase of elemental iron, and in particular it predicted strong enhancement of the electron-phonon coupling over DFT values in FeSe, which was very recently verified by pioneering time-domain experiment.

Normal mode-guided transition pathway generation in proteins

PubMed Central

Lee, Byung Ho; Seo, Sangjae; Kim, Min Hyeok; Kim, Youngjin; Jo, Soojin; Choi, Moon-ki; Lee, Hoomin; Choi, Jae Boong

2017-01-01

The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI) that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this. PMID:29020017

Adsorption structures and energetics of molecules on metal surfaces: Bridging experiment and theory

NASA Astrophysics Data System (ADS)

Maurer, Reinhard J.; Ruiz, Victor G.; Camarillo-Cisneros, Javier; Liu, Wei; Ferri, Nicola; Reuter, Karsten; Tkatchenko, Alexandre

2016-05-01

Adsorption geometry and stability of organic molecules on surfaces are key parameters that determine the observable properties and functions of hybrid inorganic/organic systems (HIOSs). Despite many recent advances in precise experimental characterization and improvements in first-principles electronic structure methods, reliable databases of structures and energetics for large adsorbed molecules are largely amiss. In this review, we present such a database for a range of molecules adsorbed on metal single-crystal surfaces. The systems we analyze include noble-gas atoms, conjugated aromatic molecules, carbon nanostructures, and heteroaromatic compounds adsorbed on five different metal surfaces. The overall objective is to establish a diverse benchmark dataset that enables an assessment of current and future electronic structure methods, and motivates further experimental studies that provide ever more reliable data. Specifically, the benchmark structures and energetics from experiment are here compared with the recently developed van der Waals (vdW) inclusive density-functional theory (DFT) method, DFT + vdWsurf. In comparison to 23 adsorption heights and 17 adsorption energies from experiment we find a mean average deviation of 0.06 Å and 0.16 eV, respectively. This confirms the DFT + vdWsurf method as an accurate and efficient approach to treat HIOSs. A detailed discussion identifies remaining challenges to be addressed in future development of electronic structure methods, for which the here presented benchmark database may serve as an important reference.

Modal parameter identification based on combining transmissibility functions and blind source separation techniques

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Sánchez, Jesús Antonio García; Andersen, Palle

2018-05-01

Transmissibility-based operational modal analysis is a recent and alternative approach used to identify the modal parameters of structures under operational conditions. This approach is advantageous compared with traditional operational modal analysis because it does not make any assumptions about the excitation spectrum (i.e., white noise with a flat spectrum). However, common methodologies do not include a procedure to extract closely spaced modes with low signal-to-noise ratios. This issue is relevant when considering that engineering structures generally have closely spaced modes and that their measured responses present high levels of noise. Therefore, to overcome these problems, a new combined method for modal parameter identification is proposed in this work. The proposed method combines blind source separation (BSS) techniques and transmissibility-based methods. Here, BSS techniques were used to recover source signals, and transmissibility-based methods were applied to estimate modal information from the recovered source signals. To achieve this combination, a new method to define a transmissibility function was proposed. The suggested transmissibility function is based on the relationship between the power spectral density (PSD) of mixed signals and the PSD of signals from a single source. The numerical responses of a truss structure with high levels of added noise and very closely spaced modes were processed using the proposed combined method to evaluate its ability to identify modal parameters in these conditions. Colored and white noise excitations were used for the numerical example. The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes. The results showed that the proposed combined method is capable of identifying very closely spaced modes in the presence of noise and, thus, may be potentially applied to improve the identification of damping ratios.

Total-energy Assisted Tight-binding Method Based on Local Density Approximation of Density Functional Theory

NASA Astrophysics Data System (ADS)

Fujiwara, Takeo; Nishino, Shinya; Yamamoto, Susumu; Suzuki, Takashi; Ikeda, Minoru; Ohtani, Yasuaki

2018-06-01

A novel tight-binding method is developed, based on the extended Hückel approximation and charge self-consistency, with referring the band structure and the total energy of the local density approximation of the density functional theory. The parameters are so adjusted by computer that the result reproduces the band structure and the total energy, and the algorithm for determining parameters is established. The set of determined parameters is applicable to a variety of crystalline compounds and change of lattice constants, and, in other words, it is transferable. Examples are demonstrated for Si crystals of several crystalline structures varying lattice constants. Since the set of parameters is transferable, the present tight-binding method may be applicable also to molecular dynamics simulations of large-scale systems and long-time dynamical processes.

Methods for removing contaminant matter from a porous material

DOEpatents

Fox, Robert V [Idaho Falls, ID; Avci, Recep [Bozeman, MT; Groenewold, Gary S [Idaho Falls, ID

2010-11-16

Methods of removing contaminant matter from porous materials include applying a polymer material to a contaminated surface, irradiating the contaminated surface to cause redistribution of contaminant matter, and removing at least a portion of the polymer material from the surface. Systems for decontaminating a contaminated structure comprising porous material include a radiation device configured to emit electromagnetic radiation toward a surface of a structure, and at least one spray device configured to apply a capture material onto the surface of the structure. Polymer materials that can be used in such methods and systems include polyphosphazine-based polymer materials having polyphosphazine backbone segments and side chain groups that include selected functional groups. The selected functional groups may include iminos, oximes, carboxylates, sulfonates, .beta.-diketones, phosphine sulfides, phosphates, phosphites, phosphonates, phosphinates, phosphine oxides, monothio phosphinic acids, and dithio phosphinic acids.

Plate/shell structure topology optimization of orthotropic material for buckling problem based on independent continuous topological variables

NASA Astrophysics Data System (ADS)

Ye, Hong-Ling; Wang, Wei-Wei; Chen, Ning; Sui, Yun-Kang

2017-10-01

The purpose of the present work is to study the buckling problem with plate/shell topology optimization of orthotropic material. A model of buckling topology optimization is established based on the independent, continuous, and mapping method, which considers structural mass as objective and buckling critical loads as constraints. Firstly, composite exponential function (CEF) and power function (PF) as filter functions are introduced to recognize the element mass, the element stiffness matrix, and the element geometric stiffness matrix. The filter functions of the orthotropic material stiffness are deduced. Then these filter functions are put into buckling topology optimization of a differential equation to analyze the design sensitivity. Furthermore, the buckling constraints are approximately expressed as explicit functions with respect to the design variables based on the first-order Taylor expansion. The objective function is standardized based on the second-order Taylor expansion. Therefore, the optimization model is translated into a quadratic program. Finally, the dual sequence quadratic programming (DSQP) algorithm and the global convergence method of moving asymptotes algorithm with two different filter functions (CEF and PF) are applied to solve the optimal model. Three numerical results show that DSQP&CEF has the best performance in the view of structural mass and discretion.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zemla, A; Lang, D; Kostova, T

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitatemore » the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position.« less

Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors

PubMed Central

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-01-01

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. PMID:24896119

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

Tensor numerical methods in quantum chemistry: from Hartree-Fock to excitation energies.

PubMed

Khoromskaia, Venera; Khoromskij, Boris N

2015-12-21

We resume the recent successes of the grid-based tensor numerical methods and discuss their prospects in real-space electronic structure calculations. These methods, based on the low-rank representation of the multidimensional functions and integral operators, first appeared as an accurate tensor calculus for the 3D Hartree potential using 1D complexity operations, and have evolved to entirely grid-based tensor-structured 3D Hartree-Fock eigenvalue solver. It benefits from tensor calculation of the core Hamiltonian and two-electron integrals (TEI) in O(n log n) complexity using the rank-structured approximation of basis functions, electron densities and convolution integral operators all represented on 3D n × n × n Cartesian grids. The algorithm for calculating TEI tensor in a form of the Cholesky decomposition is based on multiple factorizations using algebraic 1D "density fitting" scheme, which yield an almost irreducible number of product basis functions involved in the 3D convolution integrals, depending on a threshold ε > 0. The basis functions are not restricted to separable Gaussians, since the analytical integration is substituted by high-precision tensor-structured numerical quadratures. The tensor approaches to post-Hartree-Fock calculations for the MP2 energy correction and for the Bethe-Salpeter excitation energies, based on using low-rank factorizations and the reduced basis method, were recently introduced. Another direction is towards the tensor-based Hartree-Fock numerical scheme for finite lattices, where one of the numerical challenges is the summation of electrostatic potentials of a large number of nuclei. The 3D grid-based tensor method for calculation of a potential sum on a L × L × L lattice manifests the linear in L computational work, O(L), instead of the usual O(L(3) log L) scaling by the Ewald-type approaches.

T-RMSD: a fine-grained, structure-based classification method and its application to the functional characterization of TNF receptors.

PubMed

Magis, Cedrik; Stricher, François; van der Sloot, Almer M; Serrano, Luis; Notredame, Cedric

2010-07-16

This study addresses the relation between structural and functional similarity in proteins. We introduce a novel method named tree based on root mean square deviation (T-RMSD), which uses distance RMSD (dRMSD) variations to build fine-grained structure-based classifications of proteins. The main improvement of the T-RMSD over similar methods, such as Dali, is its capacity to produce the equivalent of a bootstrap value for each cluster node. We validated our approach on two domain families studied extensively for their role in many biological and pathological pathways: the small GTPase RAS superfamily and the cysteine-rich domains (CRDs) associated with the tumor necrosis factor receptors (TNFRs) family. Our analysis showed that T-RMSD is able to automatically recover and refine existing classifications. In the case of the small GTPase ARF subfamily, T-RMSD can distinguish GTP- from GDP-bound states, while in the case of CRDs it can identify two new subgroups associated with well defined functional features (ligand binding and formation of ligand pre-assembly complex). We show how hidden Markov models (HMMs) can be built on these new groups and propose a methodology to use these models simultaneously in order to do fine-grained functional genomic annotation without known 3D structures. T-RMSD, an open source freeware incorporated in the T-Coffee package, is available online. 2010 Elsevier Ltd. All rights reserved.

Generator Coordinate Method Analysis of Xe and Ba Isotopes

NASA Astrophysics Data System (ADS)

Higashiyama, Koji; Yoshinaga, Naotaka; Teruya, Eri

Nuclear structure of Xe and Ba isotopes is studied in terms of the quantum-number projected generator coordinate method (GCM). The GCM reproduces well the energy levels of high-spin states as well as low-lying states. The structure of the low-lying states is analyzed through the GCM wave functions.

Comparison of two fractal interpolation methods

NASA Astrophysics Data System (ADS)

Fu, Yang; Zheng, Zeyu; Xiao, Rui; Shi, Haibo

2017-03-01

As a tool for studying complex shapes and structures in nature, fractal theory plays a critical role in revealing the organizational structure of the complex phenomenon. Numerous fractal interpolation methods have been proposed over the past few decades, but they differ substantially in the form features and statistical properties. In this study, we simulated one- and two-dimensional fractal surfaces by using the midpoint displacement method and the Weierstrass-Mandelbrot fractal function method, and observed great differences between the two methods in the statistical characteristics and autocorrelation features. From the aspect of form features, the simulations of the midpoint displacement method showed a relatively flat surface which appears to have peaks with different height as the fractal dimension increases. While the simulations of the Weierstrass-Mandelbrot fractal function method showed a rough surface which appears to have dense and highly similar peaks as the fractal dimension increases. From the aspect of statistical properties, the peak heights from the Weierstrass-Mandelbrot simulations are greater than those of the middle point displacement method with the same fractal dimension, and the variances are approximately two times larger. When the fractal dimension equals to 1.2, 1.4, 1.6, and 1.8, the skewness is positive with the midpoint displacement method and the peaks are all convex, but for the Weierstrass-Mandelbrot fractal function method the skewness is both positive and negative with values fluctuating in the vicinity of zero. The kurtosis is less than one with the midpoint displacement method, and generally less than that of the Weierstrass-Mandelbrot fractal function method. The autocorrelation analysis indicated that the simulation of the midpoint displacement method is not periodic with prominent randomness, which is suitable for simulating aperiodic surface. While the simulation of the Weierstrass-Mandelbrot fractal function method has strong periodicity, which is suitable for simulating periodic surface.

Structural studies of RNA-protein complexes: A hybrid approach involving hydrodynamics, scattering, and computational methods.

PubMed

Patel, Trushar R; Chojnowski, Grzegorz; Astha; Koul, Amit; McKenna, Sean A; Bujnicki, Janusz M

2017-04-15

The diverse functional cellular roles played by ribonucleic acids (RNA) have emphasized the need to develop rapid and accurate methodologies to elucidate the relationship between the structure and function of RNA. Structural biology tools such as X-ray crystallography and Nuclear Magnetic Resonance are highly useful methods to obtain atomic-level resolution models of macromolecules. However, both methods have sample, time, and technical limitations that prevent their application to a number of macromolecules of interest. An emerging alternative to high-resolution structural techniques is to employ a hybrid approach that combines low-resolution shape information about macromolecules and their complexes from experimental hydrodynamic (e.g. analytical ultracentrifugation) and solution scattering measurements (e.g., solution X-ray or neutron scattering), with computational modeling to obtain atomic-level models. While promising, scattering methods rely on aggregation-free, monodispersed preparations and therefore the careful development of a quality control pipeline is fundamental to an unbiased and reliable structural determination. This review article describes hydrodynamic techniques that are highly valuable for homogeneity studies, scattering techniques useful to study the low-resolution shape, and strategies for computational modeling to obtain high-resolution 3D structural models of RNAs, proteins, and RNA-protein complexes. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Self-consistent DFT +U method for real-space time-dependent density functional theory calculations

NASA Astrophysics Data System (ADS)

Tancogne-Dejean, Nicolas; Oliveira, Micael J. T.; Rubio, Angel

2017-12-01

We implemented various DFT+U schemes, including the Agapito, Curtarolo, and Buongiorno Nardelli functional (ACBN0) self-consistent density-functional version of the DFT +U method [Phys. Rev. X 5, 011006 (2015), 10.1103/PhysRevX.5.011006] within the massively parallel real-space time-dependent density functional theory (TDDFT) code octopus. We further extended the method to the case of the calculation of response functions with real-time TDDFT+U and to the description of noncollinear spin systems. The implementation is tested by investigating the ground-state and optical properties of various transition-metal oxides, bulk topological insulators, and molecules. Our results are found to be in good agreement with previously published results for both the electronic band structure and structural properties. The self-consistent calculated values of U and J are also in good agreement with the values commonly used in the literature. We found that the time-dependent extension of the self-consistent DFT+U method yields improved optical properties when compared to the empirical TDDFT+U scheme. This work thus opens a different theoretical framework to address the nonequilibrium properties of correlated systems.

Investigations of Sayre's Equation.

NASA Astrophysics Data System (ADS)

Shiono, Masaaki

Available from UMI in association with The British Library. Since the discovery of X-ray diffraction, various methods of using it to solve crystal structures have been developed. The major methods used can be divided into two categories: (1) Patterson function based methods; (2) Direct phase-determination methods. In the early days of structure determination from X-ray diffraction, Patterson methods played the leading role. Direct phase-determining methods ('direct methods' for short) were introduced by D. Harker and J. S. Kasper in the form of inequality relationships in 1948. A significant development of direct methods was produced by Sayre (1952). The equation he introduced, generally called Sayre's equation, gives exact relationships between structure factors for equal atoms. Later Cochran (1955) derived the so-called triple phase relationship, the main means by which it has become possible to find the structure factor phases automatically by computer. Although the background theory of direct methods is very mathematical, the user of direct-methods computer programs needs no detailed knowledge of these automatic processes in order to solve structures. Recently introduced direct methods are based on Sayre's equation, so it is important to investigate its properties thoroughly. One such new method involves the Sayre equation tangent formula (SETF) which attempts to minimise the least square residual for the Sayre's equations (Debaerdemaeker, Tate and Woolfson; 1985). In chapters I-III the principles and developments of direct methods will be described and in chapters IV -VI the properties of Sayre's equation and its modification will be discussed. Finally, in chapter VII, there will be described the investigation of the possible use of an equation, similar in type to Sayre's equation, derived from the characteristics of the Patterson function.

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Relations between Brain Structure and Attentional Function in Spina Bifida: Utilization of Robust Statistical Approaches

PubMed Central

Kulesz, Paulina A.; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M.; Francis, David J.

2015-01-01

Objective Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Method Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product moment correlation was compared with four robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator Results All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Conclusions Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PMID:25495830

A method for the direct measurement of electronic site populations in a molecular aggregate using two-dimensional electronic-vibrational spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Nicholas H. C.; Dong, Hui; Oliver, Thomas A. A.

2015-09-28

Two dimensional electronic spectroscopy has proven to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derivemore » response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.« less

A method for the direct measurement of electronic site populations in a molecular aggregate using two-dimensional electronic-vibrational spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Nicholas H. C.; Dong, Hui; Oliver, Thomas A. A.

2015-09-28

Two dimensional electronic spectroscopy has proved to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derivemore » response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.« less

A method for the direct measurement of electronic site populations in a molecular aggregate using two-dimensional electronic-vibrational spectroscopy.

PubMed

Lewis, Nicholas H C; Dong, Hui; Oliver, Thomas A A; Fleming, Graham R

2015-09-28

Two dimensional electronic spectroscopy has proved to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derive response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.

Study on structural and spectral properties of isobavachalcone and 4-hydroxyderricin by computational method

NASA Astrophysics Data System (ADS)

Rong, Yuzhi; Wu, Jinhong; Liu, Xing; Zhao, Bo; Wang, Zhengwu

Isobavachalcone and 4-hydroxyderricin, two major chalcone constituents isolated from the roots of Angelica keiskei KOIDZUMI, exhibit numerous biological activities. Quantum chemical methods have been employed to investigate their structural and spectral properties. The ground state structures were optimized using density functional B3LYP method with 6-311G (d, p) basis set in both gas and solvent phases. Based on the optimized geometries, the harmonic vibrational frequency, the 1H and 13C nuclear magnetic resonance (NMR) chemical shift using the GIAO method were calculated at the same level of theory, with the aim of verifying the experimental values. Results reveal that B3LYP has been a good method to study their vibrational spectroscopic and NMR spectral properties of the two chalcones. The electronic absorption spectra were calculated using the time-dependent density functional theory (TDDFT) method. The solvent polarity effects were considered and calculated using the polarizable continuum model (PCM). Results also show that substitutions of different electron donating groups can alter the absorption properties and shift the spectra to a higher wavelength region.

Prediction of molecular crystal structures by a crystallographic QM/MM model with full space-group symmetry.

PubMed

Mörschel, Philipp; Schmidt, Martin U

2015-01-01

A crystallographic quantum-mechanical/molecular-mechanical model (c-QM/MM model) with full space-group symmetry has been developed for molecular crystals. The lattice energy was calculated by quantum-mechanical methods for short-range interactions and force-field methods for long-range interactions. The quantum-mechanical calculations covered the interactions within the molecule and the interactions of a reference molecule with each of the surrounding 12-15 molecules. The interactions with all other molecules were treated by force-field methods. In each optimization step the energies in the QM and MM shells were calculated separately as single-point energies; after adding both energy contributions, the crystal structure (including the lattice parameters) was optimized accordingly. The space-group symmetry was maintained throughout. Crystal structures with more than one molecule per asymmetric unit, e.g. structures with Z' = 2, hydrates and solvates, have been optimized as well. Test calculations with different quantum-mechanical methods on nine small organic molecules revealed that the density functional theory methods with dispersion correction using the B97-D functional with 6-31G* basis set in combination with the DREIDING force field reproduced the experimental crystal structures with good accuracy. Subsequently the c-QM/MM method was applied to nine compounds from the CCDC blind tests resulting in good energy rankings and excellent geometric accuracies.

Theoretical investigation of cyromazine tautomerism using density functional theory and Møller–Plesset perturbation theory methods

USDA-ARS?s Scientific Manuscript database

A computational chemistry analysis of six unique tautomers of cyromazine, a pesticide used for fly control, was performed with density functional theory (DFT) and canonical second order Møller–Plesset perturbation theory (MP2) methods to gain insight into the contributions of molecular structure to ...

Neurolinguistic Foundations to Methods of Teaching a Second Language.

ERIC Educational Resources Information Center

Walsh, Terrence M.; Diller, Karl C.

Applied linguistic theory is examined in light of neuroscientific knowledge, especially in regard to the structure and function of the cerebral cortex, in order to illuminate the process and methods of teaching or learning language. Wernicke's Area and Broca's Area are parts of the brain that have been associated with language function.…

The Human Placenta Project: Placental Structure, Development, and Function in Real Time

PubMed Central

Guttmacher, Alan E.; Maddox, Yvonne T.; Spong, Catherine Y.

2014-01-01

Despite its crucial role in the health of both the fetus and the pregnant woman, the placenta is the least understood human organ. Since a growing body of evidence also underscores the importance of placental development in the lifelong health of both mother and offspring, this lack of knowledge about placental structure and function is particularly concerning. Given modern approaches and technologies and the ability to develop new methods, we propose a coordinated “Human Placenta Project,” with the ultimate goal of understanding human placental structure, development, and function in real time. PMID:24661567

Use of Random and Site-Directed Mutagenesis to Probe Protein Structure-Function Relationships: Applied Techniques in the Study of Helicobacter pylori.

PubMed

Whitmire, Jeannette M; Merrell, D Scott

2017-01-01

Mutagenesis is a valuable tool to examine the structure-function relationships of bacterial proteins. As such, a wide variety of mutagenesis techniques and strategies have been developed. This chapter details a selection of random mutagenesis methods and site-directed mutagenesis procedures that can be applied to an array of bacterial species. Additionally, the direct application of the techniques to study the Helicobacter pylori Ferric Uptake Regulator (Fur) protein is described. The varied approaches illustrated herein allow the robust investigation of the structural-functional relationships within a protein of interest.

Efficacy of function specific 3D-motifs in enzyme classification according to their EC-numbers.

PubMed

Rahimi, Amir; Madadkar-Sobhani, Armin; Touserkani, Rouzbeh; Goliaei, Bahram

2013-11-07

Due to the increasing number of protein structures with unknown function originated from structural genomics projects, protein function prediction has become an important subject in bioinformatics. Among diverse function prediction methods, exploring known 3D-motifs, which are associated with functional elements in unknown protein structures is one of the most biologically meaningful methods. Homologous enzymes inherit such motifs in their active sites from common ancestors. However, slight differences in the properties of these motifs, results in variation in the reactions and substrates of the enzymes. In this study, we examined the possibility of discriminating highly related active site patterns according to their EC-numbers by 3D-motifs. For each EC-number, the spatial arrangement of an active site, which has minimum average distance to other active sites with the same function, was selected as a representative 3D-motif. In order to characterize the motifs, various points in active site elements were tested. The results demonstrated the possibility of predicting full EC-number of enzymes by 3D-motifs. However, the discriminating power of 3D-motifs varies among different enzyme families and depends on selecting the appropriate points and features. © 2013 Elsevier Ltd. All rights reserved.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Visualizing water molecules in transmembrane proteins using radiolytic labeling methods†

PubMed Central

Orban, Tivadar; Gupta, Sayan; Palczewski, Krzysztof; Chance, Mark R.

2010-01-01

Essential to cells and their organelles, water is both shuttled to where it is needed and trapped within cellular compartments and structures. Moreover, ordered waters within protein structures often co-localize with strategically placed polar or charged groups critical for protein function. Yet it is unclear if these ordered water molecules provide structural stabilization, mediate conformational changes in signaling, neutralize charged residues, or carry out a combination of all these functions. Structures of many integral membrane proteins, including G protein-coupled receptors (GPCRs), reveal the presence of ordered water molecules that may act like prosthetic groups in a manner quite unlike bulk water. Identification of ‘ordered’ waters within a crystalline protein structure requires sufficient occupancy of water to enable its detection in the protein's X-ray diffraction pattern and thus the observed waters likely represent a subset of tightly-bound functional waters. In this review, we highlight recent studies that suggest the structures of ordered waters within GPCRs are as conserved (and thus as important) as conserved side chains. In addition, methods of radiolysis, coupled to structural mass spectrometry (protein footprinting), reveal dynamic changes in water structure that mediate transmembrane signaling. The idea of water as a prosthetic group mediating chemical reaction dynamics is not new in fields such as catalysis. However, the concept of water as a mediator of conformational dynamics in signaling is just emerging, owing to advances in both crystallographic structure determination and new methods of protein footprinting. Although oil and water do not mix, understanding the roles of water is essential to understanding the function of membrane proteins. PMID:20047303

Toward a methodical framework for comprehensively assessing forest multifunctionality.

PubMed

Trogisch, Stefan; Schuldt, Andreas; Bauhus, Jürgen; Blum, Juliet A; Both, Sabine; Buscot, François; Castro-Izaguirre, Nadia; Chesters, Douglas; Durka, Walter; Eichenberg, David; Erfmeier, Alexandra; Fischer, Markus; Geißler, Christian; Germany, Markus S; Goebes, Philipp; Gutknecht, Jessica; Hahn, Christoph Zacharias; Haider, Sylvia; Härdtle, Werner; He, Jin-Sheng; Hector, Andy; Hönig, Lydia; Huang, Yuanyuan; Klein, Alexandra-Maria; Kühn, Peter; Kunz, Matthias; Leppert, Katrin N; Li, Ying; Liu, Xiaojuan; Niklaus, Pascal A; Pei, Zhiqin; Pietsch, Katherina A; Prinz, Ricarda; Proß, Tobias; Scherer-Lorenzen, Michael; Schmidt, Karsten; Scholten, Thomas; Seitz, Steffen; Song, Zhengshan; Staab, Michael; von Oheimb, Goddert; Weißbecker, Christina; Welk, Erik; Wirth, Christian; Wubet, Tesfaye; Yang, Bo; Yang, Xuefei; Zhu, Chao-Dong; Schmid, Bernhard; Ma, Keping; Bruelheide, Helge

2017-12-01

Biodiversity-ecosystem functioning (BEF) research has extended its scope from communities that are short-lived or reshape their structure annually to structurally complex forest ecosystems. The establishment of tree diversity experiments poses specific methodological challenges for assessing the multiple functions provided by forest ecosystems. In particular, methodological inconsistencies and nonstandardized protocols impede the analysis of multifunctionality within, and comparability across the increasing number of tree diversity experiments. By providing an overview on key methods currently applied in one of the largest forest biodiversity experiments, we show how methods differing in scale and simplicity can be combined to retrieve consistent data allowing novel insights into forest ecosystem functioning. Furthermore, we discuss and develop recommendations for the integration and transferability of diverse methodical approaches to present and future forest biodiversity experiments. We identified four principles that should guide basic decisions concerning method selection for tree diversity experiments and forest BEF research: (1) method selection should be directed toward maximizing data density to increase the number of measured variables in each plot. (2) Methods should cover all relevant scales of the experiment to consider scale dependencies of biodiversity effects. (3) The same variable should be evaluated with the same method across space and time for adequate larger-scale and longer-time data analysis and to reduce errors due to changing measurement protocols. (4) Standardized, practical and rapid methods for assessing biodiversity and ecosystem functions should be promoted to increase comparability among forest BEF experiments. We demonstrate that currently available methods provide us with a sophisticated toolbox to improve a synergistic understanding of forest multifunctionality. However, these methods require further adjustment to the specific requirements of structurally complex and long-lived forest ecosystems. By applying methods connecting relevant scales, trophic levels, and above- and belowground ecosystem compartments, knowledge gain from large tree diversity experiments can be optimized.

A real-space stochastic density matrix approach for density functional electronic structure.

PubMed

Beck, Thomas L

2015-12-21

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

A Model-Based Approach for Microvasculature Structure Distortion Correction in Two-Photon Fluorescence Microscopy Images

PubMed Central

Dao, Lam; Glancy, Brian; Lucotte, Bertrand; Chang, Lin-Ching; Balaban, Robert S; Hsu, Li-Yueh

2015-01-01

SUMMARY This paper investigates a post-processing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modeling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to sub volumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images. PMID:26224257

Printing three-dimensional tissue analogues with decellularized extracellular matrix bioink

PubMed Central

Pati, Falguni; Jang, Jinah; Ha, Dong-Heon; Won Kim, Sung; Rhie, Jong-Won; Shim, Jin-Hyung; Kim, Deok-Ho; Cho, Dong-Woo

2014-01-01

The ability to print and pattern all the components that make up a tissue (cells and matrix materials) in three dimensions to generate structures similar to tissues is an exciting prospect of bioprinting. However, the majority of the matrix materials used so far for bioprinting cannot represent the complexity of natural extracellular matrix (ECM) and thus are unable to reconstitute the intrinsic cellular morphologies and functions. Here, we develop a method for the bioprinting of cell-laden constructs with novel decellularized extracellular matrix (dECM) bioink capable of providing an optimized microenvironment conducive to the growth of three-dimensional structured tissue. We show the versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function. We achieve high cell viability and functionality of the printed dECM structures using our bioprinting method. PMID:24887553

The Precambrian crustal structure of East Africa

NASA Astrophysics Data System (ADS)

Young, A. J.; Tugume, F.; Nyblade, A.; Julia, J.; Mulibo, G.

2011-12-01

We present new results on crustal structure from East Africa from analyzing P wave receiver functions. The data for this study come from temporary AfricaArray broadband seismic stations deployed between 2007 and 2011 in Uganda, Tanzania and Zambia. Receiver functions have been computed using an iterative deconvolution method. Crustal structure has been imaged using the H-k stacking method and by jointly inverting the receiver functions and surface wave phase and group velocities. The results show remarkably uniform crust throughout the Archean and Proterozoic terrains that comprise the Precambrian tectonic framework of the region. Crustal thickness for most terrains is between 37 and 40 km, and Poisson's ratio is between 0.25 and 0.27. Results from the joint inversion yield average crustal Vs values of 3.6 to 3.7 km/s. For most terrains, a thin (1-5 km) thick high velocity (Vs>4.0 km/s) is found at the base of the crust.

Prediction of enzymatic pathways by integrative pathway mapping

PubMed Central

Wichelecki, Daniel J; San Francisco, Brian; Zhao, Suwen; Rodionov, Dmitry A; Vetting, Matthew W; Al-Obaidi, Nawar F; Lin, Henry; O'Meara, Matthew J; Scott, David A; Morris, John H; Russel, Daniel; Almo, Steven C; Osterman, Andrei L

2018-01-01

The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology. PMID:29377793

Printing three-dimensional tissue analogues with decellularized extracellular matrix bioink

NASA Astrophysics Data System (ADS)

Pati, Falguni; Jang, Jinah; Ha, Dong-Heon; Won Kim, Sung; Rhie, Jong-Won; Shim, Jin-Hyung; Kim, Deok-Ho; Cho, Dong-Woo

2014-06-01

The ability to print and pattern all the components that make up a tissue (cells and matrix materials) in three dimensions to generate structures similar to tissues is an exciting prospect of bioprinting. However, the majority of the matrix materials used so far for bioprinting cannot represent the complexity of natural extracellular matrix (ECM) and thus are unable to reconstitute the intrinsic cellular morphologies and functions. Here, we develop a method for the bioprinting of cell-laden constructs with novel decellularized extracellular matrix (dECM) bioink capable of providing an optimized microenvironment conducive to the growth of three-dimensional structured tissue. We show the versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function. We achieve high cell viability and functionality of the printed dECM structures using our bioprinting method.

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

PubMed Central

Ding, Feng; Sharma, Shantanu; Chalasani, Poornima; Demidov, Vadim V.; Broude, Natalia E.; Dokholyan, Nikolay V.

2008-01-01

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNAPhe, pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses. PMID:18456842

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

This report was prepared at the request of the Lawrence Livermore Laboratory (LLL) to provide background information for analyzing soil-structure interaction by the frequency-independent impedance function approach. LLL is conducting such analyses as part of its seismic review of selected operating plants under the Systematic Evaluation Program for the US Nuclear Regulatory Commission. The analytical background and basic assumptionsof the impedance function theory are briefly reviewed, and the role of radiation damping in soil-structure interaction analysis is discussed. The validity of modeling soil-structure interaction by using frequency-independent functions is evaluated based on data from several field tests. Finally, the recommendedmore » procedures for performing soil-structure interaction analyses are discussed with emphasis on the modal superposition method.« less

Fiber-reinforced dielectric elastomer laminates with integrated function of actuating and sensing

NASA Astrophysics Data System (ADS)

Li, Tiefeng; Xie, Yuhan; Li, Chi; Yang, Xuxu; Jin, Yongbin; Liu, Junjie; Huang, Xiaoqiang

2015-04-01

The natural limbs of animals and insects integrate muscles, skins and neurons, providing both the actuating and sensing functions simultaneously. Inspired by the natural structure, we present a novel structure with integrated function of actuating and sensing with dielectric elastomer (DE) laminates. The structure can deform when subjected to high voltage loading and generate corresponding output signal in return. We investigate the basic physical phenomenon of dielectric elastomer experimentally. It is noted that when applying high voltage, the actuating dielectric elastomer membrane deforms and the sensing dielectric elastomer membrane changes the capacitance in return. Based on the concept, finite element method (FEM) simulation has been conducted to further investigate the electromechanical behavior of the structure.

A cubic extended interior penalty function for structural optimization

NASA Technical Reports Server (NTRS)

Prasad, B.; Haftka, R. T.

1979-01-01

This paper describes an optimization procedure for the minimum weight design of complex structures. The procedure is based on a new cubic extended interior penalty function (CEIPF) used with the sequence of unconstrained minimization technique (SUMT) and Newton's method. The Hessian matrix of the penalty function is approximated using only constraints and their derivatives. The CEIPF is designed to minimize the error in the approximation of the Hessian matrix, and as a result the number of structural analyses required is small and independent of the number of design variables. Three example problems are reported. The number of structural analyses is reduced by as much as 50 per cent below previously reported results.

System and method for memory allocation in a multiclass memory system

DOEpatents

Loh, Gabriel; Meswani, Mitesh; Ignatowski, Michael; Nutter, Mark

2016-06-28

A system for memory allocation in a multiclass memory system includes a processor coupleable to a plurality of memories sharing a unified memory address space, and a library store to store a library of software functions. The processor identifies a type of a data structure in response to a memory allocation function call to the library for allocating memory to the data structure. Using the library, the processor allocates portions of the data structure among multiple memories of the multiclass memory system based on the type of the data structure.

First principle study of transport properties of a graphene nano structure

NASA Astrophysics Data System (ADS)

Kumar, Naveen; Sharma, Munish; Sharma, Jyoti Dhar; Ahluwalia, P. K.

2013-06-01

The first principle quantum transport calculations have been performed for graphene using Tran SIESTA which calculates transport properties using nonequilibrium Green's function method in conjunction with density-functional theory. Transmission functions, electron density of states and current-voltage characteristic have been calculated for a graphene nano structure using graphene electrodes. Transmission function, density of states and projected density of states show a discrete band structure which varies with applied voltage. The value of current is very low for applied voltage between 0.0 V to 5.0 V and lies in the range of pico ampere. In the V-I characteristic current shows non-linear fluctuating pattern with increase in voltage.

Flow cytometry combined with viSNE for the analysis of microbial biofilms and detection of microplastics

PubMed Central

Sgier, Linn; Freimann, Remo; Zupanic, Anze; Kroll, Alexandra

2016-01-01

Biofilms serve essential ecosystem functions and are used in different technical applications. Studies from stream ecology and waste-water treatment have shown that biofilm functionality depends to a great extent on community structure. Here we present a fast and easy-to-use method for individual cell-based analysis of stream biofilms, based on stain-free flow cytometry and visualization of the high-dimensional data by viSNE. The method allows the combined assessment of community structure, decay of phototrophic organisms and presence of abiotic particles. In laboratory experiments, it allows quantification of cellular decay and detection of survival of larger cells after temperature stress, while in the field it enables detection of community structure changes that correlate with known environmental drivers (flow conditions, dissolved organic carbon, calcium) and detection of microplastic contamination. The method can potentially be applied to other biofilm types, for example, for inferring community structure for environmental and industrial research and monitoring. PMID:27188265

Complex basis functions for molecular resonances: Methodology and applications

NASA Astrophysics Data System (ADS)

White, Alec; McCurdy, C. William; Head-Gordon, Martin

The computation of positions and widths of metastable electronic states is a challenge for molecular electronic structure theory because, in addition to the difficulty of the many-body problem, such states obey scattering boundary conditions. These resonances cannot be addressed with naïve application of traditional bound state electronic structure theory. Non-Hermitian electronic structure methods employing complex basis functions is one way that we may rigorously treat resonances within the framework of traditional electronic structure theory. In this talk, I will discuss our recent work in this area including the methodological extension from single determinant SCF-based approaches to highly correlated levels of wavefunction-based theory such as equation of motion coupled cluster and many-body perturbation theory. These approaches provide a hierarchy of theoretical methods for the computation of positions and widths of molecular resonances. Within this framework, we may also examine properties of resonances including the dependence of these parameters on molecular geometry. Some applications of these methods to temporary anions and dianions will also be discussed.

Multiple-wavelength neutron holography with pulsed neutrons

PubMed Central

Hayashi, Kouichi; Ohoyama, Kenji; Happo, Naohisa; Matsushita, Tomohiro; Hosokawa, Shinya; Harada, Masahide; Inamura, Yasuhiro; Nitani, Hiroaki; Shishido, Toetsu; Yubuta, Kunio

2017-01-01

Local structures around impurities in solids provide important information for understanding the mechanisms of material functions, because most of them are controlled by dopants. For this purpose, the x-ray absorption fine structure method, which provides radial distribution functions around specific elements, is most widely used. However, a similar method using neutron techniques has not yet been developed. If one can establish a method of local structural analysis with neutrons, then a new frontier of materials science can be explored owing to the specific nature of neutron scattering—that is, its high sensitivity to light elements and magnetic moments. Multiple-wavelength neutron holography using the time-of-flight technique with pulsed neutrons has great potential to realize this. We demonstrated multiple-wavelength neutron holography using a Eu-doped CaF2 single crystal and obtained a clear three-dimensional atomic image around trivalent Eu substituted for divalent Ca, revealing an interesting feature of the local structure that allows it to maintain charge neutrality. The new holography technique is expected to provide new information on local structures using the neutron technique. PMID:28835917

Multiple-wavelength neutron holography with pulsed neutrons.

PubMed

Hayashi, Kouichi; Ohoyama, Kenji; Happo, Naohisa; Matsushita, Tomohiro; Hosokawa, Shinya; Harada, Masahide; Inamura, Yasuhiro; Nitani, Hiroaki; Shishido, Toetsu; Yubuta, Kunio

2017-08-01

Local structures around impurities in solids provide important information for understanding the mechanisms of material functions, because most of them are controlled by dopants. For this purpose, the x-ray absorption fine structure method, which provides radial distribution functions around specific elements, is most widely used. However, a similar method using neutron techniques has not yet been developed. If one can establish a method of local structural analysis with neutrons, then a new frontier of materials science can be explored owing to the specific nature of neutron scattering-that is, its high sensitivity to light elements and magnetic moments. Multiple-wavelength neutron holography using the time-of-flight technique with pulsed neutrons has great potential to realize this. We demonstrated multiple-wavelength neutron holography using a Eu-doped CaF 2 single crystal and obtained a clear three-dimensional atomic image around trivalent Eu substituted for divalent Ca, revealing an interesting feature of the local structure that allows it to maintain charge neutrality. The new holography technique is expected to provide new information on local structures using the neutron technique.

Structural Optimization for Reliability Using Nonlinear Goal Programming

NASA Technical Reports Server (NTRS)

El-Sayed, Mohamed E.

1999-01-01

This report details the development of a reliability based multi-objective design tool for solving structural optimization problems. Based on two different optimization techniques, namely sequential unconstrained minimization and nonlinear goal programming, the developed design method has the capability to take into account the effects of variability on the proposed design through a user specified reliability design criterion. In its sequential unconstrained minimization mode, the developed design tool uses a composite objective function, in conjunction with weight ordered design objectives, in order to take into account conflicting and multiple design criteria. Multiple design criteria of interest including structural weight, load induced stress and deflection, and mechanical reliability. The nonlinear goal programming mode, on the other hand, provides for a design method that eliminates the difficulty of having to define an objective function and constraints, while at the same time has the capability of handling rank ordered design objectives or goals. For simulation purposes the design of a pressure vessel cover plate was undertaken as a test bed for the newly developed design tool. The formulation of this structural optimization problem into sequential unconstrained minimization and goal programming form is presented. The resulting optimization problem was solved using: (i) the linear extended interior penalty function method algorithm; and (ii) Powell's conjugate directions method. Both single and multi-objective numerical test cases are included demonstrating the design tool's capabilities as it applies to this design problem.

Towards solution and refinement of organic crystal structures by fitting to the atomic pair distribution function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prill, Dragica; Juhas, Pavol; Billinge, Simon J. L.

2016-01-01

In this study, a method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may bemore » used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.« less

A method for surface topography measurement using a new focus function based on dual-tree complex wavelet transform

NASA Astrophysics Data System (ADS)

Li, Shimiao; Guo, Tong; Yuan, Lin; Chen, Jinping

2018-01-01

Surface topography measurement is an important tool widely used in many fields to determine the characteristics and functionality of a part or material. Among existing methods for this purpose, the focus variation method has proved high performance particularly in large slope scenarios. However, its performance depends largely on the effectiveness of focus function. This paper presents a method for surface topography measurement using a new focus measurement function based on dual-tree complex wavelet transform. Experiments are conducted on simulated defocused images to prove its high performance in comparison with other traditional approaches. The results showed that the new algorithm has better unimodality and sharpness. The method was also verified by measuring a MEMS micro resonator structure.

Global Dynamics of Proteins: Bridging Between Structure and Function

PubMed Central

Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781

Global dynamics of proteins: bridging between structure and function.

PubMed

Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.

A new hierarchical method to find community structure in networks

NASA Astrophysics Data System (ADS)

Saoud, Bilal; Moussaoui, Abdelouahab

2018-04-01

Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

Relating Anaerobic Digestion Microbial Community and Process Function.

PubMed

Venkiteshwaran, Kaushik; Bocher, Benjamin; Maki, James; Zitomer, Daniel

2015-01-01

Anaerobic digestion (AD) involves a consortium of microorganisms that convert substrates into biogas containing methane for renewable energy. The technology has suffered from the perception of being periodically unstable due to limited understanding of the relationship between microbial community structure and function. The emphasis of this review is to describe microbial communities in digesters and quantitative and qualitative relationships between community structure and digester function. Progress has been made in the past few decades to identify key microorganisms influencing AD. Yet, more work is required to realize robust, quantitative relationships between microbial community structure and functions such as methane production rate and resilience after perturbations. Other promising areas of research for improved AD may include methods to increase/control (1) hydrolysis rate, (2) direct interspecies electron transfer to methanogens, (3) community structure-function relationships of methanogens, (4) methanogenesis via acetate oxidation, and (5) bioaugmentation to study community-activity relationships or improve engineered bioprocesses.

A deep look into the spray coating process in real-time—the crucial role of x-rays

NASA Astrophysics Data System (ADS)

Roth, Stephan V.

2016-10-01

Tailoring functional thin films and coating by rapid solvent-based processes is the basis for the fabrication of large scale high-end applications in nanotechnology. Due to solvent loss of the solution or dispersion inherent in the installation of functional thin films and multilayers the spraying and drying processes are strongly governed by non-equilibrium kinetics, often passing through transient states, until the final structure is installed. Therefore, the challenge is to observe the structural build-up during these coating processes in a spatially and time-resolved manner on multiple time and length scales, from the nanostructure to macroscopic length scales. During installation, the interaction of solid-fluid interfaces and between the different layers, the flow and evaporation themselves determine the structure of the coating. Advanced x-ray scattering methods open a powerful pathway for observing the involved processes in situ, from the spray to the coating, and allow for gaining deep insight in the nanostructuring processes. This review first provides an overview over these rapidly evolving methods, with main focus on functional coatings, organic photovoltaics and organic electronics. Secondly the role and decisive advantage of x-rays is outlined. Thirdly, focusing on spray deposition as a rapidly emerging method, recent advances in investigations of spray deposition of functional materials and devices via advanced x-ray scattering methods are presented.

Associations of Structural and Functional Social Support with Diabetes Prevalence in U.S. Hispanics/Latinos: Results from the HCHS/SOL Sociocultural Ancillary Study

PubMed Central

Gallo, Linda C.; Fortmann, Addie L.; McCurley, Jessica L.; Isasi, Carmen R.; Penedo, Frank J.; Daviglus, Martha L.; Roesch, Scott C.; Talavera, Gregory A.; Gouskova, Natalia; Gonzalez, Franklyn; Schneiderman, Neil; Carnethon, Mercedes R.

2015-01-01

Background Little research has examined associations of social support with diabetes (or other physical health outcomes) in Hispanics, who are at elevated risk. Purpose We examined associations between social support and diabetes prevalence in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sociocultural Ancillary Study. Methods Participants were 5181 adults, 18–74 years old, representing diverse Hispanic backgrounds, who underwent baseline exam with fasting blood draw, oral glucose tolerance test, medication review, sociodemographic assessment, and sociocultural exam with functional and structural social support measures. Results In adjusted analyses, one standard deviation higher structural and functional social support related to 16% and 15% lower odds, respectively, of having diabetes. Structural and functional support were related to both previously diagnosed diabetes (OR = .84 and .88, respectively) and newly recognized diabetes prevalence (OR = .84 and .83, respectively). Conclusions Higher functional and structural social support are associated with lower diabetes prevalence in Hispanics/Latinos. PMID:25107504

Beyond sex differences: new approaches for thinking about variation in brain structure and function

PubMed Central

Joel, Daphna; Fausto-Sterling, Anne

2016-01-01

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. PMID:26833844

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Metal-ligand delocalization and spin density in the CuCl{sub 2} and [CuCl{sub 4}]{sup 2−} molecules: Some insights from wave function theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giner, Emmanuel, E-mail: gnrmnl@unife.it; Angeli, Celestino, E-mail: anc@unife.it

2015-09-28

The aim of this paper is to unravel the physical phenomena involved in the calculation of the spin density of the CuCl{sub 2} and [CuCl{sub 4}]{sup 2−} systems using wave function methods. Various types of wave functions are used here, both variational and perturbative, to analyse the effects impacting the spin density. It is found that the spin density on the chlorine ligands strongly depends on the mixing between two types of valence bond structures. It is demonstrated that the main difficulties found in most of the previous studies based on wave function methods come from the fact that eachmore » valence bond structure requires a different set of molecular orbitals and that using a unique set of molecular orbitals in a variational procedure leads to the removal of one of them from the wave function. Starting from these results, a method to compute the spin density at a reasonable computational cost is proposed.« less

Structural and functional plasticity of dendritic spines – root or result of behavior?

PubMed Central

Gipson, Cassandra D.; Olive, M. Foster

2016-01-01

Dendritic spines are multifunctional integrative units of the nervous system and are highly diverse and dynamic in nature. Both internal and external stimuli influence dendritic spine density and morphology on the order of minutes. It is clear that the structural plasticity of dendritic spines is related to changes in synaptic efficacy, learning and memory, and other cognitive processes. However, it is currently unclear whether structural changes in dendritic spines are primary instigators of changes in specific behaviors, a consequence of behavioral changes, or both. In this review, we first review the basic structure and function of dendritic spines in the brain, as well as laboratory methods to characterize and quantify morphological changes in dendritic spines. We then discuss the existing literature on the temporal and functional relationship between changes in dendritic spines in specific brain regions and changes in specific behaviors mediated by those regions. Although technological advancements have allowed us to better understand the functional relevance of structural changes in dendritic spines that are influenced by environmental stimuli, the role of spine dynamics as an underlying driver or consequence of behavior still remains elusive. We conclude that while it is likely that structural changes in dendritic spines are both instigators and results of behavioral changes, improved research tools and methods are needed to experimentally and directly manipulate spine dynamics in order to more empirically delineate the relationship between spine structure and behavior. PMID:27561549

Methods of Attaching or Grafting Carbon Nanotubes to Silicon Surfaces and Composite Structures Derived Therefrom

NASA Technical Reports Server (NTRS)

Tour, James M. (Inventor); Chen, Bo (Inventor); Flatt, Austen K. (Inventor); Stewart, Michael P. (Inventor); Dyke, Christopher A. (Inventor); Maya, Francisco (Inventor)

2012-01-01

The present invention is directed toward methods of attaching or grafting carbon nanotubes (CNTs) to silicon surfaces. In some embodiments, such attaching or grafting occurs via functional groups on either or both of the CNTs and silicon surface. In some embodiments, the methods of the present invention include: (1) reacting a silicon surface with a functionalizing agent (such as oligo(phenylene ethynylene)) to form a functionalized silicon surface; (2) dispersing a quantity of CNTs in a solvent to form dispersed CNTs; and (3) reacting the functionalized silicon surface with the dispersed CNTs. The present invention is also directed to the novel compositions produced by such methods.

Structural Health Monitoring Using High-Density Fiber Optic Strain Sensor and Inverse Finite Element Methods

NASA Technical Reports Server (NTRS)

Vazquez, Sixto L.; Tessler, Alexander; Quach, Cuong C.; Cooper, Eric G.; Parks, Jeffrey; Spangler, Jan L.

2005-01-01

In an effort to mitigate accidents due to system and component failure, NASA s Aviation Safety has partnered with industry, academia, and other governmental organizations to develop real-time, on-board monitoring capabilities and system performance models for early detection of airframe structure degradation. NASA Langley is investigating a structural health monitoring capability that uses a distributed fiber optic strain system and an inverse finite element method for measuring and modeling structural deformations. This report describes the constituent systems that enable this structural monitoring function and discusses results from laboratory tests using the fiber strain sensor system and the inverse finite element method to demonstrate structural deformation estimation on an instrumented test article

DFTB Parameters for the Periodic Table: Part 1, Electronic Structure.

PubMed

Wahiduzzaman, Mohammad; Oliveira, Augusto F; Philipsen, Pier; Zhechkov, Lyuben; van Lenthe, Erik; Witek, Henryk A; Heine, Thomas

2013-09-10

A parametrization scheme for the electronic part of the density-functional based tight-binding (DFTB) method that covers the periodic table is presented. A semiautomatic parametrization scheme has been developed that uses Kohn-Sham energies and band structure curvatures of real and fictitious homoatomic crystal structures as reference data. A confinement potential is used to tighten the Kohn-Sham orbitals, which includes two free parameters that are used to optimize the performance of the method. The method is tested on more than 100 systems and shows excellent overall performance.

Synthesis of aircraft structures using integrated design and analysis methods

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Goetz, R. C.

1978-01-01

A systematic research is reported to develop and validate methods for structural sizing of an airframe designed with the use of composite materials and active controls. This research program includes procedures for computing aeroelastic loads, static and dynamic aeroelasticity, analysis and synthesis of active controls, and optimization techniques. Development of the methods is concerned with the most effective ways of integrating and sequencing the procedures in order to generate structural sizing and the associated active control system, which is optimal with respect to a given merit function constrained by strength and aeroelasticity requirements.

From action representation to action execution: exploring the links between cognitive and biomechanical levels of motor control

PubMed Central

Land, William M.; Volchenkov, Dima; Bläsing, Bettina E.; Schack, Thomas

2013-01-01

Along with superior performance, research indicates that expertise is associated with a number of mediating cognitive adaptations. To this extent, extensive practice is associated with the development of general and task-specific mental representations, which play an important role in the organization and control of action. Recently, new experimental methods have been developed, which allow for investigating the organization and structure of these representations, along with the functional structure of the movement kinematics. In the current article, we present a new approach for examining the overlap between skill representations and motor output. In doing so, we first present an architecture model, which addresses links between biomechanical and cognitive levels of motor control. Next, we review the state of the art in assessing memory structures underlying complex action. Following we present a new spatio-temporal decomposition method for illuminating the functional structure of movement kinematics, and finally, we apply these methods to investigate the overlap between the structure of motor representations in memory and their corresponding kinematic structures. Our aim is to understand the extent to which the output at a kinematic level is governed by representations at a cognitive level of motor control. PMID:24065915

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

PubMed Central

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Real-time ligand binding pocket database search using local surface descriptors.

PubMed

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-07-01

Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.

Recognition of functional sites in protein structures.

PubMed

Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J

2004-06-04

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.

Bioinspired Design: Magnetic Freeze Casting

NASA Astrophysics Data System (ADS)

Porter, Michael Martin

Nature is the ultimate experimental scientist, having billions of years of evolution to design, test, and adapt a variety of multifunctional systems for a plethora of diverse applications. Next-generation materials that draw inspiration from the structure-property-function relationships of natural biological materials have led to many high-performance structural materials with hybrid, hierarchical architectures that fit form to function. In this dissertation, a novel materials processing method, magnetic freeze casting, is introduced to develop porous scaffolds and hybrid composites with micro-architectures that emulate bone, abalone nacre, and other hard biological materials. This method uses ice as a template to form ceramic-based materials with continuously, interconnected microstructures and magnetic fields to control the alignment of these structures in multiple directions. The resulting materials have anisotropic properties with enhanced mechanical performance that have potential applications as bone implants or lightweight structural composites, among others.

Systems and strippable coatings for decontaminating structures that include porous material

DOEpatents

Fox, Robert V [Idaho Falls, ID; Avci, Recep [Bozeman, MT; Groenewold, Gary S [Idaho Falls, ID

2011-12-06

Methods of removing contaminant matter from porous materials include applying a polymer material to a contaminated surface, irradiating the contaminated surface to cause redistribution of contaminant matter, and removing at least a portion of the polymer material from the surface. Systems for decontaminating a contaminated structure comprising porous material include a radiation device configured to emit electromagnetic radiation toward a surface of a structure, and at least one spray device configured to apply a capture material onto the surface of the structure. Polymer materials that can be used in such methods and systems include polyphosphazine-based polymer materials having polyphosphazine backbone segments and side chain groups that include selected functional groups. The selected functional groups may include iminos, oximes, carboxylates, sulfonates, .beta.-diketones, phosphine sulfides, phosphates, phosphites, phosphonates, phosphinates, phosphine oxides, monothio phosphinic acids, and dithio phosphinic acids.

Positive semidefinite tensor factorizations of the two-electron integral matrix for low-scaling ab initio electronic structure.

PubMed

Hoy, Erik P; Mazziotti, David A

2015-08-14

Tensor factorization of the 2-electron integral matrix is a well-known technique for reducing the computational scaling of ab initio electronic structure methods toward that of Hartree-Fock and density functional theories. The simplest factorization that maintains the positive semidefinite character of the 2-electron integral matrix is the Cholesky factorization. In this paper, we introduce a family of positive semidefinite factorizations that generalize the Cholesky factorization. Using an implementation of the factorization within the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], we study several inorganic molecules, alkane chains, and potential energy curves and find that this generalized factorization retains the accuracy and size extensivity of the Cholesky factorization, even in the presence of multi-reference correlation. The generalized family of positive semidefinite factorizations has potential applications to low-scaling ab initio electronic structure methods that treat electron correlation with a computational cost approaching that of the Hartree-Fock method or density functional theory.

Combination of complex momentum representation and Green's function methods in relativistic mean-field theory

NASA Astrophysics Data System (ADS)

Shi, Min; Niu, Zhong-Ming; Liang, Haozhao

2018-06-01

We have combined the complex momentum representation method with the Green's function method in the relativistic mean-field framework to establish the RMF-CMR-GF approach. This new approach is applied to study the halo structure of 74Ca. All the continuum level density of concerned resonant states are calculated accurately without introducing any unphysical parameters, and they are independent of the choice of integral contour. The important single-particle wave functions and densities for the halo phenomenon in 74Ca are discussed in detail.

Complete fold annotation of the human proteome using a novel structural feature space.

PubMed

Middleton, Sarah A; Illuminati, Joseph; Kim, Junhyong

2017-04-13

Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.

A program for calculating photonic band structures, Green's functions and transmission/reflection coefficients using a non-orthogonal FDTD method

NASA Astrophysics Data System (ADS)

Ward, A. J.; Pendry, J. B.

2000-06-01

In this paper we present an updated version of our ONYX program for calculating photonic band structures using a non-orthogonal finite difference time domain method. This new version employs the same transparent formalism as the first version with the same capabilities for calculating photonic band structures or causal Green's functions but also includes extra subroutines for the calculation of transmission and reflection coefficients. Both the electric and magnetic fields are placed onto a discrete lattice by approximating the spacial and temporal derivatives with finite differences. This results in discrete versions of Maxwell's equations which can be used to integrate the fields forwards in time. The time required for a calculation using this method scales linearly with the number of real space points used in the discretization so the technique is ideally suited to handling systems with large and complicated unit cells.

Peeling linear inversion of upper mantle velocity structure with receiver functions

NASA Astrophysics Data System (ADS)

Shen, Xuzhang; Zhou, Huilan

2012-02-01

A peeling linear inversion method is presented to study the upper mantle (from Moho to 800 km depth) velocity structures with receiver functions. The influences of the crustal and upper mantle velocity ratio error on the inversion results are analyzed, and three valid measures are taken for its reduction. This method is tested with the IASP91 and the PREM models, and the upper mantle structures beneath the stations GTA, LZH, and AXX in northwestern China are then inverted. The results indicate that this inversion method is feasible to quantify upper mantle discontinuities, besides the discontinuities between 3 h M ( h M denotes the depth of Moho) and 5 h M due to the interference of multiples from Moho. Smoothing is used to overcome possible false discontinuities from the multiples and ensure the stability of the inversion results, but the detailed information on the depth range between 3 h M and 5 h M is sacrificed.

Structures and construction of nuclear power plants on lunar surface

NASA Astrophysics Data System (ADS)

Shimizu, Katsunori; Kobatake, Masuhiko; Ogawa, Sachio; Kanamori, Hiroshi; Okada, Yasuhiko; Mano, Hideyuki; Takagi, Kenji

1991-07-01

The best structure and construction techniques of nuclear power plants in the severe environments on the lunar surface are studied. Facility construction types (functional conditions such as stable structure, shield thickness, maintainability, safety distances, and service life), construction conditions (such as construction methods, construction equipment, number of personnel, time required for construction, external power supply, and required transportation) and construction feasibility (construction method, reactor transportation between the moon and the earth, ground excavation for installation, loading and unloading, transportation, and installation, filling up the ground, electric power supply of plant S (300 kW class) and plant L (3000 kW class)) are outlined. Items to pay attention to in construction are (1) automation and robotization of construction; (2) cost reduction by multi functional robots; and (3) methods of supplying power to robots. A precast concrete block manufacturing plant is also outlined.

Complete fold annotation of the human proteome using a novel structural feature space

PubMed Central

Middleton, Sarah A.; Illuminati, Joseph; Kim, Junhyong

2017-01-01

Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families. PMID:28406174

Decoupling of the Leading Order DGLAP Evolution Equation with Spin Dependent Structure Functions

NASA Astrophysics Data System (ADS)

Azadbakht, F. Teimoury; Boroun, G. R.

2018-02-01

We propose an analytical solution for DGLAP evolution equations with polarized splitting functions at the Leading Order (LO) approximation based on the Laplace transform method. It is shown that the DGLAP evolution equations can be decoupled completely into two second order differential equations which then are solved analytically by using the initial conditions δ FS(x,Q2)=F[partial δ FS0(x), δ FS0(x)] and {δ G}(x,Q2)=G[partial δ G0(x), δ G0(x)]. We used this method to obtain the polarized structure function of the proton as well as the polarized gluon distribution function inside the proton and compared the numerical results with experimental data of COMPASS, HERMES, and AAC'08 Collaborations. It was found that there is a good agreement between our predictions and the experiments.

Fast Nonlinear Generalized Inversion of Gravity Data with Application to the Three-Dimensional Crustal Density Structure of Sichuan Basin, Southwest China

NASA Astrophysics Data System (ADS)

Wang, Jun; Meng, Xiaohong; Li, Fang

2017-11-01

Generalized inversion is one of the important steps in the quantitative interpretation of gravity data. With appropriate algorithm and parameters, it gives a view of the subsurface which characterizes different geological bodies. However, generalized inversion of gravity data is time consuming due to the large amount of data points and model cells adopted. Incorporating of various prior information as constraints deteriorates the above situation. In the work discussed in this paper, a method for fast nonlinear generalized inversion of gravity data is proposed. The fast multipole method is employed for forward modelling. The inversion objective function is established with weighted data misfit function along with model objective function. The total objective function is solved by a dataspace algorithm. Moreover, depth weighing factor is used to improve depth resolution of the result, and bound constraint is incorporated by a transfer function to limit the model parameters in a reliable range. The matrix inversion is accomplished by a preconditioned conjugate gradient method. With the above algorithm, equivalent density vectors can be obtained, and interpolation is performed to get the finally density model on the fine mesh in the model domain. Testing on synthetic gravity data demonstrated that the proposed method is faster than conventional generalized inversion algorithm to produce an acceptable solution for gravity inversion problem. The new developed inversion method was also applied for inversion of the gravity data collected over Sichuan basin, southwest China. The established density structure in this study helps understanding the crustal structure of Sichuan basin and provides reference for further oil and gas exploration in this area.

Accounting for epistatic interactions improves the functional analysis of protein structures

PubMed Central

Wilkins, Angela D.; Venner, Eric; Marciano, David C.; Erdin, Serkan; Atri, Benu; Lua, Rhonald C.; Lichtarge, Olivier

2013-01-01

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. Contact: lichtarge@bcm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24021383

Validation of experimental molecular crystal structures with dispersion-corrected density functional theory calculations.

PubMed

van de Streek, Jacco; Neumann, Marcus A

2010-10-01

This paper describes the validation of a dispersion-corrected density functional theory (d-DFT) method for the purpose of assessing the correctness of experimental organic crystal structures and enhancing the information content of purely experimental data. 241 experimental organic crystal structures from the August 2008 issue of Acta Cryst. Section E were energy-minimized in full, including unit-cell parameters. The differences between the experimental and the minimized crystal structures were subjected to statistical analysis. The r.m.s. Cartesian displacement excluding H atoms upon energy minimization with flexible unit-cell parameters is selected as a pertinent indicator of the correctness of a crystal structure. All 241 experimental crystal structures are reproduced very well: the average r.m.s. Cartesian displacement for the 241 crystal structures, including 16 disordered structures, is only 0.095 Å (0.084 Å for the 225 ordered structures). R.m.s. Cartesian displacements above 0.25 A either indicate incorrect experimental crystal structures or reveal interesting structural features such as exceptionally large temperature effects, incorrectly modelled disorder or symmetry breaking H atoms. After validation, the method is applied to nine examples that are known to be ambiguous or subtly incorrect.

A generalized modal shock spectra method for spacecraft loads analysis. [internal loads in a spacecraft structure subjected to a dynamic launch environment

NASA Technical Reports Server (NTRS)

Trubert, M.; Salama, M.

1979-01-01

Unlike an earlier shock spectra approach, generalization permits an accurate elastic interaction between the spacecraft and launch vehicle to obtain accurate bounds on the spacecraft response and structural loads. In addition, the modal response from a previous launch vehicle transient analysis with or without a dummy spacecraft - is exploited to define a modal impulse as a simple idealization of the actual forcing function. The idealized modal forcing function is then used to derive explicit expressions for an estimate of the bound on the spacecraft structural response and forces. Greater accuracy is achieved with the present method over the earlier shock spectra, while saving much computational effort over the transient analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verma, U. P.; Nayak, V.

Quantum mechanical first principle calculations have been performed to study the electronic and structural properties of TiN and TiAs in zinc blende (ZB) and rock salt (RS) structures. The full-potential linearized augmented plane wave (FP-LAPW) method has been used within the framework of density functional theory (DFT). The exchange correlation functional has been solved employing generalized gradient approximation (GGA). Our predicted results for lattice constants are in good agreement with the earlier findings. The electronic band structures of TiX are metallic in both the phases.

Implementation of density functional theory method on object-oriented programming (C++) to calculate energy band structure using the projector augmented wave (PAW)

NASA Astrophysics Data System (ADS)

Alfianto, E.; Rusydi, F.; Aisyah, N. D.; Fadilla, R. N.; Dipojono, H. K.; Martoprawiro, M. A.

2017-05-01

This study implemented DFT method into the C++ programming language with object-oriented programming rules (expressive software). The use of expressive software results in getting a simple programming structure, which is similar to mathematical formula. This will facilitate the scientific community to develop the software. We validate our software by calculating the energy band structure of Silica, Carbon, and Germanium with FCC structure using the Projector Augmented Wave (PAW) method then compare the results to Quantum Espresso calculation’s results. This study shows that the accuracy of the software is 85% compared to Quantum Espresso.

Computing and visualizing time-varying merge trees for high-dimensional data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oesterling, Patrick; Heine, Christian; Weber, Gunther H.

2017-06-03

We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

Spatial Control of Functional Response in 4D-Printed Active Metallic Structures

NASA Astrophysics Data System (ADS)

Ma, Ji; Franco, Brian; Tapia, Gustavo; Karayagiz, Kubra; Johnson, Luke; Liu, Jun; Arroyave, Raymundo; Karaman, Ibrahim; Elwany, Alaa

2017-04-01

We demonstrate a method to achieve local control of 3-dimensional thermal history in a metallic alloy, which resulted in designed spatial variations in its functional response. A nickel-titanium shape memory alloy part was created with multiple shape-recovery stages activated at different temperatures using the selective laser melting technique. The multi-stage transformation originates from differences in thermal history, and thus the precipitate structure, at various locations created from controlled variations in the hatch distance within the same part. This is a first example of precision location-dependent control of thermal history in alloys beyond the surface, and utilizes additive manufacturing techniques as a tool to create materials with novel functional response that is difficult to achieve through conventional methods.

Automated 3D structure composition for large RNAs

PubMed Central

Popenda, Mariusz; Szachniuk, Marta; Antczak, Maciej; Purzycka, Katarzyna J.; Lukasiak, Piotr; Bartol, Natalia; Blazewicz, Jacek; Adamiak, Ryszard W.

2012-01-01

Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues. PMID:22539264

Function Invariant and Parameter Scale-Free Transformation Methods

ERIC Educational Resources Information Center

Bentler, P. M.; Wingard, Joseph A.

1977-01-01

A scale-invariant simple structure function of previously studied function components for principal component analysis and factor analysis is defined. First and second partial derivatives are obtained, and Newton-Raphson iterations are utilized. The resulting solutions are locally optimal and subjectively pleasing. (Author/JKS)

Design and Structure-Function Characterization of 3D Printed Synthetic Porous Biomaterials for Tissue Engineering.

PubMed

Kelly, Cambre N; Miller, Andrew T; Hollister, Scott J; Guldberg, Robert E; Gall, Ken

2018-04-01

3D printing is now adopted for use in a variety of industries and functions. In biomedical engineering, 3D printing has prevailed over more traditional manufacturing methods in tissue engineering due to its high degree of control over both macro- and microarchitecture of porous tissue scaffolds. However, with the improved flexibility in design come new challenges in characterizing the structure-function relationships between various architectures and both mechanical and biological properties in an assortment of clinical applications. Presently, the field of tissue engineering lacks a comprehensive body of literature that is capable of drawing meaningful relationships between the designed structure and resulting function of 3D printed porous biomaterial scaffolds. This work first discusses the role of design on 3D printed porous scaffold function and then reviews characterization of these structure-function relationships for 3D printed synthetic metallic, polymeric, and ceramic biomaterials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A topological hierarchy for functions on triangulated surfaces.

PubMed

Bremer, Peer-Timo; Edelsbrunner, Herbert; Hamann, Bernd; Pascucci, Valerio

2004-01-01

We combine topological and geometric methods to construct a multiresolution representation for a function over a two-dimensional domain. In a preprocessing stage, we create the Morse-Smale complex of the function and progressively simplify its topology by cancelling pairs of critical points. Based on a simple notion of dependency among these cancellations, we construct a hierarchical data structure supporting traversal and reconstruction operations similarly to traditional geometry-based representations. We use this data structure to extract topologically valid approximations that satisfy error bounds provided at runtime.

Polymers functionalized with bronsted acid groups

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Humbeck, Jeffrey; Long, Jeffrey R.; McDonald, Thomas M.

Porous aromatic framework polymers functionalized with Bronsted acid moieties are prepared by polymerization of a three-dimensional organic aryl or heteroaryl monomer and its copolymerization with a second aryl or heteroaryl monomer functionalized with one or more Bronsted acid moiety. The polymers are characterized by a stable three-dimensional structure, which, in exemplary embodiments, includes interpenetrating subunits within one or more domain of the bulk polymer structure. The polymers are of use in methods of adsorbing ammonia and amines and in devices and systems configured for this purpose.

Measurements of the Temperature Structure-Function Parameters with a Small Unmanned Aerial System Compared with a Sodar

NASA Astrophysics Data System (ADS)

Bonin, Timothy A.; Goines, David C.; Scott, Aaron K.; Wainwright, Charlotte E.; Gibbs, Jeremy A.; Chilson, Phillip B.

2015-06-01

The structure function is often used to quantify the intensity of spatial inhomogeneities within turbulent flows. Here, the Small Multifunction Research and Teaching Sonde (SMARTSonde), an unmanned aerial system, is used to measure horizontal variations in temperature and to calculate the structure function of temperature at various heights for a range of separation distances. A method for correcting for the advection of turbulence in the calculation of the structure function is discussed. This advection correction improves the data quality, particularly when wind speeds are high. The temperature structure-function parameter can be calculated from the structure function of temperature. Two case studies from which the SMARTSonde was able to take measurements used to derive at several heights during multiple consecutive flights are discussed and compared with sodar measurements, from which is directly related to return power. Profiles of from both the sodar and SMARTSonde from an afternoon case exhibited generally good agreement. However, the profiles agreed poorly for a morning case. The discrepancies are partially attributed to different averaging times for the two instruments in a rapidly evolving environment, and the measurement errors associated with the SMARTSonde sampling within the stable boundary layer.

Computational mining for hypothetical patterns of amino acid side chains in protein data bank (PDB)

NASA Astrophysics Data System (ADS)

Ghani, Nur Syatila Ab; Firdaus-Raih, Mohd

2018-04-01

The three-dimensional structure of a protein can provide insights regarding its function. Functional relationship between proteins can be inferred from fold and sequence similarities. In certain cases, sequence or fold comparison fails to conclude homology between proteins with similar mechanism. Since the structure is more conserved than the sequence, a constellation of functional residues can be similarly arranged among proteins of similar mechanism. Local structural similarity searches are able to detect such constellation of amino acids among distinct proteins, which can be useful to annotate proteins of unknown function. Detection of such patterns of amino acids on a large scale can increase the repertoire of important 3D motifs since available known 3D motifs currently, could not compensate the ever-increasing numbers of uncharacterized proteins to be annotated. Here, a computational platform for an automated detection of 3D motifs is described. A fuzzy-pattern searching algorithm derived from IMagine an Amino Acid 3D Arrangement search EnGINE (IMAAAGINE) was implemented to develop an automated method for searching of hypothetical patterns of amino acid side chains in Protein Data Bank (PDB), without the need for prior knowledge on related sequence or structure of pattern of interest. We present an example of the searches, which is the detection of a hypothetical pattern derived from known structural motif of C2H2 structural pattern from zinc fingers. The conservation of particular patterns of amino acid side chains in unrelated proteins is highlighted. This approach can act as a complementary method for available structure- and sequence-based platforms and may contribute in improving functional association between proteins.

Normal response function method for mass and stiffness matrix updating using complex FRFs

NASA Astrophysics Data System (ADS)

Pradhan, S.; Modak, S. V.

2012-10-01

Quite often a structural dynamic finite element model is required to be updated so as to accurately predict the dynamic characteristics like natural frequencies and the mode shapes. Since in many situations undamped natural frequencies and mode shapes need to be predicted, it has generally been the practice in these situations to seek updating of only mass and stiffness matrix so as to obtain a reliable prediction model. Updating using frequency response functions (FRFs) has been one of the widely used approaches for updating, including updating of mass and stiffness matrices. However, the problem with FRF based methods, for updating mass and stiffness matrices, is that these methods are based on use of complex FRFs. Use of complex FRFs to update mass and stiffness matrices is not theoretically correct as complex FRFs are not only affected by these two matrices but also by the damping matrix. Therefore, in situations where updating of only mass and stiffness matrices using FRFs is required, the use of complex FRFs based updating formulation is not fully justified and would lead to inaccurate updated models. This paper addresses this difficulty and proposes an improved FRF based finite element model updating procedure using the concept of normal FRFs. The proposed method is a modified version of the existing response function method that is based on the complex FRFs. The effectiveness of the proposed method is validated through a numerical study of a simple but representative beam structure. The effect of coordinate incompleteness and robustness of method under presence of noise is investigated. The results of updating obtained by the improved method are compared with the existing response function method. The performance of the two approaches is compared for cases of light, medium and heavily damped structures. It is found that the proposed improved method is effective in updating of mass and stiffness matrices in all the cases of complete and incomplete data and with all levels and types of damping.

Reductive chemical release of N-glycans as 1-amino-alditols and subsequent 9-fluorenylmethyloxycarbonyl labeling for MS and LC/MS analysis.

PubMed

Wang, Chengjian; Qiang, Shan; Jin, Wanjun; Song, Xuezheng; Zhang, Ying; Huang, Linjuan; Wang, Zhongfu

2018-06-06

Glycoproteins play pivotal roles in a series of biological processes and their glycosylation patterns need to be structurally and functionally characterized. However, the lack of versatile methods to release N-glycans as functionalized forms has been undermining glycomics studies. Here a novel method is developed for dissociation of N-linked glycans from glycoproteins for analysis by MS and online LC/MS. This new method employs aqueous ammonia solution containing NaBH 3 CN as the reaction medium to release glycans from glycoproteins as 1-amino-alditol forms. The released glycans are conveniently labeled with 9-fluorenylmethyloxycarbonyl (Fmoc) and analyzed by ESI-MS and online LC/MS. Using the method, the neutral and acidic N-glycans were successfully released without peeling degradation of the core α-1,3-fucosylated structure or detectable de-N-acetylation, revealing its general applicability to various types of N-glycans. The Fmoc-derivatized N-glycans derived from chicken ovalbumin, Fagopyrum esculentum Moench Pollen and FBS were successfully analyzed by online LC/MS to distinguish isomers. The 1-amino-alditols were also permethylated to form quaternary ammonium cations at the reducing end, which enhance the MS sensitivity and are compatible with sequential multi-stage mass spectrometry (MS n ) fragmentation for glycan sequencing. The Fmoc-labeled N-glycans were further permethylated to produce methylated carbamates for determination of branches and linkages by sequential MS n fragmentation. N-Glycosylation represents one of the most common post-translational modification forms and plays pivotal roles in the structural and functional regulation of proteins in various biological activities, relating closely to human health and diseases. As a type of informational molecule, the N-glycans of glycoproteins participate directly in the molecular interactions between glycan epitopes and their corresponding protein receptors. Detailed structural and functional characterization of different types of N-glycans is essential for understanding the functional mechanisms of many biological activities and the pathologies of many diseases. Here we describe a simple, versatile method to indistinguishably release all types of N-glycans as functionalized forms without remarkable side reactions, enabling convenient, rapid analysis and preparation of released N-glycans from various complex biological samples. It is very valuable for studies on the complicated structure-function relationship of N-glycans, as well as for the search of N-glycan biomarkers of some major diseases and N-glycan related targets of some drugs. Copyright © 2018. Published by Elsevier B.V.

The application of the mesh-free method in the numerical simulations of the higher-order continuum structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yuzhou, E-mail: yuzhousun@126.com; Chen, Gensheng; Li, Dongxia

2016-06-08

This paper attempts to study the application of mesh-free method in the numerical simulations of the higher-order continuum structures. A high-order bending beam considers the effect of the third-order derivative of deflections, and can be viewed as a one-dimensional higher-order continuum structure. The moving least-squares method is used to construct the shape function with the high-order continuum property, the curvature and the third-order derivative of deflections are directly interpolated with nodal variables and the second- and third-order derivative of the shape function, and the mesh-free computational scheme is establish for beams. The coupled stress theory is introduced to describe themore » special constitutive response of the layered rock mass in which the bending effect of thin layer is considered. The strain and the curvature are directly interpolated with the nodal variables, and the mesh-free method is established for the layered rock mass. The good computational efficiency is achieved based on the developed mesh-free method, and some key issues are discussed.« less

Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM.

PubMed

Tuncbag, Nurcan; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2011-08-11

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank-formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.

Structure and Electronic Properties of Neutral and Negatively Charged RhBn Clusters (n = 3-10): A Density Functional Theory Study.

PubMed

Li, Peifang; Mei, Tingting; Lv, Linxia; Lu, Cheng; Wang, Weihua; Bao, Gang; Gutsev, Gennady L

2017-08-31

The geometrical structure and electronic properties of the neutral RhB n and singly negatively charged RhB n - clusters are obtained in the range of 3 ≤ n ≤ 10 using the unbiased CALYPSO structure search method and density functional theory (DFT). A combination of the PBE0 functional and the def2-TZVP basis set is used for determining global minima on potential energy surfaces of the Rh-doped B n clusters. The photoelectron spectra of the anions are simulated using the time-dependent density functional theory (TD-DFT) method. Good agreement between our simulated and experimentally obtained photoelectron spectra for RhB 9 - provides support to the validity of our theoretical method. The relative stabilities of the ground-state RhB n and RhB n - clusters are estimated using the calculated binding energies, second-order total energy differences, and HOMO-LUMO gaps. It is found that RhB 7 and RhB 8 - are the most stable species in the neutral and anionic series, respectively. The chemical bonding analysis reveals that the RhB 8 - cluster possesses two sets of delocalized σ and π bonds. In both cases, the Hückel 4N + 2 rule is fulfilled and this cluster possesses both σ and π aromaticities.

Mathematical modelling of the growth of human fetus anatomical structures.

PubMed

Dudek, Krzysztof; Kędzia, Wojciech; Kędzia, Emilia; Kędzia, Alicja; Derkowski, Wojciech

2017-09-01

The goal of this study was to present a procedure that would enable mathematical analysis of the increase of linear sizes of human anatomical structures, estimate mathematical model parameters and evaluate their adequacy. Section material consisted of 67 foetuses-rectus abdominis muscle and 75 foetuses- biceps femoris muscle. The following methods were incorporated to the study: preparation and anthropologic methods, image digital acquisition, Image J computer system measurements and statistical analysis method. We used an anthropologic method based on age determination with the use of crown-rump length-CRL (V-TUB) by Scammon and Calkins. The choice of mathematical function should be based on a real course of the curve presenting growth of anatomical structure linear size Ύ in subsequent weeks t of pregnancy. Size changes can be described with a segmental-linear model or one-function model with accuracy adequate enough for clinical purposes. The interdependence of size-age is described with many functions. However, the following functions are most often considered: linear, polynomial, spline, logarithmic, power, exponential, power-exponential, log-logistic I and II, Gompertz's I and II and von Bertalanffy's function. With the use of the procedures described above, mathematical models parameters were assessed for V-PL (the total length of body) and CRL body length increases, rectus abdominis total length h, its segments hI, hII, hIII, hIV, as well as biceps femoris length and width of long head (LHL and LHW) and of short head (SHL and SHW). The best adjustments to measurement results were observed in the exponential and Gompertz's models.

Multiscale Persistent Functions for Biomolecular Structure Characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Kelin; Li, Zhiming; Mu, Lin

Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolutionmore » parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first time, to describe the “regularity” of protein structures. Basically, a protein structure is deemed as regular if it has a consistent and orderly configuration. Our PSI model is tested on a database of 110 proteins; we find that structures with larger portions of loops and intrinsically disorder regions are always associated with larger PSI, meaning an irregular configuration, while proteins with larger portions of secondary structures, i.e., alpha-helix or beta-sheet, have smaller PSI. Essentially, PSI can be used to describe the “regularity” information in any systems.« less

3D bioprinting of structural proteins.

PubMed

Włodarczyk-Biegun, Małgorzata K; Del Campo, Aránzazu

2017-07-01

3D bioprinting is a booming method to obtain scaffolds of different materials with predesigned and customized morphologies and geometries. In this review we focus on the experimental strategies and recent achievements in the bioprinting of major structural proteins (collagen, silk, fibrin), as a particularly interesting technology to reconstruct the biochemical and biophysical composition and hierarchical morphology of natural scaffolds. The flexibility in molecular design offered by structural proteins, combined with the flexibility in mixing, deposition, and mechanical processing inherent to bioprinting technologies, enables the fabrication of highly functional scaffolds and tissue mimics with a degree of complexity and organization which has only just started to be explored. Here we describe the printing parameters and physical (mechanical) properties of bioinks based on structural proteins, including the biological function of the printed scaffolds. We describe applied printing techniques and cross-linking methods, highlighting the modifications implemented to improve scaffold properties. The used cell types, cell viability, and possible construct applications are also reported. We envision that the application of printing technologies to structural proteins will enable unprecedented control over their supramolecular organization, conferring printed scaffolds biological properties and functions close to natural systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Searching molecular structure databases with tandem mass spectra using CSI:FingerID

PubMed Central

Dührkop, Kai; Shen, Huibin; Meusel, Marvin; Rousu, Juho; Böcker, Sebastian

2015-01-01

Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin. PMID:26392543

Characterization of SWNT based Polystyrene Nanocomposites

NASA Astrophysics Data System (ADS)

Mitchell, Cynthia; Bahr, Jeffrey; Tour, James; Arepalli, Sivaram; Krishnamoorti, Ramanan

2003-03-01

Polystyrene nanocomposites with functionalized single walled carbon nanotubes (SWNTs), prepared by the in-situ generation and addition of organic diazonium compounds, were characterized using a range of structural and dynamic methods. These were contrasted to the properties of polystyrene composites prepared with unfunctionalized SWNTs at the same loadings. The functionalized nanocomposites demonstrated a percolated SWNT network structure at concentrations of 1 vol SWNT based composites at similar loadings of SWNT exhibited behavior comparable to that of the unfilled polymer. This formation of the SWNT network structure is because of the improved compatibility between the SWNTs and the polymer matrix due to the functionalization. Further structural evidence for the compatibility of the modified SWNTs and the polymer matrix will be discussed in the presentation.

Exploring the boundary between aromatic and olefinic character: Bad news for second-order perturbation theory and density functional schemes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sulzbach, H.M.; Schaefer, H.F. III; Klopper, W.

1996-04-10

The question whether [10]annulene prefers olefinic structures with alternate single and double bonds or aromatic structures like all other small to medium sized uncharged (4n + 2){pi} electron homologs (e.g. benzene, [14]annulene) has been controversial for more than 20 years. Our new results suggest that only the high-order correlated methods will be able to correctly predict the [10]annulene potential energy surface. The UNO-CAS results and the strong oscillation of the MP series show that nondynamical electron correlation is important. Consequently, reliable results can only be expected at the highest correlated levels like CCSD(T) method, which predicts the olefinic twist structuremore » to be lower in energy by 3-7 kcal/mol. This prediction that the twist structure is lower in energy is supported by (a) the MP2-R12 method, which shows that large basis sets favor the olefinic structure relative to the aromatic, and (b) the fact that both structures are about equally affected by nondynamical electron correlation. We conclude that [10]annulene is a system which cannot be described adequately by either second-order Moller-Plesset perturbation theory or density functional methods. 13 refs., 3 tabs.« less

Structural and Functional Phenotyping of the Failing Heart: Is the Left Ventricular Ejection Fraction Obsolete?

PubMed

Bristow, Michael R; Kao, David P; Breathett, Khadijah K; Altman, Natasha L; Gorcsan, John; Gill, Edward A; Lowes, Brian D; Gilbert, Edward M; Quaife, Robert A; Mann, Douglas L

2017-11-01

Diagnosis, prognosis, treatment, and development of new therapies for diseases or syndromes depend on a reliable means of identifying phenotypes associated with distinct predictive probabilities for these various objectives. Left ventricular ejection fraction (LVEF) provides the current basis for combined functional and structural phenotyping in heart failure by classifying patients as those with heart failure with reduced ejection fraction (HFrEF) and those with heart failure with preserved ejection fraction (HFpEF). Recently the utility of LVEF as the major phenotypic determinant of heart failure has been challenged based on its load dependency and measurement variability. We review the history of the development and adoption of LVEF as a critical measurement of LV function and structure and demonstrate that, in chronic heart failure, load dependency is not an important practical issue, and we provide hemodynamic and molecular biomarker evidence that LVEF is superior or equal to more unwieldy methods of identifying phenotypes of ventricular remodeling. We conclude that, because it reliably measures both left ventricular function and structure, LVEF remains the best current method of assessing pathologic remodeling in heart failure in both individual clinical and multicenter group settings. Because of the present and future importance of left ventricular phenotyping in heart failure, LVEF should be measured by using the most accurate technology and methodologic refinements available, and improved characterization methods should continue to be sought. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Effects of nitrogenous substituent groups on the benzene dication

NASA Astrophysics Data System (ADS)

Forgy, C. C.; Schlimgen, A. W.; Mazziotti, D. A.

2018-05-01

The benzene dication possesses a pentagonal-pyramidal structure with a hexacoordinated carbon. In contrast, halogenated benzene dications retain a similar structure to their parent molecules. In this work, we report on theoretical studies of the structures of the dications of benzene with nitrogenous substituents. We find that the nitrobenzene dication favours a near ideal pentagonal-pyramidal structure, while the aniline dication favours a flat, hexagonal structure. Reduced-density-matrices methods give predictions in agreement with available ab initio calculations and experiment. These results are also compared with those from the Hartree-Fock method and density functional theory.

Maximum entropy formalism for the analytic continuation of matrix-valued Green's functions

NASA Astrophysics Data System (ADS)

Kraberger, Gernot J.; Triebl, Robert; Zingl, Manuel; Aichhorn, Markus

2017-10-01

We present a generalization of the maximum entropy method to the analytic continuation of matrix-valued Green's functions. To treat off-diagonal elements correctly based on Bayesian probability theory, the entropy term has to be extended for spectral functions that are possibly negative in some frequency ranges. In that way, all matrix elements of the Green's function matrix can be analytically continued; we introduce a computationally cheap element-wise method for this purpose. However, this method cannot ensure important constraints on the mathematical properties of the resulting spectral functions, namely positive semidefiniteness and Hermiticity. To improve on this, we present a full matrix formalism, where all matrix elements are treated simultaneously. We show the capabilities of these methods using insulating and metallic dynamical mean-field theory (DMFT) Green's functions as test cases. Finally, we apply the methods to realistic material calculations for LaTiO3, where off-diagonal matrix elements in the Green's function appear due to the distorted crystal structure.

NoFold: RNA structure clustering without folding or alignment.

PubMed

Middleton, Sarah A; Kim, Junhyong

2014-11-01

Structures that recur across multiple different transcripts, called structure motifs, often perform a similar function-for example, recruiting a specific RNA-binding protein that then regulates translation, splicing, or subcellular localization. Identifying common motifs between coregulated transcripts may therefore yield significant insight into their binding partners and mechanism of regulation. However, as most methods for clustering structures are based on folding individual sequences or doing many pairwise alignments, this results in a tradeoff between speed and accuracy that can be problematic for large-scale data sets. Here we describe a novel method for comparing and characterizing RNA secondary structures that does not require folding or pairwise alignment of the input sequences. Our method uses the idea of constructing a distance function between two objects by their respective distances to a collection of empirical examples or models, which in our case consists of 1973 Rfam family covariance models. Using this as a basis for measuring structural similarity, we developed a clustering pipeline called NoFold to automatically identify and annotate structure motifs within large sequence data sets. We demonstrate that NoFold can simultaneously identify multiple structure motifs with an average sensitivity of 0.80 and precision of 0.98 and generally exceeds the performance of existing methods. We also perform a cross-validation analysis of the entire set of Rfam families, achieving an average sensitivity of 0.57. We apply NoFold to identify motifs enriched in dendritically localized transcripts and report 213 enriched motifs, including both known and novel structures. © 2014 Middleton and Kim; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Building Quakes: Detection of Weld Fractures in Buildings using High-Frequency Seismic Techniques

NASA Astrophysics Data System (ADS)

Heckman, V.; Kohler, M. D.; Heaton, T. H.

2009-12-01

Catastrophic fracture of welded beam-column connections in buildings was observed in the Northridge and Kobe earthquakes. Despite the structural importance of such connections, it can be difficult to locate damage in structural members underneath superficial building features. We have developed a novel technique to locate fracturing welds in buildings in real time using high-frequency information from seismograms. Numerical and experimental methods were used to investigate an approach for detecting the brittle fracture of welds of beam-column connections in instrumented steel moment-frame buildings through the use of time-reversed Green’s functions and wave propagation reciprocity. The approach makes use of a prerecorded catalogue of Green’s functions for an instrumented building to detect high-frequency failure events in the building during a later earthquake by screening continuous data for the presence of one or more of the events. This was explored experimentally by comparing structural responses of a small-scale laboratory structure under a variety of loading conditions. Experimentation was conducted on a polyvinyl chloride frame model structure with data recorded at a sample rate of 2000 Hz using piezoelectric accelerometers and a 24-bit digitizer. Green’s functions were obtained by applying impulsive force loads at various locations along the structure with a rubber-tipped force transducer hammer. We performed a blind test using cross-correlation techniques to determine if it was possible to use the catalogue of Green’s functions to pinpoint the absolute times and locations of subsequent, induced failure events in the structure. A finite-element method was used to simulate the response of the model structure to various source mechanisms in order to determine the types of elastic waves that were produced as well as to obtain a general understanding of the structural response to localized loading and fracture.

Determination of the structural properties of the aqueous electrolyte LiCl6H 2 O at the supercooled state using the Reverse Monte Carlo (RMC) simulation

NASA Astrophysics Data System (ADS)

ZIANE, M.; HABCHI, M.; DEROUICHE, A.; MESLI, S. M.; BENZOUINE, F.; KOTBI, M.

2017-03-01

A structural study of an aqueous electrolyte whose experimental results are available. It is a solution of A structural study of an aqueous electrolyte whose experimental results are available. It is a solution LiCl6H 2 O type at supercooled state (162K) contrasted with pure water at room temperature by means of Partial Distribution Functions (PDF) issue from neutron scattering technique. The aqueous electrolyte solution of the chloride lithium LiCl presents interesting properties which is studied by different methods at different concentration and thermodynamical states: This system possesses the property to become a glass through a metastable supercooled state when the temperature decreases. Based on these partial functions, the Reverse Monte Carlo method (RMC) computes radial correlation functions which allow exploring a number of structural features of the system. The purpose of the RMC is to produce a consistent configuration with the experimental data. They are usually the most important in the limit of systematic errors (of unknown distribution).

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

On the importance of cotranscriptional RNA structure formation

PubMed Central

Lai, Daniel; Proctor, Jeff R.; Meyer, Irmtraud M.

2013-01-01

The expression of genes, both coding and noncoding, can be significantly influenced by RNA structural features of their corresponding transcripts. There is by now mounting experimental and some theoretical evidence that structure formation in vivo starts during transcription and that this cotranscriptional folding determines the functional RNA structural features that are being formed. Several decades of research in bioinformatics have resulted in a wide range of computational methods for predicting RNA secondary structures. Almost all state-of-the-art methods in terms of prediction accuracy, however, completely ignore the process of structure formation and focus exclusively on the final RNA structure. This review hopes to bridge this gap. We summarize the existing evidence for cotranscriptional folding and then review the different, currently used strategies for RNA secondary-structure prediction. Finally, we propose a range of ideas on how state-of-the-art methods could be potentially improved by explicitly capturing the process of cotranscriptional structure formation. PMID:24131802

Probabilistic structural analysis methods of hot engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1989-01-01

Development of probabilistic structural analysis methods for hot engine structures at Lewis Research Center is presented. Three elements of the research program are: (1) composite load spectra methodology; (2) probabilistic structural analysis methodology; and (3) probabilistic structural analysis application. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) turbine blade temperature, pressure, and torque of the space shuttle main engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; and (3) evaluation of the failure probability. Collectively, the results demonstrate that the structural durability of hot engine structural components can be effectively evaluated in a formal probabilistic/reliability framework.

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

Brain Morphometry using MRI in Schizophrenia Patients

NASA Astrophysics Data System (ADS)

Abanshina, I.; Pirogov, Yu.; Kupriyanov, D.; Orlova, V.

2010-01-01

Schizophrenia has been the focus of intense neuroimaging research. Although its fundamental pathobiology remains elusive, neuroimaging studies provide evidence of abnormalities of cerebral structure and function in patients with schizophrenia. We used morphometry as a quantitative method for estimation of volume of brain structures. Seventy eight right-handed subjects aged 18-45 years were exposed to MRI-examination. Patients were divided into 3 groups: patients with schizophrenia, their relatives and healthy controls. The volumes of interested structures (caudate nucleus, putamen, ventricles, frontal and temporal lobe) were measured using T2-weighted MR-images. Correlations between structural differences and functional deficit were evaluated.

A novel knowledge-based potential for RNA 3D structure evaluation

NASA Astrophysics Data System (ADS)

Yang, Yi; Gu, Qi; Zhang, Ben-Gong; Shi, Ya-Zhou; Shao, Zhi-Gang

2018-03-01

Ribonucleic acids (RNAs) play a vital role in biology, and knowledge of their three-dimensional (3D) structure is required to understand their biological functions. Recently structural prediction methods have been developed to address this issue, but a series of RNA 3D structures are generally predicted by most existing methods. Therefore, the evaluation of the predicted structures is generally indispensable. Although several methods have been proposed to assess RNA 3D structures, the existing methods are not precise enough. In this work, a new all-atom knowledge-based potential is developed for more accurately evaluating RNA 3D structures. The potential not only includes local and nonlocal interactions but also fully considers the specificity of each RNA by introducing a retraining mechanism. Based on extensive test sets generated from independent methods, the proposed potential correctly distinguished the native state and ranked near-native conformations to effectively select the best. Furthermore, the proposed potential precisely captured RNA structural features such as base-stacking and base-pairing. Comparisons with existing potential methods show that the proposed potential is very reliable and accurate in RNA 3D structure evaluation. Project supported by the National Science Foundation of China (Grants Nos. 11605125, 11105054, 11274124, and 11401448).

Computer-Aided Design of RNA Origami Structures.

PubMed

Sparvath, Steffen L; Geary, Cody W; Andersen, Ebbe S

2017-01-01

RNA nanostructures can be used as scaffolds to organize, combine, and control molecular functionalities, with great potential for applications in nanomedicine and synthetic biology. The single-stranded RNA origami method allows RNA nanostructures to be folded as they are transcribed by the RNA polymerase. RNA origami structures provide a stable framework that can be decorated with functional RNA elements such as riboswitches, ribozymes, interaction sites, and aptamers for binding small molecules or protein targets. The rich library of RNA structural and functional elements combined with the possibility to attach proteins through aptamer-based binding creates virtually limitless possibilities for constructing advanced RNA-based nanodevices.In this chapter we provide a detailed protocol for the single-stranded RNA origami design method using a simple 2-helix tall structure as an example. The first step involves 3D modeling of a double-crossover between two RNA double helices, followed by decoration with tertiary motifs. The second step deals with the construction of a 2D blueprint describing the secondary structure and sequence constraints that serves as the input for computer programs. In the third step, computer programs are used to design RNA sequences that are compatible with the structure, and the resulting outputs are evaluated and converted into DNA sequences to order.

Contact resistance extraction methods for short- and long-channel carbon nanotube field-effect transistors

NASA Astrophysics Data System (ADS)

Pacheco-Sanchez, Anibal; Claus, Martin; Mothes, Sven; Schröter, Michael

2016-11-01

Three different methods for the extraction of the contact resistance based on both the well-known transfer length method (TLM) and two variants of the Y-function method have been applied to simulation and experimental data of short- and long-channel CNTFETs. While for TLM special CNT test structures are mandatory, standard electrical device characteristics are sufficient for the Y-function methods. The methods have been applied to CNTFETs with low and high channel resistance. It turned out that the standard Y-function method fails to deliver the correct contact resistance in case of a relatively high channel resistance compared to the contact resistances. A physics-based validation is also given for the application of these methods based on applying traditional Si MOSFET theory to quasi-ballistic CNTFETs.

COREPA-M: NEW MULTI-DIMENSIONAL FUNCTIONALITY OF THE COREPA METHOD

EPA Science Inventory

The COmmon REactivity PAttern (COREPA) method is a recently developed pattern recognition technique accounting for conformational flexibility of chemicals in 3-D quantitative structure-activity relationships (QSARs). The method is based on the assumption that non-congeneric chemi...

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

On implementation of the extended interior penalty function. [optimum structural design

NASA Technical Reports Server (NTRS)

Cassis, J. H.; Schmit, L. A., Jr.

1976-01-01

The extended interior penalty function formulation is implemented. A rational method for determining the transition between the interior and extended parts is set forth. The formulation includes a straightforward method for avoiding design points with some negative components, which are physically meaningless in structural analysis. The technique, when extended to problems involving parametric constraints, can facilitate closed form integration of the penalty terms over the most important parts of the parameter interval. The method lends itself well to the use of approximation concepts, such as design variable linking, constraint deletion and Taylor series expansions of response quantities in terms of design variables. Examples demonstrating the algorithm, in the context of planar orthogonal frames subjected to ground motion, are included.

1-Pentyl-3-(4-methoxy-1-naphthoyl)indole and 2-(2-methoxy-phenyl)-1-(1-pentyl-1 H-indol-3-yl)-ethanone: X-ray structures and computational studies

NASA Astrophysics Data System (ADS)

Nycz, Jacek E.; Malecki, Grzegorz; Zawiazalec, Marcin; Pazdziorek, Tadeusz; Skop, Patrycja

2010-12-01

1-Pentyl-3-(4-methoxy-1-naphthoyl)indole (shortly named JWH-081) ( 1) and 2-(2-methoxy-phenyl)-1-(1-pentyl-1 H-indol-3-yl)-ethanone (shortly named JWH-250) ( 2), are examples of cannabinoids which were characterized by FTIR, UV-Vis, multinuclear NMR spectroscopy and single crystal X-ray diffraction method. The geometries of the studied compounds were optimized in singlet states using the density functional theory (DFT) method with B3LYP functional. Electronic spectra were calculated by TDDFT method. In general, the predicted bond lengths and angles are in a good agreement with the values based on the X-ray crystal structure data.

Structure prediction of the second extracellular loop in G-protein-coupled receptors.

PubMed

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-06-03

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

A thermally driven differential mutation approach for the structural optimization of large atomic systems

NASA Astrophysics Data System (ADS)

Biswas, Katja

2017-09-01

A computational method is presented which is capable to obtain low lying energy structures of topological amorphous systems. The method merges a differential mutation genetic algorithm with simulated annealing. This is done by incorporating a thermal selection criterion, which makes it possible to reliably obtain low lying minima with just a small population size and is suitable for multimodal structural optimization. The method is tested on the structural optimization of amorphous graphene from unbiased atomic starting configurations. With just a population size of six systems, energetically very low structures are obtained. While each of the structures represents a distinctly different arrangement of the atoms, their properties, such as energy, distribution of rings, radial distribution function, coordination number, and distribution of bond angles, are very similar.

Structure of a peptide adsorbed on graphene and graphite.

PubMed

Katoch, Jyoti; Kim, Sang Nyon; Kuang, Zhifeng; Farmer, Barry L; Naik, Rajesh R; Tatulian, Suren A; Ishigami, Masa

2012-05-09

Noncovalent functionalization of graphene using peptides is a promising method for producing novel sensors with high sensitivity and selectivity. Here we perform atomic force microscopy, Raman spectroscopy, infrared spectroscopy, and molecular dynamics simulations to investigate peptide-binding behavior to graphene and graphite. We studied a dodecamer peptide identified with phage display to possess affinity for graphite. Optical spectroscopy reveals that the peptide forms secondary structures both in powder form and in an aqueous medium. The dominant structure in the powder form is α-helix, which undergoes a transition to a distorted helical structure in aqueous solution. The peptide forms a complex reticular structure upon adsorption on graphene and graphite, having a helical conformation different from α-helix due to its interaction with the surface. Our observation is consistent with our molecular dynamics calculations, and our study paves the way for rational functionalization of graphene using biomolecules with defined structures and, therefore, functionalities.

Is there a neuroanatomical basis of the vulnerability to suicidal behavior? A coordinate-based meta-analysis of structural and functional MRI studies

PubMed Central

van Heeringen, Kees; Bijttebier, Stijn; Desmyter, Stefanie; Vervaet, Myriam; Baeken, Chris

2014-01-01

Objective: We conducted meta-analyses of functional and structural neuroimaging studies comparing adolescent and adult individuals with a history of suicidal behavior and a psychiatric disorder to psychiatric controls in order to objectify changes in brain structure and function in association with a vulnerability to suicidal behavior. Methods: Magnetic resonance imaging studies published up to July 2013 investigating structural or functional brain correlates of suicidal behavior were identified through computerized and manual literature searches. Activation foci from 12 studies encompassing 475 individuals, i.e., 213 suicide attempters and 262 psychiatric controls were subjected to meta-analytical study using anatomic or activation likelihood estimation (ALE). Result: Activation likelihood estimation revealed structural deficits and functional changes in association with a history of suicidal behavior. Structural findings included reduced volumes of the rectal gyrus, superior temporal gyrus and caudate nucleus. Functional differences between study groups included an increased reactivity of the anterior and posterior cingulate cortices. Discussion: A history of suicidal behavior appears to be associated with (probably interrelated) structural deficits and functional overactivation in brain areas, which contribute to a decision-making network. The findings suggest that a vulnerability to suicidal behavior can be defined in terms of a reduced motivational control over the intentional behavioral reaction to salient negative stimuli. PMID:25374525

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

De novo identification of highly diverged protein repeats by probabilistic consistency.

PubMed

Biegert, A; Söding, J

2008-03-15

An estimated 25% of all eukaryotic proteins contain repeats, which underlines the importance of duplication for evolving new protein functions. Internal repeats often correspond to structural or functional units in proteins. Methods capable of identifying diverged repeated segments or domains at the sequence level can therefore assist in predicting domain structures, inferring hypotheses about function and mechanism, and investigating the evolution of proteins from smaller fragments. We present HHrepID, a method for the de novo identification of repeats in protein sequences. It is able to detect the sequence signature of structural repeats in many proteins that have not yet been known to possess internal sequence symmetry, such as outer membrane beta-barrels. HHrepID uses HMM-HMM comparison to exploit evolutionary information in the form of multiple sequence alignments of homologs. In contrast to a previous method, the new method (1) generates a multiple alignment of repeats; (2) utilizes the transitive nature of homology through a novel merging procedure with fully probabilistic treatment of alignments; (3) improves alignment quality through an algorithm that maximizes the expected accuracy; (4) is able to identify different kinds of repeats within complex architectures by a probabilistic domain boundary detection method and (5) improves sensitivity through a new approach to assess statistical significance. Server: http://toolkit.tuebingen.mpg.de/hhrepid; Executables: ftp://ftp.tuebingen.mpg.de/pub/protevo/HHrepID

Greek classicism in living structure? Some deductive pathways in animal morphology.

PubMed

Zweers, G A

1985-01-01

Classical temples in ancient Greece show two deterministic illusionistic principles of architecture, which govern their functional design: geometric proportionalism and a set of illusion-strengthening rules in the proportionalism's "stochastic margin". Animal morphology, in its mechanistic-deductive revival, applies just one architectural principle, which is not always satisfactory. Whether a "Greek Classical" situation occurs in the architecture of living structure is to be investigated by extreme testing with deductive methods. Three deductive methods for explanation of living structure in animal morphology are proposed: the parts, the compromise, and the transformation deduction. The methods are based upon the systems concept for an organism, the flow chart for a functionalistic picture, and the network chart for a structuralistic picture, whereas the "optimal design" serves as the architectural principle for living structure. These methods show clearly the high explanatory power of deductive methods in morphology, but they also make one open end most explicit: neutral issues do exist. Full explanation of living structure asks for three entries: functional design within architectural and transformational constraints. The transformational constraint brings necessarily in a stochastic component: an at random variation being a sort of "free management space". This variation must be a variation from the deterministic principle of the optimal design, since any transformation requires space for plasticity in structure and action, and flexibility in role fulfilling. Nevertheless, finally the question comes up whether for animal structure a similar situation exists as in Greek Classical temples. This means that the at random variation, that is found when the optimal design is used to explain structure, comprises apart from a stochastic part also real deviations being yet another deterministic part. This deterministic part could be a set of rules that governs actualization in the "free management space".

Hybrid-DFT  +  V w method for band structure calculation of semiconducting transition metal compounds: the case of cerium dioxide.

PubMed

Ivády, Viktor; Gali, Adam; Abrikosov, Igor A

2017-11-15

Hybrid functionals' non-local exchange-correlation potential contains a derivative discontinuity that improves on standard semi-local density functional theory (DFT) band gaps. Moreover, by careful parameterization, hybrid functionals can provide self-interaction reduced description of selected states. On the other hand, the uniform description of all the electronic states of a given system is a known drawback of these functionals that causes varying accuracy in the description of states with different degrees of localization. This limitation can be remedied by the orbital dependent exact exchange extension of hybrid functionals; the hybrid-DFT  +  V w method (Ivády et al 2014 Phys. Rev. B 90 035146). Based on the analogy of quasi-particle equations and hybrid-DFT single particle equations, here we demonstrate that parameters of hybrid-DFT  +  V w functional can be determined from approximate theoretical quasi-particle spectra without any fitting to experiment. The proposed method is illustrated on the charge self-consistent electronic structure calculation for cerium dioxide where itinerant valence states interact with well-localized 4f atomic like states, making this system challenging for conventional methods, either hybrid-DFT or LDA  +  U, and therefore allowing for a demonstration of the advantages of the proposed scheme.

Streamline integration as a method for two-dimensional elliptic grid generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiesenberger, M., E-mail: Matthias.Wiesenberger@uibk.ac.at; Held, M.; Einkemmer, L.

We propose a new numerical algorithm to construct a structured numerical elliptic grid of a doubly connected domain. Our method is applicable to domains with boundaries defined by two contour lines of a two-dimensional function. Furthermore, we can adapt any analytically given boundary aligned structured grid, which specifically includes polar and Cartesian grids. The resulting coordinate lines are orthogonal to the boundary. Grid points as well as the elements of the Jacobian matrix can be computed efficiently and up to machine precision. In the simplest case we construct conformal grids, yet with the help of weight functions and monitor metricsmore » we can control the distribution of cells across the domain. Our algorithm is parallelizable and easy to implement with elementary numerical methods. We assess the quality of grids by considering both the distribution of cell sizes and the accuracy of the solution to elliptic problems. Among the tested grids these key properties are best fulfilled by the grid constructed with the monitor metric approach. - Graphical abstract: - Highlights: • Construct structured, elliptic numerical grids with elementary numerical methods. • Align coordinate lines with or make them orthogonal to the domain boundary. • Compute grid points and metric elements up to machine precision. • Control cell distribution by adaption functions or monitor metrics.« less

Identifying the stored energy of a hyperelastic structure by using an attenuated Landweber method

NASA Astrophysics Data System (ADS)

Seydel, Julia; Schuster, Thomas

2017-12-01

We consider the nonlinear inverse problem of identifying the stored energy function of a hyperelastic material from full knowledge of the displacement field as well as from surface sensor measurements. The displacement field is represented as a solution of Cauchy’s equation of motion, which is a nonlinear elastic wave equation. Hyperelasticity means that the first Piola-Kirchhoff stress tensor is given as the gradient of the stored energy function. We assume that a dictionary of suitable functions is available. The aim is to recover the stored energy with respect to this dictionary. The considered inverse problem is of vital interest for the development of structural health monitoring systems which are constructed to detect defects in elastic materials from boundary measurements of the displacement field, since the stored energy encodes the mechanical properties of the underlying structure. In this article we develop a numerical solver using the attenuated Landweber method. We show that the parameter-to-solution map satisfies the local tangential cone condition. This result can be used to prove local convergence of the attenuated Landweber method in the case that the full displacement field is measured. In our numerical experiments we demonstrate how to construct an appropriate dictionary and show that our method is well suited to localize damages in various situations.

Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition

PubMed Central

Saeed, Isaam; Tang, Sen-Lin; Halgamuge, Saman K.

2012-01-01

An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis. PMID:22180538

Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.

PubMed

Peng, Jiajie; Zhang, Xuanshuo; Hui, Weiwei; Lu, Junya; Li, Qianqian; Liu, Shuhui; Shang, Xuequn

2018-03-19

Gene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, most existing semantic similarity approaches rely only on GO annotations and structure, or incorporate only local interactions in the co-functional network. This may lead to inaccurate GO-based similarity resulting from the incomplete GO topology structure and gene annotations. We present NETSIM2, a new network-based method that allows researchers to measure GO-based gene functional similarities by considering the global structure of the co-functional network with a random walk with restart (RWR)-based method, and by selecting the significant term pairs to decrease the noise information. Based on the EC number (Enzyme Commission)-based groups of yeast and Arabidopsis, evaluation test shows that NETSIM2 can enhance the accuracy of Gene Ontology-based gene functional similarity. Using NETSIM2 as an example, we found that the accuracy of semantic similarities can be significantly improved after effectively incorporating the global gene-to-gene interactions in the co-functional network, especially on the species that gene annotations in GO are far from complete.

The Vertical Structure of Urban Soils and Their Convergence Across Cities

EPA Science Inventory

The theoretical patterns for vertical soil structure (e.g., A-B-C ordering of horizons) are a basis for research methods and our understanding of ecosystem structure and function in general. A general understanding of how urban soils differ from non-urban soils vertically is need...

Diagnostic approaches for diabetic cardiomyopathy and myocardial fibrosis

PubMed Central

Maya, Lisandro; Villarreal, Francisco J.

2009-01-01

In diabetes mellitus, alterations in cardiac structure/function in the absence of ischemic heart disease, hypertension or other cardiac pathologies is termed diabetic cardiomyopathy. In the United States, the prevalence of diabetes mellitus continues to rise and the disease currently affects about 8% of the general population. Hence, it is imperative the use of appropriate diagnostic strategies for diabetic cardiomyopathy, which may help correctly identify the disease at early stages and implement suitable corrective therapies. Currently, there is no single diagnostic method for the identification of diabetic cardiomyopathy. Diabetic cardiomyopathy is known to induce changes in cardiac structure such as, myocardial hypertrophy, fibrosis and fat droplet deposition. Early changes in cardiac function are typically manifested as abnormal diastolic function that with time leads to loss of contractile function. Echocardiography based methods currently stands as the preferred diagnostic approach for diabetic cardiomyopathy, due to its wide availability and economical use. In addition to conventional techniques, magnetic resonance imaging and spectroscopy along with contrast agents are now leading new approaches in the diagnosis of myocardial fibrosis, and cardiac and hepatic metabolic changes. These strategies can be complemented with serum biomarkers so they can offer a clear picture as to diabetes-induced changes in cardiac structure/function even at very early stages of the disease. This review article intends to provide a summary of experimental and routine tools currently available to diagnose diabetic cardiomyopathy induced changes in cardiac structure/function. These tools can be reliably used in either experimental models of diabetes or for clinical applications. PMID:19595694

Structural, electronic and optical properties of LiNbO3 using GGA-PBE and TB-mBJ functionals: A DFT study

NASA Astrophysics Data System (ADS)

Arshad Javid, M.; Khan, Zafar Ullah; Mehmood, Zahid; Nabi, Azeem; Hussain, Fayyaz; Imran, M.; Nadeem, Muhammad; Anjum, Naeem

2018-06-01

In the present work, first-principles calculations were performed to obtain the structural, electronic and optical properties of lithium niobate crystal using two exchange-correlation functionals (GGA-PBE and TB-mBJ). The calculated structural parameters were very close to the experimental values. TB-mBJ functional was found to be good when compared to LDA and GGA functionals in case of bandgap energy of 3.715 eV of lithium niobate. It was observed that the upper valence and lower conduction bands consist mainly the O-2p and Nb-4d states, respectively. Furthermore, calculations for real and imaginary parts of frequency-dependent dielectric function 𝜀(ω) of lithium niobate crystal were performed using TD-DFT method. The ordinary refractive index no(ω), extraordinary refractive index ne(ω), its birefringence and absorption peaks in imaginary dielectric function 𝜀2(ω) were also calculated.

Dynamic nuclear polarization methods in solids and solutions to explore membrane proteins and membrane systems.

PubMed

Cheng, Chi-Yuan; Han, Songi

2013-01-01

Membrane proteins regulate vital cellular processes, including signaling, ion transport, and vesicular trafficking. Obtaining experimental access to their structures, conformational fluctuations, orientations, locations, and hydration in membrane environments, as well as the lipid membrane properties, is critical to understanding their functions. Dynamic nuclear polarization (DNP) of frozen solids can dramatically boost the sensitivity of current solid-state nuclear magnetic resonance tools to enhance access to membrane protein structures in native membrane environments. Overhauser DNP in the solution state can map out the local and site-specific hydration dynamics landscape of membrane proteins and lipid membranes, critically complementing the structural and dynamics information obtained by electron paramagnetic resonance spectroscopy. Here, we provide an overview of how DNP methods in solids and solutions can significantly increase our understanding of membrane protein structures, dynamics, functions, and hydration in complex biological membrane environments.

First-principle study of structural, electronic and magnetic properties of (FeC)n (n = 1-8) and (FeC)8TM (TM = V, Cr, Mn and Co) clusters.

PubMed

Li, Cheng-Gang; Zhang, Jie; Zhang, Wu-Qin; Tang, Ya-Nan; Ren, Bao-Zeng; Hu, Yan-Fei

2017-12-13

The structural, electronic and magnetic properties of the (FeC) n (n = 1-8) clusters are studied using the unbiased CALYPSO structure search method and density functional theory. A combination of the PBE functional and 6-311 + G* basis set is used for determining global minima on potential energy surfaces of (FeC) n clusters. Relatively stabilities are analyzed via computing their binding energies, second order difference and HOMO-LUMO gaps. In addition, the origin of magnetic properties, spin density and density of states are discussed in detail, respectively. At last, based on the same computational method, the structures, magnetic properties and density of states are systemically investigated for the 3d (V, Cr, Mn and Co) atom doped (FeC) 8 cluster.

Bioelectrochemical Systems Workshop:Standardized Analyses, Design Benchmarks, and Reporting

DTIC Science & Technology

2012-01-01

related to the exoelectrogenic biofilm activity, and to investigate whether the community structure is a function of design and operational parameters...where should biofilm samples be collected? The most prevalent methods of community characterization in BES studies have entailed phylogenetic ...of function associated with this genetic marker, and in methods that involve polymerase chain reaction (PCR) amplification the quantitative

Improved protein model quality assessments by changing the target function.

PubMed

Uziela, Karolis; Menéndez Hurtado, David; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne

2018-06-01

Protein modeling quality is an important part of protein structure prediction. We have for more than a decade developed a set of methods for this problem. We have used various types of description of the protein and different machine learning methodologies. However, common to all these methods has been the target function used for training. The target function in ProQ describes the local quality of a residue in a protein model. In all versions of ProQ the target function has been the S-score. However, other quality estimation functions also exist, which can be divided into superposition- and contact-based methods. The superposition-based methods, such as S-score, are based on a rigid body superposition of a protein model and the native structure, while the contact-based methods compare the local environment of each residue. Here, we examine the effects of retraining our latest predictor, ProQ3D, using identical inputs but different target functions. We find that the contact-based methods are easier to predict and that predictors trained on these measures provide some advantages when it comes to identifying the best model. One possible reason for this is that contact based methods are better at estimating the quality of multi-domain targets. However, training on the S-score gives the best correlation with the GDT_TS score, which is commonly used in CASP to score the global model quality. To take the advantage of both of these features we provide an updated version of ProQ3D that predicts local and global model quality estimates based on different quality estimates. © 2018 Wiley Periodicals, Inc.

GIRAF: a method for fast search and flexible alignment of ligand binding interfaces in proteins at atomic resolution

PubMed Central

Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

Comparison and classification of protein structures are fundamental means to understand protein functions. Due to the computational difficulty and the ever-increasing amount of structural data, however, it is in general not feasible to perform exhaustive all-against-all structure comparisons necessary for comprehensive classifications. To efficiently handle such situations, we have previously proposed a method, now called GIRAF. We herein describe further improvements in the GIRAF protein structure search and alignment method. The GIRAF method achieves extremely efficient search of similar structures of ligand binding sites of proteins by exploiting database indexing of structural features of local coordinate frames. In addition, it produces refined atom-wise alignments by iterative applications of the Hungarian method to the bipartite graph defined for a pair of superimposed structures. By combining the refined alignments based on different local coordinate frames, it is made possible to align structures involving domain movements. We provide detailed accounts for the database design, the search and alignment algorithms as well as some benchmark results. PMID:27493524

Protein structure based prediction of catalytic residues

PubMed Central

2013-01-01

Background Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. Results We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. Conclusions We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases. PMID:23433045

Structural Analysis of PTM Hotspots (SAPH-ire)--A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families.

PubMed

Dewhurst, Henry M; Choudhury, Shilpa; Torres, Matthew P

2015-08-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)--a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits--conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit-N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

First Principles Study of Chemically Functionalized Graphene

NASA Astrophysics Data System (ADS)

Jha, Sanjiv; Vasiliev, Igor

2015-03-01

The electronic, structural and vibrational properties of carbon nanomaterials can be affected by chemical functionalization. We applied ab initio computational methods based on density functional theory to study the covalent functionalization of graphene with benzyne, carboxyl groups and tetracyanoethylene oxide (TCNEO). Our calculations were carried out using the SIESTA and Quantum-ESPRESSO electronic structure codes combined with the local density and generalized gradient approximations for the exchange correlation functional and norm-conserving Troullier-Martins pseudopotentials. The simulated Raman and infrared spectra of graphene functionalized with carboxyl groups and TCNEO were consistent with the available experimental results. The computed vibrational spectra of graphene functionalized with carboxyl groups showed that the presence of point defects near the functionalization site affects the Raman and infrared spectroscopic signatures of functionalized graphene. Supported by NSF CHE-1112388.

Introducing anisotropic Minkowski functionals and quantitative anisotropy measures for local structure analysis in biomedical imaging

NASA Astrophysics Data System (ADS)

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2013-03-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging

PubMed Central

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2017-01-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10−4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications. PMID:29170580

Critical Features of Fragment Libraries for Protein Structure Prediction

PubMed Central

dos Santos, Karina Baptista

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction. PMID:28085928

Critical Features of Fragment Libraries for Protein Structure Prediction.

PubMed

Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

Proposed method for determining the thickness of glass in solar collector panels

NASA Technical Reports Server (NTRS)

Moore, D. M.

1980-01-01

An analytical method was developed for determining the minimum thickness for simply supported, rectangular glass plates subjected to uniform normal pressure environmental loads such as wind, earthquake, snow, and deadweight. The method consists of comparing an analytical prediction of the stress in the glass panel to a glass breakage stress determined from fracture mechanics considerations. Based on extensive analysis using the nonlinear finite element structural analysis program ARGUS, design curves for the structural analysis of simply supported rectangular plates were developed. These curves yield the center deflection, center stress and corner stress as a function of a dimensionless parameter describing the load intensity. A method of estimating the glass breakage stress as a function of a specified failure rate, degree of glass temper, design life, load duration time, and panel size is also presented.

A complete active space valence bond method with nonorthogonal orbitals

NASA Astrophysics Data System (ADS)

Hirao, Kimihiko; Nakano, Haruyuki; Nakayama, Kenichi

1997-12-01

A complete active space self-consistent field (SCF) wave function is transformed into a valence bond type representation built from nonorthogonal orbitals, each strongly localized on a single atom. Nonorthogonal complete active space SCF orbitals are constructed by Ruedenberg's projected localization procedure so that they have maximal overlaps with the corresponding minimum basis set of atomic orbitals of the free-atoms. The valence bond structures which are composed of such nonorthogonal quasiatomic orbitals constitute the wave function closest to the concept of the oldest and most simple valence bond method. The method is applied to benzene, butadiene, hydrogen, and methane molecules and compared to the previously proposed complete active space valence bond approach with orthogonal orbitals. The results demonstrate the validity of the method as a powerful tool for describing the electronic structure of various molecules.

Experimental application of OMA solutions on the model of industrial structure

NASA Astrophysics Data System (ADS)

Mironov, A.; Mironovs, D.

2017-10-01

It is very important and sometimes even vital to maintain reliability of industrial structures. High quality control during production and structural health monitoring (SHM) in exploitation provides reliable functioning of large, massive and remote structures, like wind generators, pipelines, power line posts, etc. This paper introduces a complex of technological and methodical solutions for SHM and diagnostics of industrial structures, including those that are actuated by periodic forces. Solutions were verified on a wind generator scaled model with integrated system of piezo-film deformation sensors. Simultaneous and multi-patch Operational Modal Analysis (OMA) approaches were implemented as methodical means for structural diagnostics and monitoring. Specially designed data processing algorithms provide objective evaluation of structural state modification.

An efficient method for hybrid density functional calculation with spin-orbit coupling

NASA Astrophysics Data System (ADS)

Wang, Maoyuan; Liu, Gui-Bin; Guo, Hong; Yao, Yugui

2018-03-01

In first-principles calculations, hybrid functional is often used to improve accuracy from local exchange correlation functionals. A drawback is that evaluating the hybrid functional needs significantly more computing effort. When spin-orbit coupling (SOC) is taken into account, the non-collinear spin structure increases computing effort by at least eight times. As a result, hybrid functional calculations with SOC are intractable in most cases. In this paper, we present an approximate solution to this problem by developing an efficient method based on a mixed linear combination of atomic orbital (LCAO) scheme. We demonstrate the power of this method using several examples and we show that the results compare very well with those of direct hybrid functional calculations with SOC, yet the method only requires a computing effort similar to that without SOC. The presented technique provides a good balance between computing efficiency and accuracy, and it can be extended to magnetic materials.

Multimodal Neuroimaging of Fronto-limbic Structure and Function Associated with Suicide Attempts in Adolescents and Young Adults with Bipolar Disorder

PubMed Central

Johnston, Jennifer A. Y.; Wang, Fei; Liu, Jie; Blond, Benjamin N.; Wallace, Amanda; Liu, Jiacheng; Spencer, Linda; Cox Lippard, Elizabeth T.; Purves, Kirstin L.; Landeros-Weisenberger, Angeli; Hermes, Eric; Pittman, Brian; Zhang, Sheng; King, Robert; Martin, Andrés; Oquendo, Maria A.; Blumberg, Hilary P.

2018-01-01

Objective Bipolar disorder is associated with high risk for suicide behavior that often develops in adolescence/young adulthood. Elucidation of involved neural systems is critical for prevention. This study of adolescents/young adults with bipolar disorder with and without history of suicide attempts combines structural, diffusion tensor and functional magnetic resonance imaging methods to investigate implicated abnormalities in structural and functional connectivity within fronto-limbic systems. Method Participants with bipolar disorder included 26 with a prior suicide attempt and 42 without attempts. Regional gray matter volume, white matter integrity and functional connectivity during processing of emotional stimuli were compared between groups and differences were explored for relationships between imaging modalities and associations with suicide-related symptoms and behaviors. Results Compared to the non-attempter group, the attempter group showed reductions in gray matter volume in orbitofrontal cortex, hippocampus and cerebellum; white matter integrity in uncinate fasciculus, ventral frontal and right cerebellum regions; and amygdala functional connectivity to left ventral and right rostral prefrontal cortex (p<0.05, corrected). In exploratory analyses, among attempters, right rostral prefrontal connectivity was negatively correlated with suicidal ideation (p<0.05), and left ventral prefrontal connectivity was negatively correlated with attempt lethality (p<0.05). Conclusions Adolescent/young adult suicide attempters with bipolar disorder demonstrate less gray matter volume and decreased structural and functional connectivity in a ventral fronto-limbic neural system subserving emotion regulation. Among suicide attempters, reductions in amygdala-prefrontal functional connectivity may be associated with severity of suicide ideation and attempt lethality. PMID:28135845

MSTor: A program for calculating partition functions, free energies, enthalpies, entropies, and heat capacities of complex molecules including torsional anharmonicity

NASA Astrophysics Data System (ADS)

Zheng, Jingjing; Mielke, Steven L.; Clarkson, Kenneth L.; Truhlar, Donald G.

2012-08-01

We present a Fortran program package, MSTor, which calculates partition functions and thermodynamic functions of complex molecules involving multiple torsional motions by the recently proposed MS-T method. This method interpolates between the local harmonic approximation in the low-temperature limit, and the limit of free internal rotation of all torsions at high temperature. The program can also carry out calculations in the multiple-structure local harmonic approximation. The program package also includes six utility codes that can be used as stand-alone programs to calculate reduced moment of inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes for torsional subdomains defined by Voronoi tessellation of the conformational subspace, to generate template input files, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Catalogue identifier: AEMF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 77 434 No. of bytes in distributed program, including test data, etc.: 3 264 737 Distribution format: tar.gz Programming language: Fortran 90, C, and Perl Computer: Itasca (HP Linux cluster, each node has two-socket, quad-core 2.8 GHz Intel Xeon X5560 “Nehalem EP” processors), Calhoun (SGI Altix XE 1300 cluster, each node containing two quad-core 2.66 GHz Intel Xeon “Clovertown”-class processors sharing 16 GB of main memory), Koronis (Altix UV 1000 server with 190 6-core Intel Xeon X7542 “Westmere” processors at 2.66 GHz), Elmo (Sun Fire X4600 Linux cluster with AMD Opteron cores), and Mac Pro (two 2.8 GHz Quad-core Intel Xeon processors) Operating system: Linux/Unix/Mac OS RAM: 2 Mbytes Classification: 16.3, 16.12, 23 Nature of problem: Calculation of the partition functions and thermodynamic functions (standard-state energy, enthalpy, entropy, and free energy as functions of temperatures) of complex molecules involving multiple torsional motions. Solution method: The multi-structural approximation with torsional anharmonicity (MS-T). The program also provides results for the multi-structural local harmonic approximation [1]. Restrictions: There is no limit on the number of torsions that can be included in either the Voronoi calculation or the full MS-T calculation. In practice, the range of problems that can be addressed with the present method consists of all multi-torsional problems for which one can afford to calculate all the conformations and their frequencies. Unusual features: The method can be applied to transition states as well as stable molecules. The program package also includes the hull program for the calculation of Voronoi volumes and six utility codes that can be used as stand-alone programs to calculate reduced moment-of-inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes for torsional subdomain defined by Voronoi tessellation of the conformational subspace, to generate template input files, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Additional comments: The program package includes a manual, installation script, and input and output files for a test suite. Running time: There are 24 test runs. The running time of the test runs on a single processor of the Itasca computer is less than 2 seconds. J. Zheng, T. Yu, E. Papajak, I.M. Alecu, S.L. Mielke, D.G. Truhlar, Practical methods for including torsional anharmonicity in thermochemical calculations of complex molecules: The internal-coordinate multi-structural approximation, Phys. Chem. Chem. Phys. 13 (2011) 10885-10907.

Structural landscape of base pairs containing post-transcriptional modifications in RNA

PubMed Central

Seelam, Preethi P.; Sharma, Purshotam

2017-01-01

Base pairs involving post-transcriptionally modified nucleobases are believed to play important roles in a wide variety of functional RNAs. Here we present our attempts toward understanding the structural and functional role of naturally occurring modified base pairs using a combination of X-ray crystal structure database analysis, sequence analysis, and advanced quantum chemical methods. Our bioinformatics analysis reveals that despite their presence in all major secondary structural elements, modified base pairs are most prevalent in tRNA crystal structures and most commonly involve guanine or uridine modifications. Further, analysis of tRNA sequences reveals additional examples of modified base pairs at structurally conserved tRNA regions and highlights the conservation patterns of these base pairs in three domains of life. Comparison of structures and binding energies of modified base pairs with their unmodified counterparts, using quantum chemical methods, allowed us to classify the base modifications in terms of the nature of their electronic structure effects on base-pairing. Analysis of specific structural contexts of modified base pairs in RNA crystal structures revealed several interesting scenarios, including those at the tRNA:rRNA interface, antibiotic-binding sites on the ribosome, and the three-way junctions within tRNA. These scenarios, when analyzed in the context of available experimental data, allowed us to correlate the occurrence and strength of modified base pairs with their specific functional roles. Overall, our study highlights the structural importance of modified base pairs in RNA and points toward the need for greater appreciation of the role of modified bases and their interactions, in the context of many biological processes involving RNA. PMID:28341704

Mapping the Structure-Function Relationship in Glaucoma and Healthy Patients Measured with Spectralis OCT and Humphrey Perimetry

PubMed Central

Muñoz–Negrete, Francisco J.; Oblanca, Noelia; Rebolleda, Gema

2018-01-01

Purpose To study the structure-function relationship in glaucoma and healthy patients assessed with Spectralis OCT and Humphrey perimetry using new statistical approaches. Materials and Methods Eighty-five eyes were prospectively selected and divided into 2 groups: glaucoma (44) and healthy patients (41). Three different statistical approaches were carried out: (1) factor analysis of the threshold sensitivities (dB) (automated perimetry) and the macular thickness (μm) (Spectralis OCT), subsequently applying Pearson's correlation to the obtained regions, (2) nonparametric regression analysis relating the values in each pair of regions that showed significant correlation, and (3) nonparametric spatial regressions using three models designed for the purpose of this study. Results In the glaucoma group, a map that relates structural and functional damage was drawn. The strongest correlation with visual fields was observed in the peripheral nasal region of both superior and inferior hemigrids (r = 0.602 and r = 0.458, resp.). The estimated functions obtained with the nonparametric regressions provided the mean sensitivity that corresponds to each given macular thickness. These functions allowed for accurate characterization of the structure-function relationship. Conclusions Both maps and point-to-point functions obtained linking structure and function damage contribute to a better understanding of this relationship and may help in the future to improve glaucoma diagnosis. PMID:29850196

Resolution of structural heterogeneity in dynamic crystallography

PubMed Central

Ren, Zhong; Chan, Peter W. Y.; Moffat, Keith; Pai, Emil F.; Royer, William E.; Šrajer, Vukica; Yang, Xiaojing

2013-01-01

Dynamic behavior of proteins is critical to their function. X-­ray crystallography, a powerful yet mostly static technique, faces inherent challenges in acquiring dynamic information despite decades of effort. Dynamic ‘structural changes’ are often indirectly inferred from ‘structural differences’ by comparing related static structures. In contrast, the direct observation of dynamic structural changes requires the initiation of a biochemical reaction or process in a crystal. Both the direct and the indirect approaches share a common challenge in analysis: how to interpret the structural heterogeneity intrinsic to all dynamic processes. This paper presents a real-space approach to this challenge, in which a suite of analytical methods and tools to identify and refine the mixed structural species present in multiple crystallographic data sets have been developed. These methods have been applied to representative scenarios in dynamic crystallography, and reveal structural information that is otherwise difficult to interpret or inaccessible using conventional methods. PMID:23695239

Resolution of structural heterogeneity in dynamic crystallography.

PubMed

Ren, Zhong; Chan, Peter W Y; Moffat, Keith; Pai, Emil F; Royer, William E; Šrajer, Vukica; Yang, Xiaojing

2013-06-01

Dynamic behavior of proteins is critical to their function. X-ray crystallography, a powerful yet mostly static technique, faces inherent challenges in acquiring dynamic information despite decades of effort. Dynamic `structural changes' are often indirectly inferred from `structural differences' by comparing related static structures. In contrast, the direct observation of dynamic structural changes requires the initiation of a biochemical reaction or process in a crystal. Both the direct and the indirect approaches share a common challenge in analysis: how to interpret the structural heterogeneity intrinsic to all dynamic processes. This paper presents a real-space approach to this challenge, in which a suite of analytical methods and tools to identify and refine the mixed structural species present in multiple crystallographic data sets have been developed. These methods have been applied to representative scenarios in dynamic crystallography, and reveal structural information that is otherwise difficult to interpret or inaccessible using conventional methods.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Crystallite size strain analysis of nanocrystalline La0.7Sr0.3MnO3 perovskite by Williamson-Hall plot method

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Verma, Narendra Kumar; Singh, Chandra Bhal; Singh, Akhilesh Kumar

2018-04-01

The nanocrystalline Sr-doped LaMnO3 (La0.7Sr0.3MnO3 = LSMO) perovskite manganites having different crystallite size were synthesized using the nitrate-glycine auto-combustion method. The phase purity of the manganites was checked by X-ray diffraction (XRD) measurement. The XRD patterns of the sample reveal that La0.7S0.3MnO3 crystallizes into rhombohedral crystal structure with space group R-3c. The size-dependence of structural lattice parameters have been investigated with the help of Rietveld refinement. The structural parameters increase as a function of crystallite size. The crystallite-size and internal strain as a function of crystallite-size have been calculated using Williamson-Hall plot.

Polyphosphazine-based polymer materials

DOEpatents

Fox, Robert V.; Avci, Recep; Groenewold, Gary S.

2010-05-25

Methods of removing contaminant matter from porous materials include applying a polymer material to a contaminated surface, irradiating the contaminated surface to cause redistribution of contaminant matter, and removing at least a portion of the polymer material from the surface. Systems for decontaminating a contaminated structure comprising porous material include a radiation device configured to emit electromagnetic radiation toward a surface of a structure, and at least one spray device configured to apply a capture material onto the surface of the structure. Polymer materials that can be used in such methods and systems include polyphosphazine-based polymer materials having polyphosphazine backbone segments and side chain groups that include selected functional groups. The selected functional groups may include iminos, oximes, carboxylates, sulfonates, .beta.-diketones, phosphine sulfides, phosphates, phosphites, phosphonates, phosphinates, phosphine oxides, monothio phosphinic acids, and dithio phosphinic acids.

Molecular structure and vibrational spectra of Irinotecan: a density functional theoretical study.

PubMed

Chinna Babu, P; Sundaraganesan, N; Sudha, S; Aroulmoji, V; Murano, E

2012-12-01

The solid phase FTIR and FT-Raman spectra of Irinotecan have been recorded in the regions 400-4000 and 50-4000 cm(-1), respectively. The spectra were interpreted in terms of fundamentals modes, combination and overtone bands. The structure of the molecule was optimized and the structural characteristics were determined by density functional theory (DFT) using B3LYP method with 6-31G(d) as basis set. The vibrational frequencies were calculated for Irinotecan by DFT method and were compared with the experimental frequencies, which yield good agreement between observed and calculated frequencies. The infrared spectrum was also simulated from the calculated intensities. Besides, molecular electrostatic potential (MEP), frontier molecular orbitals (FMO) analysis were investigated using theoretical calculations. Copyright © 2012 Elsevier B.V. All rights reserved.

Nuclear magnetic and nuclear quadrupole resonance parameters of β-carboline derivatives calculated using density functional theory

NASA Astrophysics Data System (ADS)

Ahmadinejad, Neda; Tari, Mostafa Talebi

2017-04-01

A density functional theory (DFT) calculations using B3LYP/6-311++G( d,p) method were carried out to investigate the relative stability of the molecules of β-carboline derivatives such as harmaline, harmine, harmalol, harmane and norharmane. Calculated nuclear quadrupole resonance (NQR) parameters were used to determine the 14N nuclear quadrupole coupling constant χ, asymmetry parameter η and EFG tensor ( q zz ). For better understanding of the electronic structure of β-carboline derivatives, natural bond orbital (NBO) analysis, isotropic and anisotropic NMR chemical shieldings were calculated for 14N nuclei using GIAO method for the optimized structures. The NBO analysis shows that pyrrole ring nitrogen (N9) atom has greater tendency than pyridine ring nitrogen (N2) atom to participate in resonance interactions and aromaticity development in the all of these structures. The NMR and NQR parameters were studied in order to find the correlations between electronic structure and the structural stability of the studied molecules.

Design oriented structural analysis

NASA Technical Reports Server (NTRS)

Giles, Gary L.

1994-01-01

Desirable characteristics and benefits of design oriented analysis methods are described and illustrated by presenting a synoptic description of the development and uses of the Equivalent Laminated Plate Solution (ELAPS) computer code. ELAPS is a design oriented structural analysis method which is intended for use in the early design of aircraft wing structures. Model preparation is minimized by using a few large plate segments to model the wing box structure. Computational efficiency is achieved by using a limited number of global displacement functions that encompass all segments over the wing planform. Coupling with other codes is facilitated since the output quantities such as deflections and stresses are calculated as continuous functions over the plate segments. Various aspects of the ELAPS development are discussed including the analytical formulation, verification of results by comparison with finite element analysis results, coupling with other codes, and calculation of sensitivity derivatives. The effectiveness of ELAPS for multidisciplinary design application is illustrated by describing its use in design studies of high speed civil transport wing structures.

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

A new wavelet transform to sparsely represent cortical current densities for EEG/MEG inverse problems.

PubMed

Liao, Ke; Zhu, Min; Ding, Lei

2013-08-01

The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Study of structure defect interactions in aluminum by the acoustic method. [internal friction in pure aluminum

NASA Technical Reports Server (NTRS)

Nicolaescu, I. I.

1974-01-01

Using echo pulse and resonance rod methods, internal friction in pure aluminum was studied as a function of frequency, hardening temperature, time (internal friction relaxation) and impurity content. These studies led to the conclusion that internal friction in these materials depends strongly on dislocation structure and on elastic interactions between structure defects. It was found experimentally that internal friction relaxation depends on the cooling rate and on the impurity content. Some parameters of the dislocation structure and of the diffusion process were determined. It is shown that the dislocated dependence of internal friction can be used as a method of nondestructive testing of the impurity content of high-purity materials.

Novel Routes to Tune Thermal Conductivities and Thermoelectric Properties of Materials

DTIC Science & Technology

2012-11-15

expand the possibilities of borides as functional compou nds. A series of indium-free novel TCO compounds with novel crystal structures, has...powerful methods for modification were demonstrated in the borides , silicides and oxides. Introduction: The goal of this project is to...the possibility to modify the crystal structures can expand the possibilities of borides as functional compounds. A series of indium-free novel TCO

Models of determining deformations

NASA Astrophysics Data System (ADS)

Gladilin, V. N.

2016-12-01

In recent years, a lot of functions designed to determine deformation values that occur mostly as a result of settlement of structures and industrial equipment. Some authors suggest such advanced mathematical functions approximating deformations as general methods for the determination of deformations. The article describes models of deformations as physical processes. When comparing static, cinematic and dynamic models, it was found that the dynamic model reflects the deformation of structures and industrial equipment most reliably.

Structure functions in decomposing Au-Pt systems

NASA Astrophysics Data System (ADS)

Glas, R.; Blaschko, O.; Rosta, L.

1992-09-01

The evolution of Au-Pt alloys quenched within the miscibility gap is investigated by small-angle neutron-scattering techniques. Moreover, in the vicinity of fundamental Bragg reflections the evolution of ``sideband'' satellites induced by a lattice-parameter modulation connected with the precipitation pattern is investigated by diffuse scattering methods. Structure functions are evaluated for a series of concentrations within the miscibility gap and compared to recent results of the literature.

Calculation of electrostatic fields in periodic structures of complex shape

NASA Technical Reports Server (NTRS)

Kravchenko, V. F.

1978-01-01

A universal algorithm is presented for calculating electrostatic fields in an infinite periodic structure consisting of electrodes of arbitrary shape which are located in mirror-symmetrical manner along the axis of electron-beam propagation. The method is based on the theory of R-functions, and the differential operators which are derived on the basis of the functions. Numerical results are presented and the accuracy of the results is examined.

Power Series Approximation for the Correlation Kernel Leading to Kohn-Sham Methods Combining Accuracy, Computational Efficiency, and General Applicability

NASA Astrophysics Data System (ADS)

Erhard, Jannis; Bleiziffer, Patrick; Görling, Andreas

2016-09-01

A power series approximation for the correlation kernel of time-dependent density-functional theory is presented. Using this approximation in the adiabatic-connection fluctuation-dissipation (ACFD) theorem leads to a new family of Kohn-Sham methods. The new methods yield reaction energies and barriers of unprecedented accuracy and enable a treatment of static (strong) correlation with an accuracy of high-level multireference configuration interaction methods but are single-reference methods allowing for a black-box-like handling of static correlation. The new methods exhibit a better scaling of the computational effort with the system size than rivaling wave-function-based electronic structure methods. Moreover, the new methods do not suffer from the problem of singularities in response functions plaguing previous ACFD methods and therefore are applicable to any type of electronic system.

Beyond sex differences: new approaches for thinking about variation in brain structure and function.

PubMed

Joel, Daphna; Fausto-Sterling, Anne

2016-02-19

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. © 2016 The Author(s).

Accurate critical pressures for structural phase transitions of group IV, III-V, and II-VI compounds from the SCAN density functional

NASA Astrophysics Data System (ADS)

Shahi, Chandra; Sun, Jianwei; Perdew, John P.

2018-03-01

Most of the group IV, III-V, and II-VI compounds crystallize in semiconductor structures under ambient conditions. Upon application of pressure, they undergo structural phase transitions to more closely packed structures, sometimes metallic phases. We have performed density functional calculations using projector augmented wave (PAW) pseudopotentials to determine the transition pressures for these transitions within the local density approximation (LDA), the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA), and the strongly constrained and appropriately normed (SCAN) meta-GGA. LDA underestimates the transition pressure for most of the studied materials. PBE under- or overestimates in many cases. SCAN typically corrects the errors of LDA and PBE for the transition pressure. The accuracy of SCAN is comparable to that of computationally expensive methods like the hybrid functional HSE06, the random phase approximation (RPA), and quantum Monte Carlo (QMC), in cases where calculations with these methods have been reported, but at a more modest computational cost. The improvement from LDA to PBE to SCAN is especially clearcut and dramatic for covalent semiconductor-metal transitions, as for Si and Ge, where it reflects the increasing relative stabilization of the covalent semiconducting phases under increasing functional sophistication.

Decoupling the NLO-coupled QED⊗QCD, DGLAP evolution equations, using Laplace transform method

NASA Astrophysics Data System (ADS)

Mottaghizadeh, Marzieh; Eslami, Parvin; Taghavi-Shahri, Fatemeh

2017-05-01

We analytically solved the QED⊗QCD-coupled DGLAP evolution equations at leading order (LO) quantum electrodynamics (QED) and next-to-leading order (NLO) quantum chromodynamics (QCD) approximations, using the Laplace transform method and then computed the proton structure function in terms of the unpolarized parton distribution functions. Our analytical solutions for parton densities are in good agreement with those from CT14QED (1.2952 < Q2 < 1010) (Ref. 6) global parametrizations and APFEL (A PDF Evolution Library) (2 < Q2 < 108) (Ref. 4). We also compared the proton structure function, F2p(x,Q2), with the experimental data released by the ZEUS and H1 collaborations at HERA. There is a nice agreement between them in the range of low and high x and Q2.

Spatial Control of Functional Response in 4D-Printed Active Metallic Structures

PubMed Central

Ma, Ji; Franco, Brian; Tapia, Gustavo; Karayagiz, Kubra; Johnson, Luke; Liu, Jun; Arroyave, Raymundo; Karaman, Ibrahim; Elwany, Alaa

2017-01-01

We demonstrate a method to achieve local control of 3-dimensional thermal history in a metallic alloy, which resulted in designed spatial variations in its functional response. A nickel-titanium shape memory alloy part was created with multiple shape-recovery stages activated at different temperatures using the selective laser melting technique. The multi-stage transformation originates from differences in thermal history, and thus the precipitate structure, at various locations created from controlled variations in the hatch distance within the same part. This is a first example of precision location-dependent control of thermal history in alloys beyond the surface, and utilizes additive manufacturing techniques as a tool to create materials with novel functional response that is difficult to achieve through conventional methods. PMID:28429796

Theoretical investigations on diamondoids (CnHm, n = 10-41): Nomenclature, structural stabilities, and gap distributions

NASA Astrophysics Data System (ADS)

Wang, Ya-Ting; Zhao, Yu-Jun; Liao, Ji-Hai; Yang, Xiao-Bao

2018-01-01

Combining the congruence check and the first-principles calculations, we have systematically investigated the structural stabilities and gap distributions of possible diamondoids (CnHm) with the carbon numbers (n) from 10 to 41. A simple method for the nomenclature is proposed, which can be used to distinguish and screen the candidates with high efficiency. Different from previous theoretical studies, the possible diamondoids can be enumerated according to our nomenclature, without any pre-determination from experiments. The structural stabilities and electronic properties have been studied by density functional based tight binding and first-principles methods, where a nearly linear correlation is found between the energy gaps obtained by these two methods. According to the formation energy of structures, we have determined the stable configurations as a function of chemical potential. The maximum and minimum energy gaps are found to be dominated by the shape of diamondoids for clusters with a given number of carbon atoms, while the gap decreases in general as the size increases due to the quantum confinement.

Effective dimension reduction for sparse functional data

PubMed Central

YAO, F.; LEI, E.; WU, Y.

2015-01-01

Summary We propose a method of effective dimension reduction for functional data, emphasizing the sparse design where one observes only a few noisy and irregular measurements for some or all of the subjects. The proposed method borrows strength across the entire sample and provides a way to characterize the effective dimension reduction space, via functional cumulative slicing. Our theoretical study reveals a bias-variance trade-off associated with the regularizing truncation and decaying structures of the predictor process and the effective dimension reduction space. A simulation study and an application illustrate the superior finite-sample performance of the method. PMID:26566293

Analysis of the structural, electronic and optic properties of Ni doped MgSiP{sub 2} semiconductor chalcopyrite compound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kocak, Belgin, E-mail: koakbelgin@gmail.com; Ciftci, Yasemin Oztekin, E-mail: yasemin@gazi.edu.tr

2016-03-25

The structural, electronic band structure and optic properties of the Ni doped MgSiP{sub 2} chalcopyrite compound have been performed by using first-principles method in the density functional theory (DFT) as implemented in Vienna Ab-initio Simulation Package (VASP). The generalized gradient approximation (GGA) in the scheme of Perdew, Burke and Ernzerhof (PBE) is used for the exchange and correlation functional. The present lattice constant (a) follows generally the Vegard’s law. The electronic band structure, total and partial density of states (DOS and PDOS) are calculated. We present data for the frequency dependence of imaginary and real parts of dielectric functions ofmore » Ni doped MgSiP{sub 2}. For further investigation of the optical properties the reflectivity, refractive index, extinction coefficient and electron energy loss function are also predicted. Our obtained results indicate that the lattice constants, electronic band structure and optical properties of this compound are dependent on the substitution concentration of Ni.« less

Functional Performances of CuZnAl Shape Memory Alloy Open-Cell Foams

NASA Astrophysics Data System (ADS)

Biffi, C. A.; Casati, R.; Bassani, P.; Tuissi, A.

2018-01-01

Shape memory alloys (SMAs) with cellular structure offer a unique mixture of thermo-physical-mechanical properties. These characteristics can be tuned by changing the pore size and make the shape memory metallic foams very attractive for developing new devices for structural and functional applications. In this work, CuZnAl SMA foams were produced through the liquid infiltration of space holder method. In comparison, a conventional CuZn brass alloy was foamed trough the same method. Functional performances were studied on both bulk and foamed SMA specimens. Calorimetric response shows similar martensitic transformation (MT) below 0 °C. Compressive response of CuZnAl revealed that mechanical behavior is strongly affected by sample morphology and that damping capacity of metallic foam is increased above the MT temperatures. The shape memory effect was detected in the CuZnAl foams. The conventional brass shows a compressive response similar to that of the martensitic CuZnAl, in which plastic deformation accumulation occurs up to the cellular structure densification after few thermal cycles.

Looking at the Disordered Proteins through the Computational Microscope

PubMed Central

2018-01-01

Intrinsically disordered proteins (IDPs) have attracted wide interest over the past decade due to their surprising prevalence in the proteome and versatile roles in cell physiology and pathology. A large selection of IDPs has been identified as potential targets for therapeutic intervention. Characterizing the structure–function relationship of disordered proteins is therefore an essential but daunting task, as these proteins can adapt transient structure, necessitating a new paradigm for connecting structural disorder to function. Molecular simulation has emerged as a natural complement to experiments for atomic-level characterizations and mechanistic investigations of this intriguing class of proteins. The diverse range of length and time scales involved in IDP function requires performing simulations at multiple levels of resolution. In this Outlook, we focus on summarizing available simulation methods, along with a few interesting example applications. We also provide an outlook on how these simulation methods can be further improved in order to provide a more accurate description of IDP structure, binding, and assembly.

Structural Refinement of Proteins by Restrained Molecular Dynamics Simulations with Non-interacting Molecular Fragments.

PubMed

Shen, Rong; Han, Wei; Fiorin, Giacomo; Islam, Shahidul M; Schulten, Klaus; Roux, Benoît

2015-10-01

The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels), each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD) of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good agreement with the consensus model of the resting state VSD and the spin-spin distance histograms from ESR/DEER experiments on T4 lysozyme are accurately reproduced.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE PAGES

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

2017-04-26

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

Computational Investigation of the Geometrical and Electronic Structures of VGen-/0 (n = 1-4) Clusters by Density Functional Theory and Multiconfigurational CASSCF/CASPT2 Method.

PubMed

Tran, Van Tan; Nguyen, Minh Thao; Tran, Quoc Tri

2017-10-12

Density functional theory and the multiconfigurational CASSCF/CASPT2 method have been employed to study the low-lying states of VGe n -/0 (n = 1-4) clusters. For VGe -/0 and VGe 2 -/0 clusters, the relative energies and geometrical structures of the low-lying states are reported at the CASSCF/CASPT2 level. For the VGe 3 -/0 and VGe 4 -/0 clusters, the computational results show that due to the large contribution of the Hartree-Fock exact exchange, the hybrid B3LYP, B3PW91, and PBE0 functionals overestimate the energies of the high-spin states as compared to the pure GGA BP86 and PBE functionals and the CASPT2 method. On the basis of the pure GGA BP86 and PBE functionals and the CASSCF/CASPT2 results, the ground states of anionic and neutral clusters are defined, the relative energies of the excited states are computed, and the electron detachment energies of the anionic clusters are evaluated. The computational results are employed to give new assignments for all features in the photoelectron spectra of VGe 3 - and VGe 4 - clusters.

Extracting a shape function for a signal with intra-wave frequency modulation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

PubMed

Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

2017-01-01

As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Automated, quantitative measures of grey and white matter lesion burden correlates with motor and cognitive function in children with unilateral cerebral palsy.

PubMed

Pagnozzi, Alex M; Dowson, Nicholas; Doecke, James; Fiori, Simona; Bradley, Andrew P; Boyd, Roslyn N; Rose, Stephen

2016-01-01

White and grey matter lesions are the most prevalent type of injury observable in the Magnetic Resonance Images (MRIs) of children with cerebral palsy (CP). Previous studies investigating the impact of lesions in children with CP have been qualitative, limited by the lack of automated segmentation approaches in this setting. As a result, the quantitative relationship between lesion burden has yet to be established. In this study, we perform automatic lesion segmentation on a large cohort of data (107 children with unilateral CP and 18 healthy children) with a new, validated method for segmenting both white matter (WM) and grey matter (GM) lesions. The method has better accuracy (94%) than the best current methods (73%), and only requires standard structural MRI sequences. Anatomical lesion burdens most predictive of clinical scores of motor, cognitive, visual and communicative function were identified using the Least Absolute Shrinkage and Selection operator (LASSO). The improved segmentations enabled identification of significant correlations between regional lesion burden and clinical performance, which conform to known structure-function relationships. Model performance was validated in an independent test set, with significant correlations observed for both WM and GM regional lesion burden with motor function (p < 0.008), and between WM and GM lesions alone with cognitive and visual function respectively (p < 0.008). The significant correlation of GM lesions with functional outcome highlights the serious implications GM lesions, in addition to WM lesions, have for prognosis, and the utility of structural MRI alone for quantifying lesion burden and planning therapy interventions.

Towards Full-Waveform Ambient Noise Inversion

NASA Astrophysics Data System (ADS)

Sager, K.; Ermert, L. A.; Boehm, C.; Fichtner, A.

2016-12-01

Noise tomography usually works under the assumption that the inter-station ambient noise correlation is equal to a scaled version of the Green function between the two receivers. This assumption, however, is only met under specific conditions, e.g. wavefield diffusivity and equipartitioning, or the isotropic distribution of both mono- and dipolar uncorrelated noise sources. These assumptions are typically not satisfied in the Earth. This inconsistency inhibits the exploitation of the full waveform information contained in noise correlations in order to constrain Earth structure and noise generation. To overcome this limitation, we attempt to develop a method that consistently accounts for the distribution of noise sources, 3D heterogeneous Earth structure and the full seismic wave propagation physics. This is intended to improve the resolution of tomographic images, to refine noise source location, and thereby to contribute to a better understanding of noise generation. We introduce an operator-based formulation for the computation of correlation functions and apply the continuous adjoint method that allows us to compute first and second derivatives of misfit functionals with respect to source distribution and Earth structure efficiently. Based on these developments we design an inversion scheme using a 2D finite-difference code. To enable a joint inversion for noise sources and Earth structure, we investigate the following aspects: The capability of different misfit functionals to image wave speed anomalies and source distribution. Possible source-structure trade-offs, especially to what extent unresolvable structure can be mapped into the inverted noise source distribution and vice versa. In anticipation of real-data applications, we present an extension of the open-source waveform modelling and inversion package Salvus, which allows us to compute correlation functions in 3D media with heterogeneous noise sources at the surface.

Patterning nanofibrils through the templated growth of multiple modified amyloid peptides

PubMed Central

Sakai, Hiroki; Watanabe, Ken; Kudoh, Fuki; Kamada, Rui; Chuman, Yoshiro; Sakaguchi, Kazuyasu

2016-01-01

There has been considerable interest in the patterning of functionalized nanowires because of the potential applications of these materials to the construction of nanodevices. A variety of biomolecular building blocks containing amyloid peptides have been used to functionalize nanowires. However, the patterning of self-assembled nanowires can be challenging because of the difficulties associated with controlling the self-assembly of these functionalized building blocks. Herein, we present a versatile approach for the patterning of nanowires based on the combination of templated fibril growth with a versatile functionalization method using our structure-controllable amyloid peptides (SCAPs). Using this approach, we have succeeded in the formation of multi-type nanowires with tandem domain structures in high yields. Given that the mixing-SCAP method can lead to the formation of tandem fibrils, it is noteworthy that our method allowed us to control the initiation of fibril formation from the gold nanoparticles, which were attached to a short fibril as initiation points. This approach could be used to prepare a wide variety of fibril patterns, and therefore holds great potential for the development of novel self-assembled nanodevices. PMID:27559011

3D receiver function Kirchhoff depth migration image of Cascadia subduction slab weak zone

NASA Astrophysics Data System (ADS)

Cheng, C.; Allen, R. M.; Bodin, T.; Tauzin, B.

2016-12-01

We have developed a highly computational efficient algorithm of applying 3D Kirchhoff depth migration to telesismic receiver function data. Combine primary PS arrival with later multiple arrivals we are able to reveal a better knowledge about the earth discontinuity structure (transmission and reflection). This method is highly useful compare with traditional CCP method when dipping structure is met during the imaging process, such as subduction slab. We apply our method to the reginal Cascadia subduction zone receiver function data and get a high resolution 3D migration image, for both primary and multiples. The image showed us a clear slab weak zone (slab hole) in the upper plate boundary under Northern California and the whole Oregon. Compare with previous 2D receiver function image from 2D array(CAFE and CASC93), the position of the weak zone shows interesting conherency. This weak zone is also conherent with local seismicity missing and heat rising, which lead us to think about and compare with the ocean plate stucture and the hydralic fluid process during the formation and migration of the subduction slab.

Will isomalto-oligosaccharides, a well-established functional food in Asia, break through the European and American market? The status of knowledge on these prebiotics.

PubMed

Goffin, Dorothee; Delzenne, Nathalie; Blecker, Christophe; Hanon, Emilien; Deroanne, Claude; Paquot, Michel

2011-05-01

This critical review article presents the current state of knowledge on isomalto-oligosaccharides, some well known functional oligosaccharides in Asia, to evaluate their potential as emergent prebiotics in the American and European functional food market. It includes first a unique inventory of the different families of compounds which have been considered as IMOs and their specific structure. A description has been given of the different production methods including the involved enzymes and their specific activities, the substrates, and the types of IMOs produced. Considering the structural complexity of IMO products, specific characterization methods are described, as well as purification methods which enable the body to get rid of digestible oligosaccharides. Finally, an extensive review of their techno-functional and nutritional properties enables placing IMOs inside the growing prebiotic market. This review is of particular interest considering that IMO commercialization in America and Europe is a topical subject due to the recent submission by Bioneutra Inc. (Canada) of a novel food file to the UK Food Standards Agency, as well as several patents for IMO production.

Methods for Evaluating the Temperature Structure-Function Parameter Using Unmanned Aerial Systems and Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Wainwright, Charlotte E.; Bonin, Timothy A.; Chilson, Phillip B.; Gibbs, Jeremy A.; Fedorovich, Evgeni; Palmer, Robert D.

2015-05-01

Small-scale turbulent fluctuations of temperature are known to affect the propagation of both electromagnetic and acoustic waves. Within the inertial-subrange scale, where the turbulence is locally homogeneous and isotropic, these temperature perturbations can be described, in a statistical sense, using the structure-function parameter for temperature, . Here we investigate different methods of evaluating , using data from a numerical large-eddy simulation together with atmospheric observations collected by an unmanned aerial system and a sodar. An example case using data from a late afternoon unmanned aerial system flight on April 24 2013 and corresponding large-eddy simulation data is presented and discussed.